This is an Online ANYTIME course library and includes multiple individual online courses. Online ANYTIME gives you access to a self-paced training solution that uses the same core course content as our world-renowned Instructor-Led Training.

• A/B Testing, Bayesian Networks, and Support Vector Machine
• Accessing Data with Spark: An Introduction to Spark
• Accessing Data with Spark: Data Analysis using Spark SQL
• Accessing Data with Spark: Data Analysis Using the Spark DataFrame API
• Administering a SQL Database Infrastructure Expert Live with Encore
• Administering Microsoft SQL Server 2012 Databases Expert Live with Encore
• Advanced TIBCO Spotfire
• Aggregating Data in SQL Server 2016
• An Overview of Apache Cassandra
• Analytics by Function
• Apache Hadoop
• Apache Hadoop on Amazon EMR
• Apache HBase Fundamentals: Access Data through the Shell and Client API
• Apache HBase Fundamentals: Advanced API, Administration, and MapReduce
• Apache HBase Fundamentals: Installation, Architecture, and Data Modeling
• Apache Kafka Development
• Apache Kafka Operations
• Apache Solr - Query and Data Management
• Apache Solr – Deployment and Configuration
• Apache Spark SQL
• Apache Storm Introduction - API and Topology
• Apache Storm Introduction – Architecture and Installation
• Applied Predictive Modeling
• Auditing, Logging, and Event Handling
• Automation and Machine Learning
• Automation Design & Robotics
• Azure SQL Database Encryption
• Azure Virtual Machines
• Backing Up, Recovering, Importing, and Exporting Data in Oracle Database 12c
• Balancing the Four Vs of Data: The Four Vs of Data
• Base SAS 9 Programming: Creating Reports
• Base SAS 9 Programming: Data Structures
• Base SAS 9 Programming: Inputs and Outputs
• Base SAS 9 Programming: Introduction to Data Sets
• Base SAS 9 Programming: The SAS Environment
• Base SAS 9 Programming: Working with Data Sets
• Batch Solutions with Hive and Apache Pig
• Bayesian Methods: Advanced Bayesian Computation Model
• Bayesian Methods: Bayesian Concepts & Core Components
• Bayesian Methods: Implementing Bayesian Model and Computation with PyMC
• BI with QlikView: Application Deployment and Performance
• BI with QlikView: Dashboards and Comparative Analysis
• BI with QlikView: Data Governance and Metadata Management
• BI with QlikView: Data Modeling
• BI with QlikView: Getting Started
• BI with QlikView: Macros and Properties
• BI with QlikView: Scripting and Designing
• BI with QlikView: Server
• Big Data - The Legal Perspective
• Big Data Corporate Leadership Perspective
• Big Data Engineering Perspectives
• Big Data Fundamentals
• Big Data Interpretation
• Big Data Marketing Perspective
• Big Data Opportunities and Challenges
• Big Data Sales Perspective
• Big Data Strategic Planning
• Bitcoin Internals and Wallet Configuration
• Bitcoin Technology Fundamentals
• Blockchain and Your Business
• Blockchain Architectural Components and Platforms
• Blockchain in Action and IoT
• Blockchain Trust and Design
• Blockchains & Ethereum: Introduction
• Blockchains & Ethereum: Mining and Smart Contracts in Ethereum
• Blockchains & Ethereum: Performing Transactions in Ethereum
• Building Data Pipelines
• Building Decentralized Applications for Ethereum: An Introduction to dApps
• Building Decentralized Applications for Ethereum: Bespoke Ethereum Tokens
• Building Decentralized Applications for Ethereum: Building the Back End
• Building Decentralized Applications for Ethereum: Building the Front End
• Building ML Training Sets: Introduction
• Building ML Training Sets: Preprocessing Datasets for Classification
• Building ML Training Sets: Preprocessing Datasets for Linear Regression
• Building Solutions using Kafka and HBase
• Capacity Management for Hadoop Clusters
• Cassandra vs. SQL
• Cloud Blockchains: An Introduction to Blockchain on the Cloud
• Cloud Blockchains: Building Apps on the Azure Blockchain Workbench
• Cloud Blockchains: Multi-Organization Networks on Amazon Managed Blockchain
• Cloud Blockchains: Single Organization Networks on Amazon Managed Blockchain
• Cloud Data Science: Azure AI Gallery and Azure Machine Learning
• Cloud Data Science: Consume Models and APIs Using Azure Machine Learning Studio
• Cloud Data Science: Data Cleanup with Azure Machine Learning Studio
• Cloud Data Science: Deploying Models with Azure Machine Learning Studio
