On successful Completion of the course you will get a sound understanding of:

• Review and describe the characteristics of a data warehouse
• Describe all of the components of an enterprise architecture
• Examine different data warehouse architectures
• List various types of data that may be considered for the warehouse
• Identify the requirements of a decision support query environment
• Outline the steps to building a data warehouse
• Describe how to determine the first increment according to the value proposition and return on investment
• Know the different modeling techniques, specifically entity relationship modeling
• Identify the modeling conventions and terminology used, specifically in the Oracle environment
• Define metadata and describe why it is important to the warehouse and users
• Identify types of metadata for every aspect of warehouse operation, management, and access
• Identify the organizational and technical uses of metadata
• Evaluate sources for metadata currently in your enterprise
• Conduct gap analysis and appreciate where this occurs in the Data Warehouse Method

In this course Students are introduced to the data warehouse environment in the context of the enterprise architecture. Students learn to identify each component of the architecture and its role in the overall system. Students learn how specific business needs can influence the data warehouse design, and also learn how to translate business issues into subject areas.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors
• Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting
• Get value out of Big Data by using a 5-step process to structure your analysis
• Identify what are and what are not big data problems and be able to recast big data problems as data science questions
• Provide an explanation of the architectural components and programming models used for scalable big data analysis
• Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model
• Install and run a program using Hadoop

This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible; increasing the potential for data to transform our world.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Understanding Big Data
• Business Motivations and Drivers for Big Data Adoption
• Big Data Adoption and Planning Considerations
• Enterprise Technologies and Big Data Business Intelligence
• Storing and Analyzing Big Data
• Big Data Storage Concepts
• Big Data Processing Concepts
• Big Data Storage Technology
• Big Data Analysis Techniques

This course covers the essentials of Big Data, primarily from a business perspective. Businesses need to understand that Big Data is not just about technology—it is also about how these technologies can propel an organization forward. This second set of topics shifts from providing a high-level understanding of Big Data and its business implications to covering key concepts related to the two main Big Data concerns: storage and analysis.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Recognize different data elements in your own work and in everyday life problems
• Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design
• Identify the frequent data operations required for various types of data
• Select a data model to suit the characteristics of your data
• Apply techniques to handle streaming data
• Differentiate between a traditional Database Management System and a Big Data Management System
• Appreciate why there are so many data management systems
• Design a big data information system for an online game company

In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Retrieve data from example database and big data management systems
• Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications
• Identify when a big data problem needs data integration
• Execute simple big data integration and processing on Hadoop and Spark platforms

This course covers Big Data Integration and Processing including the various aspects of data retrieval for NoSQL data, as well as data aggregation and working with data frames. You will be introduced to MongoDB and you will learn how to retrieve data from them.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Define Big Data
• Describe Oracle's Integrated Big Data Solution and its components
• Learn about the Hadoop ecosystem and its components
• Learn about the Oracle Big Data Appliance (BDA)
• Learn about Cloudera's distribution of Hadoop and its core components and the Hadoop ecosystem
• Use the Hadoop Distributed File System (HDFS)
• Understand and the Oracle Big Data Connectors
• Oracle SQL Connector for Hadoop Distributed File System (OSCH)
• Oracle Loader for Hadoop (OLH), and Oracle Data Integrator (ODI)
• Oracle XQuery for Hadoop (OXH)
• Oracle R Advanced Analytics for Hadoop (ORAAH)
• Learn to acquire big data using the Command Line Interface, Flume, and Oracle NoSQL Database
• Process big data using MapReduce, YARN, Hive, Oracle XQuery for Hadoop, Solr, and Spark

This course will assist in preparation for the Oracle Big Data Management Certification Examinations.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Understand Big Data Analysis Techniques
• Understand Graph Theory
• Describe Graph Tools and Technologies
• Understand Neo4j
• Understand Graph Analytics
• Understand Graph Databases
• Model a problem into a graph database and perform analytical tasks over the graph in a scalable manner

This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Gain a high-level understanding of big data and Hadoop
• Understand Hadoop Components: MapReduce and HDFS
• Understand Hadoop Components: YARN and Apache Tez
• Understand HCatalog
• Understand development with Hive
• Understand development with Pig
• Understand development with HBase
• Gain a high-level understanding of Apache Spark
• Understand Resilient Distributed Datasets (RDDs) in Apache Spark
• Understand Spark ML
• launch data analytics applications for companies
• You will be instrumental in getting data from a variety of different sources
• Learn how these data will be parsed in the right formats, assuring that they adhere to data
• Understand data quality standards
• Learn to perform downstream tasks such as reporting or exploratory analytics
• Understand NoSQL Databases

This course will assist in preparation for the Oracle, IBM and Microsoft Big Data Certification Examinations.

Product code: WLN-IDM-PBF<

On successful Completion of the course you will get a sound understanding of:

• Define big data and the business drivers for advanced, big data analytics
• Describe why and how Data Science is different to traditional Business Intelligence
• Describe the roles and skills required in a big data analytics team
• Explain the phases and activities of the data analytics lifecycle and identify the main activities and deliverables
• Explore and make an initial analysis of the data, using R
• Select and execute appropriate advanced analytic methods for candidate selection, categorization, and predictive modeling
• Describe the challenges and tools for analyzing text and other unstructured data
• Describe the importance and benefits of advanced techniques such as in-database analytics and how extensions and other advanced functions add value

The Data Science and Big Data Analytics course educates students to a foundation level on big data and the state of the practice of analytics. The course provides an introduction to big data and a Data Analytics Lifecycle to address business challenges that leverage big data.

Product code: WLN-IDM-PBF<

On successful Completion of the Career Enabler: Introduction to Big Data course you will be able to:

• Store, manage, and analyze unstructured data
• Select the correct big data stores for disparate data sets
• Process large data sets using Hadoop to extract value
• Query large data sets in near real time with Pig and Hive
• Plan and implement a big data strategy for your organization

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Building Enterprise Solutions with MongoDB course you will be able to:

• Develop highly scalable and cost-efficient applications with MongoDB
• Build efficient MongoDB data models for enterprise-scale applications
• Enhance performance with indexing and sharding
• Manage consistency with write concern and read preference
• Process data and compute results with aggregation pipelines and MapReduce

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Data Science with Python course you will be able to:

• What is Python and why is it useful
• The application of Python
• How to define variables
• Sets and conditional statements in Python
• The purpose of having functions in Python
• How to operate on files to read and write data in Python
• How to use pandas, a must have package for anyone attempting data analysis in Python

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Data Science Methodology course you will be able to:

• The major steps involved in tackling a data science problem
• The major steps involved in practicing data science, from forming a concrete business or research problem
• The major steps involved in collecting and analyzing data
• The major steps involved in building a model, and understanding the feedback after model deployment
• How data scientists think through tackling interesting real-world examples

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Introduction to Statistics course you will be able to:

• The major steps involved in tackling a data science problem
• Descriptive statistics
• Variance
• Probability
• Correlation
• Data visualization

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Apache Spark for Scala Analytics course you will be able to:

• how Spark and its ecosystem work
• how to use RDD and DataFrame APIs
• how to connect DataFrames with Spark Stream
• basic concepts of machine learning
• an example of using the Spark MLlib to analyze Twitter stream data

