Complete Data Visualization with Machine Learning

  • Duration – 20 hour

 

  • Course completion certificate
  • Mode of Study – Self Paced Learning
  • 24/7 support

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Complete Data Visualization with Machine Learning

Section 1: Course Introduction

 

  1. Introduction

 

  1. Course Sections and LearningOutcomes

 

  1. Resources

 

  1. Future of Analytics and InnovationCycle for Analytics

 

  1. Setup Oracle Analytics DataVisualization Environment

 

Section 2: Selecting Data Sets from Different Data Sources

 

  1. Introduction to Data Sets and DataSources

 

  1. Built-in Data Connectors with OracleAnalytics

 

  1. Connect to Relational Database andCreate Data Set for Visualization

 

  1. Oracle Essbase Connection to CreateData Set for Visualization

 

  1. Connect to Big Data Source to BuildVisualization

 

  1. SaaS Application as a Source for DataSet and Visualization

 

  1. Oracle Autonomous Database as aSource for Data Sets

 

  1. Leverage Snowflake Connection toCreate Data Sets

 

  1. Management of Data Sets and DataConnections

 

Section 3: Data Flow Deep-Dive with Oracle Analytics

 

  1. Introduction to Data Flow Business

 

  1. Build Your First Data Flow -Comprehensive Overview of Data Flow …

 

  1. Run and Manage Your Data FlowProcess

 

  1. Create Multiple Targets with SingleData Flow!

 

  1. Create Execution Sequence withMultiple Data Flows

 

  1. Store Your Data Flow Target Data

 

Section 4: Advanced Analytics Made Easy with Oracle Analytics

 

  1. Introduction to Business Use Case forAdvanced Analytics

 

  1. Create Reference Line to Examineyour Data

 

  1. Create Trend-line to UnderstandProgressive Stat of Measure in your Data

 

  1. Create Clusters and Outliers on DataUsing Single Click Analytics

 

  1. Compare and Understand Outlierswith ‘Explain’ Driven Analysis

 

  1. Leverage Expression Builder to createAdvanced Analytic Function

 

  1. Story Telling Your Discovery for SalesPerformance

 

Section 5: Machine Learning with Data Visualization

 

  1. Introduction to Business Use Case forMachine Learning

 

  1. Analytics Tasks Classification

 

  1. Basics of Machine LearningAlgorithms

 

  1. Learn to Make Machine Learn!

 

  1. Machine Learning for Business Users

 

  1. Bike Rental Data Exploration forMachine Learning

 

  1. Build Regression Based Model forBike Rental Use Case

 

  1. Evaluate Machine Learning ModelPerformance

 

  1. Leverage Model to Predict FutureBike Rentals

 

  1. Dynamic Analysis with ScenarioModeling

 

  1. Demo Bonus Project: PredictingChronic Kidney Disease

 

Section 6: Top 10 Features Worth Learning about Oracle Analytics

 

  1. Introduction to Top 10 Features ofOracle Analytics Cloud

 

  1. Top 5 Features for Stunning VisualExperience

 

  1. Top 5 Features for Machine LearningDriven Augmented Analytics

 

  1. Demo: Top 10 Features

 

  1. Thank You!

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What People Are Saying

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