• Cloud Data Science: Importing and Exporting in Azure Machine Learning Studio
• Cloud Data Science: Introduction to Azure Machine Learning
• Cloud Data Science: Microsoft Cognitive Toolkit and Azure Machine Learning
• Cloud Data Science: Optimize and Validate Models in Azure Machine Learning Studio
• Cloud Data Science: SQL Server & Azure Machine Learning
• Cloud Data Science: Summarize Data with Azure Machine Learning Studio
• Cloud Data Science: Transforming Data in Azure Machine Learning Studio
• Cloud Data Science: Using Algorithms in Azure Machine Learning Studio
• Cloud Data Science: Virtual Machines & HDInsight
• Cloudera Manager and Hadoop Clusters
• Cluster Analysis and Ensemble Learning
• Clustering Techniques
• Clustering with Kafka
• Columnstore Indexes
• Complex Visualizations and Analytics
• Compliance Issues and Strategies: Data Compliance
• Components of a SQL Server 2016 Installation
• Connection Managers and Data Sources
• Connectivity and Space Management in Oracle Database 12c
• Correlation & Regression
• Create Spark Streaming Applications
• Creating Data APIs Using Node.js
• Data Access & Governance Policies: Data Access Oversight and IAM
• Data Access & Governance Policies: Data Classification, Encryption, and Monitoring
• Data Analysis Application
• Data Analysis Concepts
• Data Analysis Using Spark SQL and Hive
• Data Analytics using Power BI: Concepts
• Data Analytics Using Power BI: Data Modeling and Visualization
• Data Analytics Using Power BI: Data Sourcing and Preparation
• Data and Analytics Technologies at Work
• Data Architecture - Deep Dive: Design & Implementation
• Data Architecture - Deep Dive: Microservices & Serverless Computing
• Data Architecture Primer
• Data Classification and Machine Learning
• Data Collection & Exploration
• Data Communication and Visualization
• Data Engineering Fundamentals
• Data Exploration
• Data Factory with Hive
• Data Factory with Oozie and Hue
• Data Factory with Pig
• Data Filtering
• Data Flow for the Hadoop Ecosystem
• Data Flow Implementation
• Data Gathering
• Data Integration
• Data Lake: Architectures & Data Management Principles
• Data Lake: Framework & Design Implementation
• Data Load Options
• Data Mining, Data Distributions, & Hypothesis Testing
• Data Preprocessing
• Data Quality Projects
• Data Quality Services (DQS) and Master Data Services (MDS)
• Data Reduction & Exploratory Data Analysis (EDA)
• Data Refinery with YARN and MapReduce
• Data Repository with Flume
• Data Repository with HDFS and HBase
• Data Repository with Sqoop
• Data Rollbacks: Transaction Management & Rollbacks in NoSQL
• Data Rollbacks: Transaction Rollbacks & Their Impact
• Data Science 10: Data Research Exploration Techniques
• Data Science 2: Data Driven Organizations
• Data Science 9: Data Research Techniques
• Data Science Overview
• Data Science Statistics: Applied Inferential Statistics
• Data Science Statistics: Common Approaches to Sampling Data
• Data Science Statistics: Inferential Statistics
• Data Science Statistics: Simple Descriptive Statistics
• Data Science Statistics: Using Python to Compute & Visualize Statistics
• Data Scientist 14: Data Research Statistical Approaches
• Data Silos, Lakes, & Streams: Introduction
• Data Silos, Lakes, & Streams: Sources, Visualizations, & ETL Operations
• Data Silos, Lakes, and Streams: Data Lakes on AWS
• Data Sources: Implementing Edge on the Cloud
• Data Sources: Integration
• Data Tools: Machine Learning & Deep Learning in the Cloud
• Data Tools: Technology Landscape & Tools for Data Management
• Data Transformation
• Data Visualization and Predictive Analytics
• Data Visualization: Essentials
• Data Warehouse Essential: Architecure Frameworks and Implementation
• Data Warehouse Essential: Concepts
• Data Warehousing with Azure: Analytics and Reporting
• Data Warehousing with Azure: Architecture & Modeling Techniques
• Data Warehousing with Azure: Data Lake Implementation Using Azure
• Data Warehousing with Azure: Implementing Azure SQL Data Warehouse
• Data Warehousing with Azure: Managing Azure Data Lake
• Data Warehousing with Azure: Working with SQL Data Warehouse Objects
• Data Warehousing with Hadoop: HDInsight and Retail Sales Implementation Using Hive
• Data Warehousing with Hadoop: Managing Big Data Using HDInsight Hadoop
• Data Warehousing with Hadoop: Microsoft Analytics Platform System and Hive