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Data Science with Scala course you will be able to:

• Basic statistics and data types
• Preparing data
• Feature engineering
• Fitting a model
• Pipelines and grid search

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Data Science with Open Source Tools course you will be able to:

• Describe key concepts of Data Science and Machine Learning
• Understand Open Source Data Science tools including R and Python
• Understand Open Source Machine learning Tools and Platforms
• Describe and Understand the Data Scientist Workbench
• Work with Jupyter Notebooks for interactive data science
• Work with Zeppelin Notebooks for interactive data analytics
• Work with RStudio IDE for creating and running R apps
• Work with Seahorse for creating and uploading workflows

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Machine Learning with Python course you will be able to:

• Learn how Statistical Modeling relates to Machine Learning and do a comparison of each
• Learn Real-life examples of Machine learning and how it affects society
• Explore Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction
• Explore Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Building Data Pipelines with Apache Kafka course you will be able to:

• The history of Kafka and its architecture
• How to setup Kafka, create topics, and use command-line tools
• How to configure, setup, and manage Producers and Consumers in the Java API
• Learn about Kafka Connect and how to use Kafka and Spark together
• Learn about the different use cases of Kafka

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Apache Pig Fundamentals course you will be able to:

• The different Pig data types
• The built-in functions used with the LOAD and STORE operators
• The difference between storing and dumping a relation
• The Pig operators
• The Pig evaluation functions

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Big Data Analysis with R & Apache Spark course you will be able to:

• Apache Spark a popular cluster computing framework used for performing large scale data analysis
• Learn about R a popular statistical programming language with a number of extensions that support data processing and machine learning tasks
• Learn about SparkR an R package that provides a light-weight front end to use Apache Spark from R
• Learn how SparkR provides a distributed data frame implementation that supports operations like selection, filtering, aggregation etc. (similar to R data frames, dplyr) but on large datasets
• Learn how SparkR also supports distributed machine learning using MLlib

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SPA-CBT

On successful Completion of the Career Enabler: Machine Learning Fundamentals course you will be able to:

• What Machine Learning is and the different types
• Real-life Machine Learning examples
• The concepts of how each algorithm is affected by its components
• Bias-Variance Trade off
• Model Evaluation (The pros and cons of each)
• How to determine a good approach to setting up an algorithm

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Exploring Hadoop Data Using Hive course you will be able to:

• What Apache Hive is, the Hive architecture, and Hive use cases
• Using Data Definition Language (DDL) to create new Hive databases and tables with a variety of different data types
• Creating partitioned tables that are optimized for Hadoop
• Creating and running a variety of useful Data Manipulation Language (DML) queries against Hive data warehouse
• Using built-in Hive operators and functions to get work done
• Creating your own user-defined functions in Hive

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Mastering Apache Hadoop course you will be able to:

• Comprehend key Hadoop distributors
• Comprehend Hadoop Architecture
• Comprehend HDFS
• Comprehend MapReduce
• Comprehend Backup and Recovery
• Comprehend Monitoring the Cluster
• Comprehend Hadoop Resource Management
• Comprehend Cluster Troubleshooting
• Comprehend Installation, Configuration and Implementation
• Comprehend Hadoop debugging, development, and execution of workflows and algorithms
• leverage Hive, Oozie, Pig, Flume, Sqoop, and other Hadoop ecosystem projects
• Create custom components such as InputFormats and WritableComparables to administer complex data types
• Write and execute joins to link data sets in MapReduce

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-HADO-CBT

On successful Completion of the Career Enabler: Hadoop YARN & Ambari course you will be able to:

• Hadoop fundamentals
• Big Data Approach
• RDBMS Vs. Hadoop
• Introduction to Hadoop
• Hadoop Architecture
• HDFS, YARN, Hadoop setup
• Cloudera Manager
• Ambari
• Job scheduling and monitoring

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-HYAMB-CBT

On successful Completion of the Career Enabler: Sqoop, Flume & Kafka course you will be able to:

• Ingesting Data using Sqoop
• Sqoop properties and commands
• Integrating Sqoop with RDBMS
• Sqoop features and example scenarios
• Ingesting Data using Flume
• Flume properties and setup
• Flume and streaming
• Flume Vs. Kafka

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Pig, Hive & Impala course you will be able to:

• Introduction to Pig
• Pig programming and commands
• Pig interactive shell
• Analyzing complex data using Pig
• Using Pig functions
• Introduction to Hive
• Hive Metastore
• Writing queries using Hive
• Joins and grouping
• Impala architecture
• Impala Vs. Hive
• Queries using Impala

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-PHI-CBT

On successful Completion of the Career Enabler: MapReduce and YARN course you will be able to:

• Describe the MapReduce model v1
• List the limitations of Hadoop 1 and MapReduce 1
• Review the Java code required to handle the Mapper class, the Reducer class, and the program driver needed to access MapReduce
• Describe the YARN model
• Compare YARN / Hadoop 2 / MR2 vs Hadoop 1 / MR1

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-HYAMB-CBT

On successful Completion of the Career Enabler: Apache Spark Fundamentals course you will be able to:

• the purpose of Spark and understand why and when you would use Spark
• how to list and describe the components of the Spark unified stack
• the basics of the Resilient Distributed Dataset, Spark's primary data abstraction
• Learn how Spark performs at speeds up to 100 times faster than Map Reduce for iterative algorithms or interactive data mining.
• Learn how Spark provides in-memory cluster computing for lightning fast speed and supports Java, Python, R, and Scala APIs for ease of development
• Learn how Spark can handle a wide range of data processing scenarios by combining SQL, streaming and complex analytics together seamlessly in the same application
• Learn how Spark runs on top of Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources such as HDFS, Cassandra, HBase, or S3
• how to download and install Spark standalone
• an overview of Scala and Python

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Introdution to Apache Hadoop course you will be able to:

• The definition of Big Data
• The Hadoop architecture including MapReduce and HDFS
• How to use the Hadoop file system shell and the Ambari Console to work with HDFS
• Starting and stopping Hadoop components
• How to add/remove a node to/from a Hadoop Cluster
• Determining how much space is available on each node in a Hadoop cluster
• How to modify Hadoop configuration parameters
• The concepts and purpose of other components such as MapReduce, Pig, Hive, Flume, Sqoop, and Oozie

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Introdution to Apache Hadoop course you will be able to:

• What Big Data is and why we are interested in it
• The characteristics of Big Data
• The phases of Big Data Adoption in companies
• Five high-value uses cases of Big Data
• How to tackle Big Data
• The holistic approach to Big Data
• The Big Data platform

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Fundamentals of Apache Hadoop for Business course you will be able to:

• The definition of Big Data
• The Hadoop architecture including MapReduce and HDFS
• How to use the Hadoop file system shell and the Ambari Console to work with HDFS
• Starting and stopping Hadoop components
• How to add/remove a node to/from a Hadoop Cluster
• Determining how much space is available on each node in a Hadoop cluster
• How to modify Hadoop configuration parameters
• The concepts and purpose of other components such as MapReduce, Pig, Hive, Flume, Sqoop, and Oozie

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Predictive Modeling Fundamentals course you will be able to:

• Understand Data Mining and Machine Learning
• CRISP-DM Methodology
• Introduction to IBM SPSS Modeler
• Explore the SPSS Modeler predictive data mining workbench
• Work in the SPSS Modeler interface

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-PYTH-CBT

On successful Completion of the Career Enabler: Fundamentals of Data Science for Business course you will be able to:

• Defining Data Science
• What is data science?
• The paths to data science
• Caareer advice for a new data scientist
• Understand What do data science people do
• Understand Data science tools and technology
• Understand Data Science in Business
• Understand Use Cases for Data Science

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-FBUS-CBT

On successful Completion of the Career Enabler: Introduction to Data Science course you will be able to:

• Defining Data Science
• What is data science?
• The paths to data science
• Caareer advice for a new data scientist
• Understand What do data science people do
• Understand Data science tools and technology
• Understand Data Science in Business
• Understand Use Cases for Data Science

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-FBUS-CBT

On successful Completion of the Career Enabler: Data Science for Business course you will be able to:

• Describe the entire business analytics cycle including:
• Defining a business objective
• Creating a data analytics solution
• Articulating a recommendation

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-FBUS-CBT

On successful Completion of the Career Enabler: Apache Spark MLlib Essentials course you will be able to:

• Understand Spark MLlib Datatypes
• Understand the difference between Dense and Sparse Data Types
• Understand how to create and use the different matrices that are available in Spark MLlib
• Understand the Algorithms in Spark
• Learn how to instantiate simple Linear Regression and Classification models
• Learn how to instantiate Linear Regression, Support Vector Machines, and Logistic Regression
• Understand Spark MLlib Decision Trees and Random Forests
• Understand Spark MLlib Clustering
• Learn about creating K-Means Clustering models
• Learn about creating Gaussian Mixture Clustering models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-FBUS-CBT

On successful Completion of the Career Enabler: Scala Programming for Data Science Essentials course you will be able to:

• Become a competent user of Scala
• Know and be able to apply the functional programming style in Scala
• Know how to use fundamental Scala tools
• Become confident to start using Scala in production environments

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-FBUS-CBT

On successful Completion of the Career Enabler: Data Analysis with Python Essentials course you will be able to:

• Import data sets
• Clean and prepare data for analysis
• Manipulate pandas DataFrame
• Summarize data
• Build machine learning models using scikit-learn
• Build data pipelines

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-FBUS-CBT

On successful Completion of the Career Enabler: Data Visualisation with Python course you will be able to:

• Data visualization and some of the best practices when creating plots and visuals
• The history and architecture of Matplotlib, and how to do basic plotting with Matplotlib
• Generating different visualization tools using Matplotlib such as line plots, area plots, histograms, bar charts, box plots, and pie charts
• Seaborn, another data visualization library in Python, and how to use it to create attractive statistical graphics
• Folium, and how to use to create maps and visualize geospatial data

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-VIPYTH-CBT

On successful Completion of the Career Enabler: Deep Learning Fundamentals course you will be able to:

• Understand What Deep Learning is
• Understand convolutional neural networks - CNN
• Understand Why is deep learning so powerful and what can it be used for
• Be part of a rapidly growing field in data science; there's no better time than now to get started with neural networks

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-DLF-CBT

On successful Completion of the Career Enabler: Deep Learning with TensorFlow course you will be able to:

• Introduction to TensorFlow
• Linear Regression
• Nonlinear Regression
• Logistic Regression
• Activation Functions
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• Unsupervised Learning
• Understand Autoencoders and Applications

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-DLTENS-CBT

On successful Completion of the Career Enabler: Deep Learning with GPU course you will be able to:

• Quick review on Deep Learning
• Understand the Deep Learning Pipeline
• Understand Hardware Accelerated Deep Learning
• Learn how to accelerate a deep learning model
• Describe running TensorFlow operations on CPUs vs. GPUs
• Understand Deep Learning in the Cloud
• Understand Distributed Deep Learning

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSC-DLTENS-CBT

On successful Completion of the Career Enabler: Introduction to R Programming course you will be able to:

• The basics of R
• Writing your own R scripts
• How to use R to solve problems related to movies data
• The fundamentals of R Syntax
• Vectors, lists, matrix, arrays and dataframes
• Reading and writing data in R

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-RPRG-CBT

On successful Completion of the Career Enabler: Using R with Databases course you will be able to:

• Why to use R with Relational Databases
• Connecting to Relational Databases using RJDBC and RODBC
• Creating Database Objects and Querying Data
• Modifying Data and Using Stored Procedures
• Using In-Database Analytics

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-RPRG-CBT

On successful Completion of the Career Enabler: Data Visualization with R course you will be able to:

• Basic Visualization Tools
• Specialized Visualization Tools
• how to create beautiful graphics and charts
• how to customize the look and feel of them
• How to create Maps
• How to build interactive web pages

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-RPRG-CBT

On successful Completion of the Career Enabler: SQL Access for Hadoop course you will be able to:

• Describe the Big SQL architecture and understand the Big SQL terminologies
• Understand and use different methods for working with Big SQL
• List and explain the Big SQL data types
• Create Big SQL schemas and tables
• Understand and use the file formats supported by Big SQL
• Create and use partitioned tables

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-RPRG-CBT

On successful Completion of the Career Enabler: SQL and Databases for Data Science course you will be able to:

• Relational and Non- Model Concepts
• Introduction to Databases and Basic SQL
• Provision a Cloud hosted Database instance
• Composing and Running basic SQL queries
• Information and Data Models
• Types of Relationships
• Mapping Entities to Tables
• Relational Model Concepts
• Advanced SQL Concepts
• String Patterns, Sorting & Grouping
• Accessing Databases using Python
• Accessing Databases using R

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-RPRG-CBT

On successful Completion of the Career Enabler: Machine Learning with Big Data course you will be able to:

• Explain what machine learning is
• Describe the main categories of machine learning techniques
• Identify the steps in the machine learning process
• Describe what CRISP-DM is
• Describe Data Exploration and Preparation
• Describe classification and how classification can be supervised or unsupervised
• Explain and Discuss Evaluation of Machine Learning Models
• Explain Regression, Cluster Analysis, and Association Analysis
• Define what the regression task is
• Explain the difference between regression and classification
• Construct models that learn from data using widely available open source tools
• Analyze big data problems using scalable machine learning algorithms on Spark

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the course you will be able to accomplish the following:

• Describe key concepts of Data Science
• Understand Open Source Data Science tools including R and Python
• Understand Open Source Data Science Tools and Platforms
• Understand Commercial Data Science tools including Microsoft Azure Machine Learning
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Data Science solutions using R
• Develop R based Data Science solutions using Microsoft Azure ML
• Develop Data Science solutions using Microsoft Azure ML Studio
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FND-DSCR-CBT

On successful Completion of the course you will be able to accomplish the following:

• Describe key concepts of Data Science
• Understand Open Source Data Science tools including R and Python
• Understand Open Source Data Science Tools and Platforms
• Understand Commercial Data Science tools including Microsoft Azure Machine Learning
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Data Science solutions using Python
• Develop Python based Data Science solutions using Microsoft Azure ML
• Develop Data Science solutions using Microsoft Azure ML Studio
• Create supervised and unsupervised Data Science models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FDN-DSPYTH-CBT

