EncartaLabs

Oracle Machine Learning with Autonomous Database

In Oracle Machine Learning with Autonomous Database - Essentials training course delegates will learn to provision and use Oracle Autonomous Database and Analytics Cloud service instances with Oracle Machine Learning. Experience the ease of performing predictive analysis of data on Oracle Cloud.

The Oracle Machine Learning with Autonomous Database - Advanced training course enables you to use Oracle Machine Learning with Oracle Autonomous Database so that you can implement Predictive Analysis. This is a great starting point for data scientists, developers, business users, and anyone who wants to learn about the algorithms and key features of Oracle Machine Learning.

By attending Oracle Machine Learning with Autonomous Database - Essentials workshop, delegates will learn to:

  • Describe the key features of Oracle Machine Learning
  • Create Projects and workspaces, and manage users in Oracle Machine Learning
  • Crete and run Oracle Machine Learning Notebooks
  • Develop SQL Scripts that can be used in Notebooks
  • Create Notebooks for data analysis and Data Visualization
  • Collaborate and share Notebooks with other Oracle Machine Learning users
  • Schedule Jobs to run Notebooks
  • Use Analytics Cloud to create data visualizations
  • Extract data for analytics from Autonomous Data Warehouse and Autonomous Transaction Processing Cloud service instances
  • Use Machine Learning feature in Oracle Analytics Cloud

By attending Oracle Machine Learning with Autonomous Database - Advanced workshop, delegates will learn :

  • The creation of notebooks, projects, workspaces, and assigning workspace permissions to users
  • How to develop SQL Scripts and running SQL commands in a paragraph of OML
  • Statistical functions to make use of Oracle Database
  • Different machine learning algorithms like the Classification Model, the types of classification algorithms, regression, and building a use case
  • Attribute Importance, Anomaly Detection, Clustering, Association Rules, Feature Extraction, and Time Series along with the use cases

For Oracle Machine Learning with Autonomous Database - Essentials
  • Working knowledge of SQL and PL/SQL
  • General understanding of statistics and probability
For Oracle Machine Learning with Autonomous Database - Advanced
  • Attend a training on Oracle Machine Learning with Autonomous Database - Essentials or have equivalent knowledge
For Oracle Machine Learning with Autonomous Database - Essentials
  • Analyst
  • Data Scientist
  • Manager
For Oracle Machine Learning with Autonomous Database - Advanced
  • Data Scientist
  • Integration developers
  • Business users
  • Analyst

COURSE AGENDA

Oracle Machine Learning with Autonomous Database - Essentials
(Duration : 3 Days)

1

Course Overview

  • Target Audience
  • Prerequisites
  • Course Roadmap
  • Use Case: El Tronics
  • Course Persona
  • Course Practices
  • Sample Database Schemas Used in the Course
2

Introduction to Oracle Machine Learning and Oracle Autonomous Cloud Platform

  • Growth of Oracle Machine Learning
  • Oracle Machine Learning: Features & Components
  • Compatible Oracle Cloud Services
  • Oracle Cloud Platform Autonomous Services
  • Oracle Autonomous Database
  • Oracle Analytics Cloud
  • Autonomous Data Warehouse Cloud: Use Cases
3

Creating Workspace and Projects in Oracle Machine Learning

  • Accessing the Oracle Machine Learning Home Page
  • Creating a New Project and Workspace
  • Managing Workspaces Permissions
4

Creating SQL Scripts and Running SQL Commands in Oracle Machine Learning

  • SQL Script Scratchpad
  • Developing & Running SQL Scripts
  • Exporting and Importing SQL Scripts
  • Restrictions on SQL Commands
  • Restrictions for Database Options
  • Restrictions for Database Initialization Parameters
  • Connection Groups
5

Notebooks in Oracle Machine Learning

  • Examples: OML Notebook
  • Creating & Editing a Notebook
  • Typical Workflow for Analyzing Data with Oracle Machine Learning
  • Traditional Programming Versus Machine Learning
  • Creating Text Input Forms in Notebooks
  • Creating Select Forms in Notebooks
  • Creating Check Box Forms in Notebooks
  • Setting Up an Output Format
6

Collaborating Using Templates in Oracle Machine Learning

  • Templates in Oracle Machine Learning
  • Saving a Notebook as Template in Oracle Machine Learning
  • Sharing Templates
  • Editing Template Settings
  • Collaborate Using the Export Option
7

Working with Jobs in Oracle Machine Learning

  • Jobs in Oracle Machine Learning
  • Creating a Job
  • Viewing Job Logs
8

Administering Oracle Machine Learning

  • Workflow for Managing Oracle Machine Learning
  • User Data
  • Compute Resource
  • Creating User Accounts for Oracle Machine Learning
9

Working with Oracle Machine Learning using Autonomous Transaction Processing Cloud

  • Autonomous Transaction Processing
  • Typical Workflow for Autonomous Transaction Processing, and Other Services and Tools
  • Using Oracle Machine Learning with Autonomous Transaction Processing
  • K-means Algorithm
  • Oracle Machine Learning for Data Access, Analysis, and Discovery
10

Creating Visualizations in Oracle Machine Learning Using Analytics Cloud

  • Oracle Analytics Cloud
  • Creating Connections to Oracle Autonomous Data Warehouse Cloud
  • Create Connections to Autonomous Transactional Processing Cloud
  • Use Machine Learning to Analyze Data by Using Oracle Analytics Cloud
  • Using Data Flow to Curate Data Sources
  • Running Data Flows
  • Prediction Visualization
Oracle Machine Learning with Autonomous Database - Advanced
(Duration : 3 Days)

1

Overview

  • Overview of the topics covered
  • List the prerequisites for this course
  • Describe the schedule of the course
2

Using Statistical Functions

  • An overview of statistical functions
  • List the advantages of performing statistical functions inside the database
  • Explain the descriptive statistics supported inside the database
  • Describe hypothesis testing and work through some examples
  • Describe correlation analysis and work through some examples
  • Describe cross-tabulations and work through some examples
3

Classification Model

  • Overview of classification modeling
  • Describe the testing of a classification model
  • Describe biasing a classification model
  • List the types of classification algorithms (Decision Tree, Naive Bayes, Generalized Linear Models, Random Forest, Support Vector Machines, Neural Network, MSET-SPRT, XGBoost)
4

Regression

  • Describe regression modeling
  • Describe the testing of a regression model
  • List the types of regression algorithms (Generalized Linear Models, Neural Network, Support Vector Machines)
5

Using Attribute Importance

  • Overview of attribute importance
  • List the types of attribute importance algorithms (Minimum Description Length, Principal Comp Analysis, CUR matrix decomposition)
6

Implementing Anomaly Detection

  • Describe anomaly detection
  • Explain the anomaly detection algorithm (One-Class Support Vector Machines)
  • Discuss and recognize applicable use cases
7

Using Clustering

  • Describe clustering
  • Explain hierarchical clustering
  • Discuss how to evaluate a clustering model
  • List the types of clustering algorithms (Expectation Maximization, k-Means, Orthogonal Partitioning Clustering)
8

Association Rules

  • Describe association rules
  • Explain transactional data
  • Discuss the Apriori algorithm, a type of association algorithm
9

Using Feature Selection and Extraction

  • Describe feature selection
  • Describe feature extraction
  • List the types of feature extraction algorithms:
    • Explicit Semantic Analysis
    • Non-Negative Matrix Factorization
    • Singular Value Decomposition
    • Prediction Component Analysis
10

Using Time Series

  • Describe time series
  • Select a time series model
  • Explain time series statistics
  • Discuss Exponential Smoothing, a type of time series algorithm

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

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Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

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