• Data Warehousing with Hadoop: Spark, HDInsight and Cluster Management
• Data Wrangler 4: Cleaning Data in R
• Data Wrangling in R
• Data Wrangling with Pandas: Advanced Features
• Data Wrangling with Pandas: Visualizations and Time-Series Data
• Data Wrangling with Pandas: Working with Series & DataFrames
• Database Instances
• Database Maintenance and Performance Tuning in Oracle Database 12c
• Database Programmability Objects and Non-Relational Data
• Database Systems and Relational Databases
• Debugging in R
• Decision Tree and Classification Analysis
• Deep Learning with Keras
• Deploying Applications to Microsoft Azure SQL Databases
• Deploying Data Tools: Data Science Tools
• Deploying Hadoop Clusters
• Design Thinking for Innovation: Brainstorming and Ideation
• Design Thinking for Innovation: Defining Opportunities
• Design Thinking for Innovation: Prototyping and Testing
• Design Thinking for Innovation: Stakeholder Engagement
• Designing a Fact Table
• Designing and Implementing Dimensions
• Designing Batch Processing and Data Security
• Designing Control Flow
• Designing Data Flow
• Designing Hadoop Clusters
• Designing the Lambda Architecture and Real-time Processing
• Develop Real-time Processing Solutions with Apache Storm
• Developing SQL Databases Expert Live with Encore
• Developing with Blockchain
• DevOps for Data Scientists: Containers for Data Science
• DevOps for Data Scientists: Data DevOps Concepts
• DevOps for Data Scientists: Data Science DevOps
• DevOps for Data Scientists: Deploying Data DevOps
• Diving into the World of Spotfire
• Domain-Specific Tools in R
• Ecosystem for Hadoop
• Encore Session 1: Encryption, Data Access, Permissions, and Auditing
• Encore Session 1: Installing SQL Server Instances and Creating Databases
• Encore Session 1: SQL Server 2016 Database Objects, Indexes, and Views
• Encore Session 2: Backing Up and Restoring Databases
• Encore Session 2: Columnstore Indexes and Programmability Objects
• Encore Session 2: Manage Data in SQL 2012
• Encore Session 3: Managing Database Integrity
• Encore Session 3: Optimizing and Troubleshooting SQL 2012
• Encore Session 3: Triggers, Functions, Transactions, and Isolation Levels
• Encore Session 4: Managing Database Concurrency
• Encore Session 4: Monitoring Database Activity, Queries, and SQL Server Instances
• Encore Session 4: Recovering Databases, Configuring Mail, and Automating Tasks
• Encore Session 5: Implementing Security
• Encore Session 5: Managing Indexes and Statistics
• Encore Session 5: Optimize SQL Database Objects and Infrastructure
• Encore Session 6: Database Instances and Performance Tuning
• Encore Session 6: High Availability
• Encore Session 6: High Availability and Disaster Recovery
• Exploring Blockchain
• Filter and Modify Data in SQL Server 2016
• Framing Opportunities for Effective Data-driven Decision Making
• Fundamental Methods for Data Science in R
• GCP DevOps: CloudOps with Google Cloud Platform
• Generic Database Fundamentals: Architecture and Normalization Concepts
• Generic Database Fundamentals: Relation Algebra, SQL, and Concurrency Concepts
• Generic Design and Modeling Databases: Concepts and Conceptual Design
• Generic Design and Modeling Databases: Logical and Physical Design
• Getting Started with Hadoop: Advanced Operations Using MapReduce
• Getting Started with Hadoop: Developing a Basic MapReduce Application
• Getting Started with Hadoop: Filtering Data Using MapReduce
• Getting Started with Hadoop: Fundamentals & MapReduce
• Getting Started with Hadoop: MapReduce Applications With Combiners
• Getting Started with Hive: Bucketing & Window Functions
• Getting Started with Hive: Introduction
• Getting Started with Hive: Loading and Querying Data
• Getting Started with Hive: Optimizing Query Executions
• Getting Started with Hive: Optimizing Query Executions with Partitioning
• Getting Started with Hive: Viewing and Querying Complex Data
• Getting Started with Microsoft Azure HDInsight and Administering clusters
• Getting Started with Microsoft R
• Getting Started with the Software and Integrating Data
• Guiding the Analysis for Effective Data-driven Decision Making
• Hadoop Cluster Availability
• Hadoop Clusters
• Hadoop Distributed File System
• Hadoop HDFS: File Permissions
• Hadoop HDFS: Introduction
• Hadoop HDFS: Introduction to the Shell
• Hadoop HDFS: Working with Files
• Hadoop in the Cloud