On successful Completion of the Foundations of Data Science with Microsoft Azure ML Self-Study eLearning course you will be able to:

• Describe key concepts of Data Science
• Understand Open Source Data Science tools including R and Python
• Understand Open Source Data Science Tools and Platforms
• Understand Commercial Data Science tools including Microsoft Azure Machine Learning
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Data Science solutions using Python
• Develop R based Data Science solutions using Microsoft Azure ML
• Develop Machine learning solutions using Microsoft Azure ML Studio
• Create supervised and unsupervised Data Science models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FDN-DSMSAZ-CBT

On successful Completion of the Foundations of Machine Learning with Azure ML course you will be able to:

• Describe key concepts of machine learning
• Understand Open Source Machine learning tools including Python
• Understand Open Source Machine learning Tools and Platforms
• Understand Commercial Machine learning tools including Microsoft Azure Machine Learning
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Machine learning solutions using Python
• Develop R and Python Machine learning solutions using Microsoft Azure ML
• Develop Machine learning solutions using Microsoft AzureML Studio
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FDN-MLMSAZ-CBT

On successful Completion of the Foundations of Machine Learning with Python course you will be able to:

• Describe key concepts of machine learning
• Understand Open Source Machine learning tools including Python
• Understand Open Source Machine learning Tools and Platforms
• Understand Commercial Machine learning tools including Microsoft Azure Machine Learning
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Machine learning solutions using Python
• Develop Python Machine learning solutions using Microsoft Azure ML
• Develop Machine learning solutions using Microsoft Azure ML Studio
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FDN-MLPYTH-CBT

On successful Completion of the Foundations of Machine Learning with R course you will be able to:

• Describe key concepts of machine learning
• Understand Open Source Machine learning tools including R
• Understand Open Source Machine learning Tools and Platforms
• Understand Commercial Machine learning tools including Microsoft Azure Machine Learning
• Develop Machine learning solutions using R
• Develop R Machine learning solutions using Microsoft Azure ML
• Develop Machine learning solutions using Microsoft Azure ML Studio
• Prepare data for predictive modelling
• Visualize and explore data
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FDN-MLPYTH-CBT

On successful Completion of the Career Enabler: Foundations of Data Science and Machine Learning course you will be able to:

• Describe key concepts of data science and machine learning
• Describe key concepts of machine learning
• Understand Open Source Machine learning tools including R and Python
• Understand Open Source Machine learning Platforms
• Understand Commercial Machine learning tools including Microsoft Azure Machine Learning
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Machine learning solutions using R and Python
• Develop R Machine learning solutions using Microsoft AzureML
• Develop Machine learning solutions using Microsoft AzureML Studio
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-FND-DSML-CBT

On successful Completion of the Fundamentals of Data Science and Machine Learning with Azure ML course you will be able to:

• Describe key concepts of data science and machine learning
• Understand Open Source Machine learning tools including KNIME, R and Python
• Understand Open Source Machine learning Platforms
• Understand Commercial Machine learning tools including Oracle Advanced Analytics and Microsoft Azure Machine Learning
• Develop Machine learning solutions using R and Python
• Develop R Machine learning solutions using Microsoft Azure ML
• Develop Machine learning solutions using Microsoft Azure ML Studio
• Prepare data for predictive modelling
• Visualize and explore data
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FDM-DSML-CBT

On successful Completion of the Machine Learning Fundamentals course you will be able to:

• Describe key concepts of machine learning
• Understand Open Source Machine learning tools including R, KNIME and Python
• Understand Open Source Machine learning Platforms
• Understand Commercial Machine learning tools including IBM SPSS, Oracle Analytics, Microsoft Azure ML
• Visualize and explore data
• Create supervised and unsupervised machine learning models
• Develop Machine learning solutions using R and Python
• Develop R Machine learning solutions using Microsoft Azure ML
• Develop Machine learning solutions using Microsoft Azure ML Studio
• Prepare data for predictive modelling

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: FDM-ML-CBT

On successful Completion of the Data Science and Machine Learning Bootcamp course you will be able to:

• Describe key concepts of data science and machine learning
• Describe key concepts of machine learning
• Understand Open Source Data Science tools and Platforms including Spark, R and Python
• Understand Open Source Machine learning Tools and Platforms
• Understand Commercial Data Science tools including Microsoft Azure ML Studio and Oracle Advanced Analytics
• Learn to Install and Configure R and Python
• Learn to Configure Microsoft Azure ML for R and Python Development
• Prepare data for predictive modelling
• Visualize and explore data
• Create supervised and unsupervised machine learning models
• Develop Data Science solutions using R on Azure ML Platform
• Develop Machine learning solutions using R and Python
• Develop Machine learning solutions Microsoft Azure Notebooks
• Develop Data Science solutions using Microsoft Azure ML Studio

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-BCAMP-CBT

On successful Completion of the Data Science and Machine Learning with Azure ML course you will be able to:

• Describe key concepts of data science and machine learning
• Understand Open Source Machine learning tools including R and Python
• Understand Open Source Machine learning Platforms
• Understand Commercial Machine learning tools including Microsoft Azure Machine Learning
• Set Up a R Environment for Development
• Set Up a Python Environment for Development
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Data Science solutions using R
• Develop R solutions using Microsoft Azure ML
• Develop Data Science solutions using Microsoft Azure ML Studio
• Develop Machine learning solutions using Microsoft Azure ML Studio
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-AZU-CBT

On successful Completion of the Career Enabler R Programming Disc-3mm -May2013 course you will be able to:

• Learn to Install RStudio and work on R interface
• Learn the basics of R programming including objects, classes, vectors, attributes etc.
• Write functions including generic functions using various methods and loops
• Install various packages and work effectively in the R environment
• Select and modify values as required
• Learn to use Vectorized Coding and Use Cases
• Cover the concepts of R Notation, S3 System and Closures
• Become proficient in writing a fundamental program and perform analytics with R

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-RPRG-CBT

On successful Completion of the Career Enabler: Fundamentals of R for Data Science course you will be able to:

• Understand Data Science
• Understand Data Science Tools and Technology
• Understand R
• Data Modeling in R
• Visualize and explore data
• Data Exploration in R
• Data Visualisation in R
• Profiling and Analyzing Datasets

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DS-RDS-CBT

On successful Completion of the Predictive Analytics with Spark course you will be able to:

• Using Spark to work with data
• Preprocessing data for machine learning in Spark
• Building machine learning models in Spark
• Using R at scale with R Server on Spark

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: WLN-PA-SPARK

On successful Completion of the Career Enabler: R Programming and Predictive Modelling course you will be able to:

• Basics of R Programming
• Naive Bayes
• k-nearest neighbor algorithm
• Support vector machines
• Random forests
• Sentiment Analysis using R

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: DSML-RPRG-CBT

On successful Completion of the Career Enabler AI & Machine Learning course you will be able to:

• General Concepts on Artificial Intelligence
• General Concepts on Machine Learning
• Linear Regression
• Logistic Regression
• Association Rules- Market Basket Analysis
• Recommendation system
• Item Based collaborative
• User Based Collaborative

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSAIML-CBT

On successful Completion of the Career Enabler: Mastering Apache Hadoop course you will be able to:

• Comprehend key Hadoop distributors
• Comprehend Hadoop Architecture
• Comprehend HDFS
• Comprehend MapReduce
• Comprehend Backup and Recovery
• Comprehend Monitoring the Cluster
• Comprehend Hadoop Resource Management
• Comprehend Cluster Troubleshooting
• Comprehend Installation, Configuration and Implementation
• Comprehend Hadoop debugging, development, and execution of workflows and algorithms
• leverage Hive, Oozie, Pig, Flume, Sqoop, and other Hadoop ecosystem projects
• Create custom components such as InputFormats and WritableComparables to administer complex data types
• Write and execute joins to link data sets in MapReduce

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-HADO-CBT

On successful Completion of the Career Enabler: Foundations of Mathematics & Statistics course you will be able to:

• Mean
• Mode
• Median
• Standard deviation
• Probability
• Combination
• R Studio and R Installation
• R for Statistics and mathematics (Basic Mathematics Operations)

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-FND-MATS-CBT

On successful Completion of the Career Enabler: Hadoop YARN & Ambari course you will be able to:

• Hadoop fundamentals
• Big Data Approach
• RDBMS Vs. Hadoop
• Introduction to Hadoop
• Hadoop Architecture
• HDFS, YARN, Hadoop setup
• Cloudera Manager
• Ambari
• Job scheduling and monitoring

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-HYAMB-CBT

On successful Completion of the Career Enabler: Sqoop, Flume & Kafka course you will be able to:

• Ingesting Data using Sqoop
• Sqoop properties and commands
• Integrating Sqoop with RDBMS
• Sqoop features and example scenarios
• Ingesting Data using Flume
• Flume properties and setup
• Flume and streaming
• Flume Vs. Kafka

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Pig, Hive & Impala course you will be able to:

• Introduction to Pig
• Pig programming and commands
• Pig interactive shell
• Analyzing complex data using Pig
• Using Pig functions
• Introduction to Hive
• Hive Metastore
• Writing queries using Hive
• Joins and grouping
• Impala architecture
• Impala Vs. Hive
• Queries using Impala

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-PHI-CBT

On successful Completion of the Career Enabler Spark Machine Learning course you will be able to:

• Spark Basics
• Spark MlLib Library
• Install and configure intelliJ for Spark development
• Logistic Regression
• Linear Regression
• ALS
• KMeans

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-SPAML-CBT

On successful Completion of the Career Enabler: Foundations of Data Science and Machine Learning course you will be able to:

• Describe key concepts of data science and machine learning
• Describe key concepts of machine learning
• Understand Open Source Machine learning tools including R and Python
• Understand Open Source Machine learning Platforms
• Understand Commercial Machine learning tools including Microsoft Azure Machine Learning
• Prepare data for predictive modelling
• Visualize and explore data
• Develop Machine learning solutions using R and Python
• Develop R Machine learning solutions using Microsoft AzureML
• Develop Machine learning solutions using Microsoft AzureML Studio
• Create supervised and unsupervised machine learning models

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-FND-DSML-CBT

On successful Completion of the Career Enabler: Introduction to Data Science, AI & Machine Learning course you will be able to:

• Translate business questions into Machine Learning problems to understand what your data is telling you
• Explore and analyze data from the Web, Word Documents, Email, Twitter feeds, NoSQL stores, Relational Databases and more, for patterns and trends relevant to your business
• Build Decision Tree, Logistic Regression and Naïve Bayes classifiers to make predictions about your customers’ future behaviors as well as other business critical events
• Use K-Means and Hierarchical Clustering algorithms to more effectively segment your customer market or to discover outliers in your data
• Discover hidden customer behaviors from Association Rules and Build Recommendation Engines based on behavioral patterns
• Use biologically-inspired Neural Networks to learn from observational data as humans do
• Investigate relationships and flows between people, computers and other connected entities using Social Network Analysis

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSAIML-RPRG-CBT

On successful Completion of the Career Enabler: Introduction to Big Data course you will be able to:

• Store, manage, and analyze unstructured data
• Select the correct big data stores for disparate data sets
• Process large data sets using Hadoop to extract value
• Query large data sets in near real time with Pig and Hive
• Plan and implement a big data strategy for your organization

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Building Enterprise Solutions with MongoDB course you will be able to:

• Develop highly scalable and cost-efficient applications with MongoDB
• Build efficient MongoDB data models for enterprise-scale applications
• Enhance performance with indexing and sharding
• Manage consistency with write concern and read preference
• Process data and compute results with aggregation pipelines and MapReduce

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Business Intelligence: Preparing for a BI Initiative course you will be able to:

• Apply the BI Meta Model (BIMM) to turn desired outcomes into actions
• Choose between a strategic and a tactical application of BI
• Map operational data to a data warehouse
• Design a BI solution for a business problem

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BII-CBT

On successful Completion of the Career Enabler: Introduction to Modelling for Business Analysis course you will be able to:

• Perform a functional decomposition of your organisation
• Diagram and document business processes as use cases
• Capture workflows in Business Process Model and Notation (BPMN)
• Apply UML diagrams to document your business objects and their states
• Use a CASE tool to refine business analysis models and documentation

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-MFBA-CBT

On successful Completion of the Career Enabler: Data Science and Machine Learning with Spark ML course you will be able to:

• Data Science and Machine Learning Overview
• Understand Data Science and Big Data Processing
• Understand Spark
• Making a Case for Spark
• Understand Major components of Spark programming
• Understand Major components of Spark programming
• Understand Major components of Spark programming
• Describe Spark MLlib and Data Types
• Describe Spark ML on Azure
• Describe Azure HDInsight Spark Clusters
• Spark MLlib Basic Statistics
• Understand Clustering on Spark
• Understand Regression on Spark
• Applying Regression and Classification on Spark

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Machine Learning with Big Data course you will be able to:

• Explain what machine learning is
• Describe the main categories of machine learning techniques
• Identify the steps in the machine learning process
• Describe what CRISP-DM is
• Describe Data Exploration and Preparation
• Describe classification and how classification can be supervised or unsupervised
• Explain and Discuss Evaluation of Machine Learning Models
• Explain Regression, Cluster Analysis, and Association Analysis
• Define what the regression task is
• Explain the difference between regression and classification
• Construct models that learn from data using widely available open source tools
• Analyze big data problems using scalable machine learning algorithms on Spark

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Data Science for Oracle Developers course you will be able to:

• Describe and Understand Data Science and Machine Learning
• Describe the main categories of machine learning techniques
• Describe and Understand the Data Science Process
• Identify the steps in the machine learning process
• Describe what CRISP-DM is
• Describe and Understand Oracle Advanced Analytics Tools
• Describe Oracle Data Miner
• Understand R Technologies in Oracle
• Describe Oracle R Enterprise Server
• Describe and Understand Data Science Algorithms supported by Oracle
• Describe and Understand AI and Machine Learning Techniques supported by Oracle
• Install and Configure Oracle Advanced Analytics
• Describe Data Exploration and Preparation
• Describe classification and how classification can be supervised or unsupervised
• Understand and Perform Clustering Methods
• Understand and apply Association Rules
• Understand and apply Regression Analysis
• Understand and apply Classification Methods
• Understand and apply Neural Networks
• Understand and apply Solutions Deployment

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSORA-CBT

On successful Completion of the Data Science for Microsoft Developers course you will be able to:

• Describe and Understand Data Science and Machine Learning
• Describe the main categories of machine learning techniques
• Describe and Understand the Data Science Process
• Identify the steps in the machine learning process
• Describe what CRISP-DM is
• Describe and Understand Microsoft Analytics Tools
• Describe Oracle Data Miner
• Understand R Technologies in Microsoft
• Describe Microsoft R Enterprise Server
• Describe and Understand Data Science Algorithms supported by Microsoft
• Describe and Understand AI and Machine Learning Techniques supported by Microsoft
• Install and Configure Microsoft Advanced Analytics
• Describe Data Exploration and Preparation
• Describe classification and how classification can be supervised or unsupervised
• Understand and Perform Clustering Methods
• Understand and apply Association Rules
• Understand and apply Regression Analysis
• Understand and apply Classification Methods
• Understand and apply Neural Networks
• Understand and apply Solutions Deployment

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-DSORA-CBT

On successful Completion of the Career Enabler: Foundations of Apache Spark course you will be able to:

• Gain a high-level understanding of Apache Spark
• Understand Resilient Distributed Datasets (RDDs) in Apache Spark
• Understand notebooks on Apache Spark
• Understand Spark ML
• Understand Spark SQL
• Understand Hive in Apache Spark
• Understand R on Apache Spark
• Understand Spark Streaming
• Understand machine learning with Spark MLlib

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SPK-CBT

On successful Completion of the Career Enabler: Microsoft Big Data Analytics: Hadoop and Spark on HDInsight course you will be able to:

• Gain a high-level understanding of big data and Hadoop on HDInsight
• Understand Hadoop Components: MapReduce and HDFS
• Understand Hadoop Components: YARN and Apache Tez
• Understand HDInsight
• Understand HCatalog
• Understand development with Hive
• Understand development with Pig
• Understand development with HBase
• Understand Apache Storm on HDInsight
• Understand HDInsight clusters, cluster type, and configuration
• Understand extensibility and customizing HDInsight clusters using script actions
• Understand cluster security and operations
• Understand monitoring and managing Hadoop with Ambari web UI
• Understand Hadoop Clusters in HDInsight
• Gain a high-level understanding of Apache Spark
• Understand Resilient Distributed Datasets (RDDs) in Apache Spark
• Understand notebooks on Apache Spark
• Understand Spark with Azure HDInsight
• Understand Spark ML
• Understand Spark SQL
• Understand Hive and Power BI in Apache Spark
• Understand Spark Streaming
• Understand machine learning with Spark MLlib
• Understand R Server on HDInsight with Apache Spark

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Microsoft Big Data Analytics: Hadoop on HDInsight course you will be able to:

• Gain a high-level understanding of big data and Hadoop on HDInsight
• Understand Hadoop Components: MapReduce and HDFS
• Understand Hadoop Components: YARN and Apache Tez
• Understand HDInsight
• Understand HCatalog
• Understand development with Hive
• Understand development with Pig
• Understand development with HBase
• Understand Apache Storm on HDInsight
• Understand HDInsight clusters, cluster type, and configuration
• Understand extensibility and customizing HDInsight clusters using script actions
• Understand cluster security and operations
• Understand monitoring and managing Hadoop with Ambari web UI
• Understand Hadoop Clusters in HDInsight

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SQFK-CBT

On successful Completion of the Career Enabler: Microsoft Big Data Analytics: Spark on HDInsight course you will be able to:

• Gain a high-level understanding of Apache Spark
• Understand Resilient Distributed Datasets (RDDs) in Apache Spark
• Understand notebooks on Apache Spark
• Understand Spark with Azure HDInsight
• Understand Spark ML
• Understand Spark SQL
• Understand Hive and Power BI in Apache Spark
• Understand Spark Streaming
• Understand machine learning with Spark MLlib
• Understand R Server on HDInsight with Apache Spark

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-SPK-CBT

On successful Completion of the Career Enabler: Microsoft Big Data Analytics: Hadoop on Azure course you will be able to:

• Microsoft Big Data Fundamentals
• How to implement Hadoop on HDInsight
• Hive and Tez: Querying Big Data Essentials
• Pig, Sqoop, Oozie, and Mahout Essentials
• HBase Essentials
• Storm Essentials

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-HADAZU-CBT

On successful Completion of the Career Enabler: Foundations of Microsoft AI, Machine Learning and Big Data Platform course you will be able to:

• Gain a high-level understanding of SQL Server 2016/2017
• Understand the mission-critical and hybrid capabilities of SQL Server
• Gain a high-level understanding of Azure Data Services
• Gain a high-level understanding of Modern Data Warehouse
• Gain a high-level understanding of SQL Server BI
• Gain a high-level understanding of SQL Server Enterprise Information Management
• Gain a high-level understanding of Power BI
• Gain a high-level understanding of Azure Machine Learning
• Gain a high-level understanding of Azure Data Factory
• Gain a high-level understanding of SQL Server R Services
• Gain a high-level understanding of Hadoop on Azure
• Gain a high-level understanding of Azure Data Lake
• Gain a high-level understanding of Apache Spark

Certification: This course will assist in preparation for the Microsoft, IBM and Oracle Data Science and Machine Learning Certification exams.

Product code: CEN-BIG-MSPLT-CBT

On successful Completion of the Fundamentals of Microsoft Azure Data Warehousing course you will be able to:

• Understand Data Warehousing Concepts
• Understand key SQL Data Warehouse concepts
• Understand the Data Warehouse and ETL Development Lifecycle
• Understand SQL Data Warehouse topology and architecture
• Understand Azure Data Warehouse database design
• Understand ETL (data access, data export) in SQL Data Warehouse
• Learn how to Extract, Transform, and Load (ETL) Data in Azure SQL Data Warehouse
• Understand data movement and distribution theory in SQL Data Warehouse
• Understand big data and SQL Server integration
• Understanding Azure Data Warehouse to BI integration, including with Power BI

Certification: This course will assist in preparation for the Microsoft Business Intelligence Certification exams.

Product code: WLN-MSFT-AZUDW

On successful Completion of the Fundamentals of SQL Server 2016 Platform course you will be able to:

• Gain a high-level understanding of SQL Server
• Understand the new features in SQL Server 2016
• Understand SQL Server In-Memory Optimization (OLTP)
• Understand SQL Server In-Memory Data Warehouse capabilities
• Understand SQL Server 2016 high-availability features
• Understand SQL Server 2016 SQL Server security features
• Understand SQL Server 2016 Query Store and Live Query Statistics
• Understand SQL Server 2016 Temporal Tables
• Understand the integration of SQL Server 2016 with big data sources with PolyBase
• Understand SQL Server 2016 Stretch Database
• Gain a high-level understanding of SQL Server R Services Analytics
• Understand SQL Server 2016 R Services integration

Certification: This course will assist in preparation for the Fundamentals of SQL Server 2016 Platform Certification exams.

