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HONE YOUR SKILLS AND UPGRADE YOUR STATUS AND INCOME. EARN MINIMUM £60K WITH YOUR MACHINE LEARNING AND R SKILLS.

VERY GOOD HANDS-ON TRAINING MATERIAL WITH REAL-LIFE BASED SCENARIOS. PACKED WITH TASKS AND ACTIVITIES.

PERFECT SELF-TEACH TRAINING COURSE FOR ANALYTICS DEVELOPERS, DATA WAREHOUSING DEVELOPERS, BI CONSULTANTS AND DEVELOPERS WHO WORK WITH EITHER SAP, MICROSOFT OR IBM BI TOOLS BUT LOOKING TO UPSKILL TO A MACHINE LEARNING WITH R AND DATA SCIENCE ENVIRONMENT.

Predictive Analytics with Oracle Machine Learning for R (OML4R) Self-Study CBT

How this Course is Organised

The Predictive Analytics with Oracle Machine Learning for R (OML4R) course will teach you how to leverage the Oracle Database as a high performance computing platform from the powerful R statistical programming language and environment. Overcome the memory limitations of the open source client R engine.

Prepare data, perform statistical analysis, and build predictive models on Big Data data sets that are generally impossible with open source R. Generate graphics and invoke R scripts from SQL for integration with the Oracle stack.

In addition, you'll learn how to tap into the Oracle Machine Learning Notebook platform; Learn how to create a project, a workspace, a notebook and Run your notebook. See how two or more users can collaborate and share notebooks with other Oracle Machine Learning users. Create, use, share, and run SQL scripts.

Oracle has adopted R as a language and environment to support statisticians, data analysts, and data scientists in performing statistical data analysis and advanced analytics, as well as generating sophisticated graphics. Oracle Machine Learning for R (OML4R), formerly Oracle R Enterprise (ORE) is a component of the Oracle Database Advanced Analytics Option. OML4R makes the open source R statistical programming language and environment ready for the enterprise and big data.

Audience:

Business and Data Analysts

Data and database professionals

Data Science and big data developers

Project Managers of teams of business intelligence, Analytics, and Big Data professionals

Prerequisite: None

Suggested Prerequisite

Oracle Database 11g/12c SQL

Required Prerequisite

Experience with statistics or R programming experience

Objectives:

Understand Predictive Analytics and Machine Learning Concepts

Explain data mining concepts and describe the benefits of predictive analysis

Understand the Oracle Advanced Analytics (OAA) Option

Understand Oracle Machine Learning for R (OML4R)

Start up R, load OML4R, and connect to Oracle Database

Apply R Language Basics

Use the OML4R Transparency Layer

Use OML4R for embedded R execution

Use OML4R predictive analytics packages

Interact directly with Oracle Database objects using ROracle

Create Projects and Workspaces in Oracle Machine Learning

Create and Running Notebooks in Oracle Machine Learning

Collaborate in Oracle Machine Learning

Creating a SQL Script in Oracle Machine Learning

Running SQL Statements in Oracle Machine Learning

Topics

Getting Started with Predictive Analytics and Machine Learning

Business Drivers of Predictive Analytics

Technology Enablers

Organizational Factors

The Organizational Culture

The Business Environment

The People

The I/T Architecture

The Data

The Predictive Analytics Tools

The Project

Predictive Analytics and Machine Learning Concepts

What is Predictive Analytics?

Introducting the Oracle Advanced Analytics (OAA) Option

Introducing Oracle R Enterprise (ORE)

Introducing ORE Predictive Analytics

Supported Machine Learning Algorithms and Uses

The Predictive Analytics Process

Predictive Analytics as a process

Supervised Versus Unsupervised Learning

Define the business problem

Identify the business problem

Typical Machine Learning business problems

Identify the analytical approach

Build and deploy Predictive Analytics

Data preparation

Machine Learning

Deploying the solution

Take action and measure results

Introduction to Data Science

Overview of Data Science

What Is Data Science?

The Data Science Process

Overview of the Data Science Process

Example of the Data Science Process

Introduction to Machine Learning

Understanding Machine Learning

Introduction to Classification

Introduction to Regression

Statistical Learning Theory

Introduction to Clustering

Introduction to Recommendation

Introduction to Data Science Technologies

Introduction to Open-Source tools - R and Python

Introduction to R for Data Science

Introduction to Python for Data Science

Introduction to Oracle Advanced Analytics

Introduction to Oracle Machine Learning for R (OML4R)

Introducing Oracle Machine Learning for R (OML4R)

Introduction to Oracle Machine Learning

Using R: What, Who, and Why?

R User Interfaces

Oracle’s Strategy for Machine Learning for R (OML4R)

Getting Started with ORE

Prerequisites for Using ORE

Starting R and Loading ORE

Basic Database Interaction with ORE

Introducing the R Language and Environment

Accessing R Help

R language basics

Debugging with R

Producing Graphs in R and ORE

R Graph Types

R Graphics Packages

Overloaded Functions for ORE

Using the ORE Transparency Layer - Part 1

Introducing the Transparency Layer

Working with Oracle Database

ORE Packages, Classes, and Functions

Common Data Transformations and Data Type Mapping

Using the ORE Transparency Layer - Part 2

Object Persistence

Ordering Framework

In-database Sampling and Random Partitioning

Case Study Examination

ORE Embedded R Execution - R Interface

Rationale for Embedded R Execution

Embedded R Execution

Connecting to Databases from an Embedded R Function

Generating Graphs within an Embedded R Function

ORE Embedded R Execution - SQL Interface

Embedded R Execution

Using R Scripts in the Database Repository

Generating Output Using rq*Eval Functions

Parallel Execution for Embedded R Scripts

Using ORE Predictive Analytics - Part 1

Using Functions in the OREdm Package

Using Functions in the OREmodels Package

Using ORE Predictive Analytics - Part 2

Scoring data within R models in the database

Preparing Time Series Data

Exponential Smoothing for Time Series Data Predictions

Using ROracle for Direct Database Access

What is ROracle?

Authentication

Table Access Methods

Query Execution

Rollback

Creating Projects and Workspaces in Oracle Machine Learning

Creating and Running Notebooks in Oracle Machine Learning

Collaborating in Oracle Machine Learning

Creating a SQL Script in Oracle Machine Learning

Running SQL Statements in Oracle Machine Learning

NOTE: THIS COURSE IS ALSO AVAILABLE IN SELF-STUDY TRAINING GUIDE OR DISTANCE LEARNING FORMATS. FEEL FREE TO ASK IF YOU PREFER DISTANCE, E-LEARNING OR TRAINING GUIDE EARNING FORMATS. PRICES DIFFER

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