• Hadoop Maintenance and Distributions
• Hadoop Ranger
• Hands-On Labs
• IBM BigInsights Fundamentals: Analyzing, Querying, and Extracting Big Data
• IBM BigInsights Fundamentals: Hadoop Solution
• Implementing Control Flow
• Implementing Governance Strategies
• Implementing Smart Contracts Using Ethereum
• Importing and Manipulating Data
• In Depth with NoSQL
• Indexers, Clusters, and Advanced Search
• Ingesting Data and Computing for Batch Processing
• Ingesting Data and Computing for Real-time Processing
• Installation of Hadoop
• Installing and Upgrading SQL Server 2016
• Interactive Processing using Apache Phoenix on HBase
• Interactive Queries with Spark SQL and Interactive Hive
• Introduction to Apache Spark
• Introduction to Data Modeling in Hadoop
• Introduction to Designing a Relational Database
• Introduction to Digital Currency
• Introduction to Hadoop
• Introduction to SQL
• Introduction to SQL: Managing Table Design
• Introduction to SQL: Multiple Tables and Advanced Queries
• Introduction to SQL: Views, Transactions, and SQL Security Architecture
• Java ASYNC Interface
• K-Nearest Neighbor (k-NN) & Artificial Neural Networks
• Kafka Integration with Spark
• Kafka Integration with Storm
• Kafka Real-time Applications
• Key Statistical Concepts
• Linear and Logistic Regression
• Linear Regression Models: An Introduction to Logistic Regression
• Linear Regression Models: Building Simple Regression Models with Scikit Learn and Keras
• Linear Regression Models: Introduction to Linear Regression
• Linear Regression Models: Multiple and Parsimonious Linear Regression
• Linear Regression Models: Simplifying Regression and Classification with Estimators
• Live Session 1: Encryption, Data Access, Permissions, and Auditing
• Live Session 1: Installing SQL Server Instances and Creating Databases
• Live Session 1: SQL Server 2016 Database Objects, Indexes, and Views
• Live Session 2: Backing Up and Restoring Databases
• Live Session 2: Columnstore Indexes and Programmability Objects
• Live Session 2: Manage Data in SQL 2012
• Live Session 3: Managing Database Integrity
• Live Session 3: Optimizing and Troubleshooting SQL 2012
• Live Session 3: Triggers, Functions, Transactions, and Isolation Levels
• Live Session 4: Managing Database Concurrency
• Live Session 4: Monitoring Database Activity, Queries, and SQL Server Instances
• Live Session 4: Recovering Databases, Configuring Mail, and Automating Tasks
• Live Session 5: Implementing Security
• Live Session 5: Managing Indexes and Statistics
• Live Session 5: Optimize SQL Database Objects and Infrastructure
• Live Session 6: Database Instances and Performance Tuning
• Live Session 6: High Availability
• Live Session 6: High Availability and Disaster Recovery
• Machine Learning Examples for Data Science in R
• Machine Learning, Propensity Score, & Segmentation Modeling
• Management of Relational Database Data
• Managing Activities and Data for Azure Big Data Analytics
• Managing an Oracle Database 12c Instance
• Managing Big Data Operations
• Managing Database Concurrency
• Managing HDInsight Data, Jobs, and Security
• MapReduce Essentials
• Math for Data Science & Machine Learning
• Microsoft Azure SQL Database Security
• Microsoft SQL Server 2012 – Developing Databases: CLR Integration
• Microsoft SQL Server 2012 – Developing Databases: Implementing Indexes
• Microsoft SQL Server 2012 – Developing Databases: Implementing Tables and Views
• Microsoft SQL Server 2012 – Developing Databases: Managing and Troubleshooting
• Microsoft SQL Server 2012 – Developing Databases: Stored Procedures
• Microsoft SQL Server 2012 – Developing Databases: Tuning and Optimizing Queries
• Microsoft SQL Server 2012 – Developing Databases: Working with Data
• Microsoft SQL Server 2012 – Developing Databases: Working with XML Data
• Microsoft SQL Server 2012 – Implementing a Data Warehouse: Design and Deployment
• Microsoft SQL Server 2012 – Implementing a Data Warehouse: ETL Solutions
• Microsoft SQL Server 2012: Configuring High Availability
• Microsoft SQL Server 2012: Creating Database Objects
• Microsoft SQL Server 2012: Creating Functions and Triggers
• Microsoft SQL Server 2012: Creating Programming Objects and Optimizing Queries
• Microsoft SQL Server 2012: Instance Configuration and Database Creation
• Microsoft SQL Server 2012: Managing Database Data