Product code: WLN-MSFT-BIDW

On successful Completion of the Fundamentals of SQL Server 2017 Platform course you will be able to:

• Gain a high-level understanding of SQL Server
• Understand the new features in SQL Server 2017
• Understand SQL Server In-Memory Optimization (OLTP)
• Understand SQL Server In-Memory Data Warehouse capabilities
• Understand SQL Server 2017 high-availability features
• Understand SQL Server 2017 SQL Server security features
• Understand SQL Server 2017 Query Store and Live Query Statistics
• Understand SQL Server 2017 Temporal Tables
• Understand the integration of SQL Server 2017 with big data sources with PolyBase
• Understand SQL Server 2017 Stretch Database
• Gain a high-level understanding of SQL Server R Services Analytics
• Understand SQL Server 2017 R Services integration

Certification: This course will assist in preparation for the Fundamentals of SQL Server 2017 Platform Certification exams.

Product code: WLN-MSFT-BIDW

On successful Completion of the Fundamentals of Microsoft Azure Data Warehousing course you will be able to:

• Learn to Plan and Scope your SQL Server Data Warehouse Projects
• Understand BI and Warehouse Architecture Frameworks
• Understand the BI and Warehouse Development Process
• Learn to Manage SQL Server Warehouse Projects
• Understand the Data Warehouse and ETL Development Lifecycle
• Understand Data Warehousing Concepts
• Understand Dimension Modelling
• Understand key SQL Server Data Warehouse concepts
• Understand SQL Data Warehouse topology and architecture
• Understand Azure Data Warehouse database design
• Understand ETL (data access, data export) in SQL Data Warehouse
• Understand data movement and distribution theory in SQL Data Warehouse
• Understand big data and SQL Server integration
• Understanding Azure Data Warehouse to BI integration, including with Power BI

Certification: This course will assist in preparation for the Microsoft Business Intelligence Certification exams.

Product code: WLN-MSFT-AZUDW

On successful Completion of the Introduction to Data Modeling course you will be able to:

• Fundamentals of normalization and why it's important to transactional databases
• How to develop logical and physical data models
• How to model data security, privacy and protection requirements
• When and where to model database-specific performance requirements
• How model-driven development fits in a DevOps or agile environment
• How to avoid schema drift and other data anti-patterns

Certification: This course will assist in preparation for the Microsoft MCSE & MCSA Certification exams.

Product code: WLN-MSFT-BIDW

On successful Completion of the Career Enabler: Decision Modeling course you will be able to:

• Decision Modeling
• Decision Tree
• Supervised learning
• Unsupervised learning
• Artificial Neural Networks
• Twitter Data Processing with R

Certification: This course will assist in preparation for the Decision Modeling Certification exams.

Product code: WLN-MSFT-BIDW

On successful Completion of the Informatica Data Integration & ETL Fundamentals course you will be able to:

• Understand the ETL Development Lifecycle
• Understand basic Data warehousing Concepts
• Understand basic Dimension Modelling
• Understand Data Quality Issues in ETL Process
• Understand the architecture of the complete Informatica system
• Design and build simple mappings and workflows
• Use PowerCenter 9.x Designer to build mappings that extract data from a source to a target
• Use PowerCenter 9.x Designer to build transformations
• Use PowerCenter transformations to cleanse, format and join data
• Use PowerCenter transformations to aggregate and route data to targets
• Perform error handling/trapping using PowerCenter mappings
• Describe the use of Mapping Variables and Parameter Files
• Use PowerCenter 9.x Workflow Manager to build and run a workflow
• Use PowerCenter 9.x Workflow Manager to execute sessions associated with a mapping
• Perform basic troubleshooting using PowerCenter logs and debugger
• Describe the SQL Transformation

Informatica Data Integration & ETL Fundamentals Self-Study eLearning:

Product code: WLN-INF-ETLFNDM

On successful Completion of the Informatica Data Integration & ETL BootCamp Self-Study eLearning course you will be able to:

• Learn to Plan and Scope your ETL/ELT Projects
• Understand the ETL Development Lifecycle
• Understand basic Data warehousing Concepts
• Understand basic Dimension Modelling
• Understand the Oracle Data Integration Reference Architecture
• Understand Data Quality Issues in ETL Process
• Understand the architecture of the complete Informatica system
• Describe the Informatica domain, nodes, and application services
• Describe the Informatica clients
• Install Informatica 9.6.x domain
• Describe the Administration Console
• Create Privileges and Roles
• Describe PowerCenter repositories
• Deploy PowerCenter metadata from development to test environment
• Describe Domain Management
• Design and build simple mappings and workflows
• Use PowerCenter 9.6.x Designer to build mappings that extract data from a source to a target
• Use PowerCenter 9.6.x Designer to build transformations
• Use PowerCenter transformations to cleanse, format and join data
• Use PowerCenter transformations to aggregate and route data to targets
• Perform error handling/trapping using PowerCenter mappings
• Describe the use of Mapping Variables and Parameter Files
• Use PowerCenter 9.6.x Workflow Manager to build and run a workflow
• Use PowerCenter 9.6.x Workflow Manager to execute sessions associated with a mapping
• Perform basic troubleshooting using PowerCenter logs and debugger
• Perform basic troubleshooting using PowerCenter logs and debugger
• Describe user defined and advanced functions
• Describe how to Normalize and Denormalize data using PowerCenter
• Describe the Stored Procedure transformation and its two modes of use
• Describe the SQL Transformation

Informatica Data Integration & ETL Bootcamp Self-Study eLearning:

Product code: WLN-INF-ETLBC

On successful Completion of the Informatica 9.6.x Data Warehousing Fundamentals Self-Study eLearning course you will be able to:

• Understand the Informatica Data Warehouse and ETL Development Lifecycle
• Understand the BI and Warehouse Development Process
• Learn to Manage Informatica Warehouse Projects
• Understand Data warehousing Concepts
• Understand Dimension Modelling
• Understand Data Quality Issues in ETL Process
• Understand the architecture of the Informatica system
• Manage your Informatica environment using the Informatica Console
• Use PowerCenter 9.x Designer to build mappings
• Use PowerCenter 9.x Designer to extract data from a source to a target
• Use PowerCenter 9.x Designer to build transformations
• Use PowerCenter transformations to cleanse, format and join data
• Use PowerCenter transformations to aggregate and route data to targets
• Perform error handling/trapping using PowerCenter mappings
• Describe the use of Mapping Variables and Parameter Files
• Use PowerCenter 9.x Workflow Manager to build and run a workflow
• Use PowerCenter 9.x Workflow Manager to execute sessions associated with a mapping

Informatica Data Integration & ETL Fundamentals Self-Study eLearning:

Product code: WLN-INF-DWFNDM

On successful Completion of the Informatica 9.6.x Data Warehousing BootCamp Self-Study eLearning course you will be able to:

• Understand the Informatica Data Warehouse and ETL Development Lifecycle
• Understand the BI and Warehouse Development Process
• Learn to Manage Informatica Warehouse Projects
• Understand Data warehousing Concepts
• Understand Dimension Modelling
• Understand Data Quality Issues in ETL Process
• Describe the Informatica 9.6.x Technical architecture
• Describe the Informatica domain, nodes, and application services
• Describe the Informatica clients
• Install Informatica 9.6.x domain
• Describe the Administration Console
• Create Privileges and Roles
• Describe PowerCenter repositories
• Deploy PowerCenter metadata from development to test environment
• Describe Domain Management
• Describe the Informatica PowerCenter architecture
• Design and build simple mappings and workflows
• Manage your Informatica environment using the Informatica Console
• Use PowerCenter 9.6.x Designer to build mappings
• Use PowerCenter 9.6.x Designer to extract data from a source to a target
• Use PowerCenter 9.6.x Designer to build transformations
• Use PowerCenter transformations to cleanse, format and join data
• Use PowerCenter transformations to aggregate and route data to targets
• Perform error handling/trapping using PowerCenter mappings
• Describe the use of Mapping Variables and Parameter Files
• Use PowerCenter 9.6.x Workflow Manager to build and run a workflow
• Use PowerCenter 9.6.x Workflow Manager to execute sessions associated with a mapping