• Microsoft SQL Server 2012: Managing Databases and Automating Tasks
• Microsoft SQL Server 2012: Managing XML Data
• Microsoft SQL Server 2012: Manipulate Data Using Operators and Functions
• Microsoft SQL Server 2012: Querying Basics and Modifying Data
• Microsoft SQL Server 2014 - Designing BI Solutions: Availability and Recovery
• Microsoft SQL Server 2014 - Designing BI Solutions: BI Infrastructure Design
• Microsoft SQL Server 2014 - Designing BI Solutions: Data Models
• Microsoft SQL Server 2014 - Designing BI Solutions: Extract, Transform, and Load
• Microsoft SQL Server 2014 - Designing BI Solutions: MDX Queries and Performance
• Microsoft SQL Server 2014 - Designing BI Solutions: Reporting Services
• Microsoft SQL Server 2014 - Designing BI Solutions: SharePoint Integration
• Microsoft SQL Server 2014 - Designing Solutions: Backup and Recovery
• Microsoft SQL Server 2014 - Designing Solutions: Clustering and AlwaysOn
• Microsoft SQL Server 2014 - Designing Solutions: High Availability
• Microsoft SQL Server 2014 - Designing Solutions: Planning Infrastructure
• Microsoft SQL Server 2014 - Designing Solutions: Private Clouds
• Microsoft SQL Server 2014 - Designing Solutions: Windows Azure SQL Database
• Microsoft SQL Server 2014 - Developing Databases: New Features
• Microsoft SQL Server 2014: Create and Manage Tabular Data Models
• Microsoft SQL Server 2014: Design and Implement Dimensions
• Microsoft SQL Server 2014: Design and Install Analysis Services and Tools
• Microsoft SQL Server 2014: Design Reports and Create Data Sources and Datasets
• Microsoft SQL Server 2014: Designing Multidimensional Models and Data Sources
• Microsoft SQL Server 2014: Manage Reporting Services
• Microsoft SQL Server 2014: Manage, Maintain, and Troubleshoot SSAS
• Microsoft SQL Server 2014: MDX Queries, Process Models, and Deploy Databases
• Microsoft SQL Server 2014: Process Report and Create Subscriptions and Schedules
• Microsoft SQL Server 2014: Report Formatting and Interactivity
• Microsoft SQL Server 2016 First Look: Preview
• Microsoft SQL Server 2016: Auditing
• Microsoft SQL Server 2016: Backing Up Databases
• Microsoft SQL Server 2016: Data Access and Permissions
• Microsoft SQL Server 2016: Encryption
• Microsoft SQL Server 2016: High Availability and Disaster Recovery
• Microsoft SQL Server 2016: Managing Database Integrity
• Microsoft SQL Server 2016: Managing Indexes and Statistics
• Microsoft SQL Server 2016: Monitoring Database Activity and Queries
• Microsoft SQL Server 2016: Monitoring SQL Server Instances
• Microsoft SQL Server 2016: Restoring Databases
• Microsoft SQL Server Data Warehousing and Business Intelligence Overview
• Microsoft SQL Server: Implement and Configure Cubes
• Microsoft SQL Server: Implement Partitions and Custom Logic
• Migrating Client Applications
• Model Development, Validation, & Evaluation
• Model Life Cycle Management
• Modifying and Summarizing Data
• MongoDB for Data Wrangling: Aggregation
• MongoDB for Data Wrangling: Querying
• MongoDB: Backups, Monitoring, and Stats
• MongoDB: Cloud and Hadoop Deployments
• MongoDB: Indexes and Query Optimization
• MongoDB: Installation Overview
• MongoDB: Integration with Python
• MongoDB: Integration with Spark
• MongoDB: Java REST and GridFS
• MongoDB: Map Reduce, Atomic Counters, and Binary Data
• MongoDB: Replication and Security
• MongoDB: System Management
• MongoDB: User Management
• MongoDB: Write, Read, and Aggregate Data
• More Spotfire Visualization Techniques
• Motivating Action with a Compelling and Data-driven Story
• MySQL Database Development: Database Design Fundamentals
• MySQL Database Development: DDL Statements
• MySQL Database Development: GIS, Cloud, and Connectors for MySQL
• MySQL Database Development: Introduction
• MySQL Database Development: Manipulating Data
• MySQL Database Development: Query and Performance Optimization
• MySQL Database Development: SELECT Statement and Operators
• MySQL Database Development: Stored Routines, Triggers, and the InnoDB memcached Plugin
• MySQL Database Development: Working with Functions
• MySQL: Administration, Transactions, Optimization, Scaling, Backup, and Recovery
• MySQL: Advanced Routines, Optimization, and DCL
• MySQL: Creating & Updating Tables
• MySQL: Database Concepts, Design, and Installation
• MySQL: General Syntax, Advanced Queries, and Stored Programs
• MySQL: Getting Started
• MySQL: Grouping & Aggregation Operations
• MySQL: Performance Monitoring, Database Health and Integrity, and Security
• MySQL: Querying Data
• MySQL: Querying Data Using the SELECT Statement
• MySQL: Storage Engines, Advanced Indexing, and Maintenance
• MySQL: Transactions, Savepoints, & Locks
• MySQL: Triggers & Stored Procedures
• MySQL: Understanding & Implementing Joins
• MySQL: Using the Data Manipulation and Definition Statements
• MySQL: Views, Indices, & Normal Forms
• NoSQL Concepts and Background
• NoSQL for FSD Development
• NoSQL Models and Applications
• Operating Hadoop Clusters
• Operationalize and Design with Spark
• Operators and Expressions in SQL Server 2016
• Optimize SQL Database Objects and Infrastructure
• Optimizing the Customer Experience
• Oracle 12c Performance Tuning: Application Monitoring and SQL Diagnostics
• Oracle 12c Performance Tuning: Automatic Workload Repository
• Oracle 12c Performance Tuning: Introduction
• Oracle 12c Performance Tuning: Measuring and Maintaining SQL Performance
• Oracle 12c Performance Tuning: Metrics and Monitoring
• Oracle 12c Performance Tuning: Performance Tuning Summary
• Oracle 12c Performance Tuning: Tuning Instance Memory
• Oracle 12c Performance Tuning: Tuning Problem SQL Statements
• Oracle Database 11g Release 2: Application Performance Enhancements
• Oracle Database 11g Release 2: ASM, Storage and Partitioning Enhancements
• Oracle Database 11g Release 2: Backup and Recovery
• Oracle Database 11g Release 2: Backup, Recover, Archive, and Repair Data
• Oracle Database 11g Release 2: Database Architecture and Installation
• Oracle Database 11g Release 2: Database Architecture and Recovery Operations
• Oracle Database 11g Release 2: Database Creation and Instance Management
• Oracle Database 11g Release 2: Database Diagnostics and Flashback Technologies
• Oracle Database 11g Release 2: Diagnosability Enhancements
• Oracle Database 11g Release 2: Installation and Oracle Restart
• Oracle Database 11g Release 2: Intelligent Infrastructure Enhancements
• Oracle Database 11g Release 2: Managing Concurrency, Undo, and Auditing
• Oracle Database 11g Release 2: Managing Database Maintenance and Performance
• Oracle Database 11g Release 2: Managing Database Memory and Performance
• Oracle Database 11g Release 2: Managing Database Resources and the Scheduler
• Oracle Database 11g Release 2: Managing Database Space and Duplication
• Oracle Database 11g Release 2: Moving Data and Oracle Support
• Oracle Database 11g Release 2: Oracle Partitioning and Security Features
• Oracle Database 11g Release 2: Oracle Scheduler and Secure Backup
• Oracle Database 11g Release 2: Performing Restore and Recovery Tasks
• Oracle Database 11g Release 2: SQL Monitoring and Performance Enhancements
• Oracle Database 11g Release 2: Storage Structures and User Security
• Oracle Database 11g Release 2: The ASM Instance and Network Connectivity
• Oracle Database 11g Release 2: The RMAN Catalog and Creating Backups
• Oracle Database 11g Release 2: Using Change Management Solutions
• Oracle Database 11g Release 2: Using, Monitoring and Tuning RMAN
• Oracle Database 11g: Configure, Manage, and Use Services in RAC
• Oracle Database 11g: Installation of Clusterware and RAC
• Oracle Database 12c - Backup and Recovery: Configuring for Recoverability
• Oracle Database 12c - Backup and Recovery: Duplicating Databases and Tuning RMAN
• Oracle Database 12c - Backup and Recovery: Failure and Recovery Concepts
• Oracle Database 12c - Backup and Recovery: Perform Recovery and Secure Backup
• Oracle Database 12c - Backup and Recovery: Performing and Managing Backups
• Oracle Database 12c - Backup and Recovery: Transporting Data and Performing PITR
• Oracle Database 12c - Backup and Recovery: Using Flashback Technologies
• Oracle Database 12c - Introduction to SQL: Data Conversion and Aggregating Data
• Oracle Database 12c - Introduction to SQL: Data Manipulation Language
• Oracle Database 12c - Introduction to SQL: Relational Database and SQL Developer
• Oracle Database 12c - Introduction to SQL: Restrict, Sort, and Customize Output
• Oracle Database 12c - Introduction to SQL: SQL*Plus and SELECT Statement
• Oracle Database 12c - Introduction to SQL: Working with Joins and Subqueries
• Oracle Database 12c - Introduction to SQL: Working with SET Operators and DDL