Informatica 9.6.X Data Warehousing BootCamp Self-Study eLearning:

Product code: WLN-INF-DWBC

On successful Completion of the Oracle 11g Data Warehousing Fundamentals Self-Study eLearning course you will be able to:

• Define the terminology and explain the basic concepts of data warehousing
• Understand the Oracle Data Warehouse Technology Stack
• Understand the Oracle Data Warehouse Reference Architecture
• Understand the Oracle Business Intelligence and Analytics Technology Stack
• Describe methods and tools for extracting, transforming, and loading data
• Use Oracle Data Integrator 11g ETL for extracting, transforming, and loading data
• Identify some of the tools for accessing and analysing warehouse data
• Identify the technology and some of the tools from Oracle to implement a successful data warehouse
• Define the decision support purpose and end goal of a data warehouse
• Describe the benefits of partitioning, parallel operations, materialized views, and query rewrite in a data warehouse
• Understand the implementation and organisational issues surrounding a data warehouse project
• Use materialised views and query rewrite to improve the data warehouse performance
• Develop familiarity with some of the technologies required to implement a data warehouse

Certification: This course will assist in preparation for the Oracle BI Certified Implementation Specialist 1Z0-591 Certification exam.

Product code: WLN-ORA-DWFNDM

On successful Completion of the Oracle 12c Data Warehousing Fundamentals Self-Study eLearning course you will be able to:

• Define the terminology and explain the basic concepts of data warehousing
• Understand the Oracle Data Warehouse Technology Stack
• Understand the Oracle Data Warehouse Reference Architecture
• Understand the Oracle Business Intelligence and Analytics Technology Stack
• Describe methods and tools for extracting, transforming, and loading data
• Use Oracle Data Integrator 11g ETL for extracting, transforming, and loading data
• Identify some of the tools for accessing and analysing warehouse data
• Identify the technology and some of the tools from Oracle to implement a successful data warehouse
• Define the decision support purpose and end goal of a data warehouse
• Describe the benefits of partitioning, parallel operations, materialized views, and query rewrite in a data warehouse
• Understand the implementation and organisational issues surrounding a data warehouse project
• Use materialised views and query rewrite to improve the data warehouse performance
• Develop familiarity with some of the technologies required to implement a data warehouse

Certification: This course will assist in preparation for the Oracle BI Certified Implementation Specialist 1Z0-591 Certification exam.

Product code: WLN-ORA-DWFNDM

On successful Completion of the Oracle 18c Data Warehousing Fundamentals Self-Study eLearning course you will be able to:

• Define the terminology and explain the basic concepts of data warehousing
• Define the terminology and explain the basics of Oracle Big data warehousing
• Understand the Oracle 18c Data Warehouse Technology Stack
• Understand the Oracle 18c Multitenant Architecture for Data Warehousing
• Understand the Oracle 18c Data Warehouse Reference Architecture
• Discuss the different Oracle tools to implement data warehousing on-premise
• Discuss Autonomous Data Warehouse Cloud (ADWC) and Data Integration Platform Cloud (DIPC)
• Understand the Oracle Business Intelligence and Analytics Technology Stack
• Describe methods and tools for extracting, transforming, and loading data
• Use Oracle Data Integrator ETL for extracting, transforming, and loading data
• Identify some of the tools for accessing and analysing warehouse data
• Understand the Oracle 18c AI & Machine Learning Tools for data warehousing
• Identify the technology and some of the tools from Oracle to implement a successful data warehouse
• Define the decision support purpose and end goal of a data warehouse
• Describe the benefits of partitioning, parallel operations, materialized views, and query rewrite in a data warehouse
• Understand the implementation and organisational issues surrounding a data warehouse project
• Use materialised views and query rewrite to improve the data warehouse performance
• Develop familiarity with some of the technologies required to implement a data warehouse

Certification: This course will assist in preparation for the Oracle BI Certified Implementation Specialist 1Z0-591 Certification exam.

Product code: WLN-ORA-DW18cFNDM

On successful Completion of the Oracle Data Integrator 11g Fundamentals course you will be able to:

• Understand the ETL Development Lifecycle
• Understand basic Data warehousing Concepts
• Understand basic Dimension Modelling
• Understand Data Quality Issues in ETL Process
• Understand the architecture of the Oracle Data Integrator system
• Define Data Sources
• Define Physical and Logical Architecture
• Create and reverse-engineer models
• Manage Projects
• Define Integration Processes
• Work with projects in Oracle Data Integrator
• Release your ODI work for deployment
• Understand models, reverse-engineering model metadata from your database
• Manage metadata in Oracle Data Integrator: models and data quality
• Create simple interfaces and add multiple sources to an interface
• Launch a session to run an interface
• Enforce data quality constraints in an interface
• Manage packages

Certification: This course will assist in the preparation for the Oracle Data Integrator 11g Certified Implementation Essentials - 1Z0-482 exam.

Product code: WLN-ORA-ODIFNDM

On successful Completion of the Oracle Data Integrator 11g Certified Implementation Essentials - 1Z0-482 course you will be able to:

• Learn to Plan and Scope your ETL/ELT Projects
• Understand the ETL Development Lifecycle
• Describe Oracle Fusion Middleware (FMW)
• Describe the Oracle Data Integrator (ODI) system logical architecture
• Identify and describe Oracle DI Java components
• Identify the system administration tools that are available for managing Oracle DI
• Define the Oracle Data Integrator 11g (ODI) Information System architecture
• Describe scenarios in which FMW Control is available
• Start and stop instances of WebLogic Server by using FMW Control
• Configure ODI11g Java EE Agent Components
• Monitor a WebLogic Server (WLS) domain with FMW Control
• Centrally manage Oracle DI components using Fusion Middleware Control
• Centrally manage Oracle DI Java components using the Oracle WebLogic Server Console
• Stop and start Oracle DI components
• Understand Data Quality Issues in ETL Process
• Understand the architecture of the complete Oracle Data Integrator system
• Create Data Servers and Sources
• Define Physical and Logical Architecture
• Create and reverse-engineer models
• Manage Projects
• Define Integration Processes
• Work with projects in Oracle Data Integrator
• Release your ODI work for deployment
• Understand models, reverse-engineering model metadata from your database
• Manage metadata in Oracle Data Integrator: models and data quality
• Create simple interfaces and add multiple sources to an interface
• Launch a session to run an interface
• Enforce data quality constraints in an interface
• Manage packages
• Manage and Monitor ETL processes in the ODI Console

Certification: This course will assist in the preparation for the Oracle Data Integrator 11g Certified Implementation Essentials - 1Z0-482 exam.

Product code: WLN-ORA-ODIBC