• Oracle Database 12c – Install and Upgrade: Database Architecture
• Oracle Database 12c – Install and Upgrade: Installation
• Oracle Database 12c – Install and Upgrade: Upgrading
• Oracle Database 12c R2 SQL: Controlling User Access
• Oracle Database 12c R2 SQL: Conversion Functions and Conditional Expressions
• Oracle Database 12c R2 SQL: Creating Other Schema Objects
• Oracle Database 12c R2 SQL: Data Definition Language (DDL)
• Oracle Database 12c R2 SQL: Data Manipulation Language and Transaction Control Language
• Oracle Database 12c R2 SQL: Displaying Data from Multiple Tables
• Oracle Database 12c R2 SQL: Managing Objects with Data Dictionary Views 
• Oracle Database 12c R2 SQL: Managing Schema Objects    
• Oracle Database 12c R2 SQL: Manipulating Data Using Advanced Queries
• Oracle Database 12c R2 SQL: Reporting Aggregated Data Using the Group Functions   
• Oracle Database 12c R2 SQL: Restricting and Sorting Data
• Oracle Database 12c R2 SQL: SQL*Plus
• Oracle Database 12c R2 SQL: Using Basic SELECT statements
• Oracle Database 12c R2 SQL: Using Single-Row Functions to Customize Output   
• Oracle Database 12c R2 SQL: Using Structured Query Language (SQL)
• Oracle Database 12c R2 SQL: Using Subqueries to Solve Queries 
• Oracle Database 12c R2 SQL: Using the Set Operators
• Oracle Database 12c RAC Administration: Backup and Recovery
• Oracle Database 12c RAC Administration: Client Connections and QoS
• Oracle Database 12c RAC Administration: Day-to-Day Administration
• Oracle Database 12c RAC Administration: Global Resource Management
• Oracle Database 12c RAC Administration: Installing, Configuring, and Patching
• Oracle Database 12c RAC Administration: Introduction to Oracle RAC
• Oracle Database 12c RAC Administration: Monitoring and Tuning
• Oracle Database 12c RAC Administration: Services and Multitenant Architecture
• Oracle Database 12c: Enterprise Manager Cloud Control and Creating CDB and PDB
• Oracle Database 12c: High Availability and Database Management
• Oracle Database 12c: Managing CDB and PDB, and Data Optimization
• Oracle Database 12c: Managing Security
• Oracle Database 12c: Resource Manager, Online Operations, and ADR
• Oracle Database 12c: Transporting Databases and Managing Data
• Oracle Database 12c: Tuning SQL and Using ADDM
• Oracle Database 12c: Using Automatic Data Optimization, Storage, and Archiving
• Packages and Data Types
• Performance Tuning
• Performance Tuning of Hadoop Clusters
• Planning AI Implementation
• Positioning Powerful Messages to Enable Action
• Post-Test 1: Encryption, Data Access, Permissions, and Auditing
• Post-Test 1: Installing SQL Server Instances and Creating Databases
• Post-Test 1: SQL Server 2016 Database Objects, Indexes, and Views
• Post-Test 2: Backing Up and Restoring Databases
• Post-Test 2: Columnstore Indexes and Programmability Objects
• Post-Test 2: Manage Data in SQL 2012
• Post-Test 3: Managing Database Integrity
• Post-Test 3: Optimizing and Troubleshooting SQL 2012
• Post-Test 3: Triggers, Functions, Transactions, and Isolation Levels
• Post-Test 4: Managing Database Concurrency
• Post-Test 4: Monitoring Database Activity, Queries, and SQL Server Instances
• Post-Test 4: Recovering Databases, Configuring Mail, and Automating Tasks
• Post-Test 5: Implementing Security
• Post-Test 5: Managing Indexes and Statistics
• Post-Test 5: Optimize SQL Database Objects and Infrastructure
• Post-Test 6: Database Instances and Performance Tuning
• Post-Test 6: High Availability
• Post-Test 6: High Availability and Disaster Recovery
• PostgreSQL Database Fundamentals Part #1
• PostgreSQL Database Fundamentals Part #2
• Powering Recommendation Engines: Recommendation Engines
• Practice Exam: SQL 2012 Admin
• Pre-Test 1: Encryption, Data Access, Permissions, and Auditing
• Pre-Test 1: Installing SQL Server Instances and Creating Databases
• Pre-Test 1: SQL Server 2016 Database Objects, Indexes, and Views
• Pre-Test 2: Backing Up and Restoring Databases
• Pre-Test 2: Columnstore Indexes and Programmability Objects
• Pre-Test 2: Manage Data in SQL 2012
• Pre-Test 3: Managing Database Integrity
• Pre-Test 3: Optimizing and Troubleshooting SQL 2012
• Pre-Test 3: Triggers, Functions, Transactions, and Isolation Levels
• Pre-Test 4: Managing Database Concurrency
• Pre-Test 4: Monitoring Database Activity, Queries, and SQL Server Instances
• Pre-Test 4: Recovering Databases, Configuring Mail, and Automating Tasks
• Pre-Test 5: Implementing Security
• Pre-Test 5: Managing Indexes and Statistics
• Pre-Test 5: Optimize SQL Database Objects and Infrastructure
• Pre-Test 6: Database Instances and Performance Tuning
• Pre-Test 6: High Availability
• Pre-Test 6: High Availability and Disaster Recovery
• Predictive Analytics & Big Data
• Predictive Modelling Best Practices: Applying Predictive Analytics
• Preparing Impactful Presentations that Drive Decision Makers to Action
• Process & Application
• Programmability Objects
• Programming Techniques in R
• Programming with NoSQL
• Provisioning an Azure Data Factory
• Python for Data Science – Introduction to Python for Data Science
• Python for Data Science: Advanced Data Visualization Using Seaborn
• Python for Data Science: Advanced Operations with NumPy Arrays
• Python for Data Science: Basic Data Visualization Using Seaborn
• Python for Data Science: Introduction to NumPy for Multi-dimentional Data
• Python for Data Science: Introduction to Pandas
• Python for Data Science: Manipulating and Analyzing Data in Pandas DataFrames
• Quality and Security of Big Data Operations
• Querying and Manipulating Data
• R for Data Science: Classification & Clustering
• R for Data Science: Data Exploration
• R for Data Science: Data Structures
• R for Data Science: Data Visualization
• R for Data Science: Importing and Exporting Data
• R for Data Science: Regression Methods
• Random Forests & Uplift Models
• RavenDB Integration
• RavenDB Overview
• Raw Data to Insights: Data Ingestion & Statistical Analysis
• Raw Data to Insights: Data Management & Decision Making
• Regression Analysis
• Research Topics in ML and DL
• Script Components
• Scripting with Spotfire
• Securing Blockchain Implementations
• Securing Hadoop Clusters
• Serving Digital Customers with Omnichannel
• Spark Monitoring and Tuning
• Spark Security
• Splunk Administration
• Splunk Fundamentals
• Splunk Visualizations and Dashboards
• Spotfire Automation, Analyzation, and Visualization
• Spotfire Basics
• Spotfire Data Combinations
• Spotfire Visualizations and Relationships
• SQL Server 2016 Database Objects
• SQL Server 2016 Indexes and Views
• SQL Server Database Fundamentals: Creating, Optimizing, and Securing Databases
• SQL Server Database Fundamentals: Design Principles and Data Manipulation
• SQL Server Instances and Storage Considerations
• SQL Server Performance Settings
• SQL Server Virtual Machines on Azure
• SQL Tuning, Resource Management, and Job Scheduling in Oracle Database 12c
• SSIS Components
• SSIS Package Execution and Script Tasks
• SSIS Packages
• SSIS Security
• SSIS Solutions
• SSIS Variables
• Stabilizing Hadoop Clusters
• Streaming Data Architectures: An Introduction to Streaming Data
• Streaming Data Architectures: Processing Streaming Data
• Structured Streaming
• Subqueries and Predicate
• T-SQL Querying
• Tableau Advanced Visualizations
• Tableau Calculations
• Tableau Charts
• Tableau Dashboards and Data Organization
• Tableau Data Connections
• Tableau Desktop: Real Time Dashboards
• Tableau Interface and Sharing
• Tableau Maps
• Tableau Scripting
• Tableau Time Dimensions
• Tableau Visualization
• Tableau Visualization Design
• Teradata Basics: Communication and Database Security
• Teradata Basics: Data Storage and Access Methods
• Teradata Basics: Relational Database and Data Warehouse Basics
• Teradata SQL: DDL, DML, and SQL Optimization
• Teradata SQL: Functions, Data Conversions, and Working with Time
• Teradata SQL: The SELECT Statement, Joins, and Subqueries
• Text Mining & Social Network Analysis
• The Basics of Blockchain
• The Big Data Technology Wave
• The R Language and Big Data Processing
• Time Series Modeling
• Transactions and Isolation Levels
• Trifacta for Data Wrangling: Wrangling Data
• Triggers and Functions
• Troubleshooting Data Integration
• Understanding and Raising Analytics Maturity
• Understanding the Digital Customer
• User Security and Auditing in Oracle Database 12c
• Using Data to Find Data: Correction & Categorization
• Using Data to Find Data: Data Discovery & Exploration
• Using Functions in SQL Server 2016
• Using Your Data with Splunk
• Working with Bitcoin
• Working with Cassandra
• Working with Data for Effective Decision Making
• Working with Data Mapping, Jobs, and Automation
• Working with HDInsight Clusters