About this Course

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Intermediate Level
Approx. 9 hours to complete
English

Skills you will gain

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 9 hours to complete
English

Offered by

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IBM

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

Building a Rapid Prototype with Watson Studio AutoAI

2 hours to complete
7 videos (Total 36 min), 14 readings, 4 quizzes
7 videos
Introducing AutoAI2m
Watson Studio Platform Basics2m
Building Rapid Prototypes Demo Introduction2m
Classification Demo11m
Examining the Notebook4m
Regression Demo9m
14 readings
Course Prerequisites2m
Learning Outcomes2m
AutoAI Implementations2m
References2m
Summary2m
Learning Outcomes2m
Watson Studio Setup20m
Watson Studio Lab (Activity)20m
Summary2m
Learning Outcomes2m
References2m
Building Rapid Prototypes Lab (Activity)30m
Summary2m
Summary/Review2m
4 practice exercises
Check for Understanding5m
Check for Understanding5m
Check for Understanding5m
End of Module Quiz5m
Week
2

Week 2

2 hours to complete

Automated Data Preparation and Model Selection

2 hours to complete
9 videos (Total 34 min), 11 readings, 3 quizzes
9 videos
Automated Data Preparation10m
Classification Prep Demo3m
Regression Prep Demo4m
The model selection problem2m
Multi-armed Bandit Approach4m
DAUB Algorithm5m
Demo Classification: Making Changes to the Models1m
Demo Regression: Making Changes to the Models1m
11 readings
Learning Outcomes2m
Building the Prototype: Prep (graphic)2m
References2m
Data Preparation Lab (Activity)30m
Summary2m
Learning Outcomes2m
Building the Prototype: Model selection (graphic)2m
References10m
Model Selection Lab (Activity)30m
Summary2m
Summary/Review2m
3 practice exercises
Check for Understanding5m
Check for Understanding5m
End of Module Quiz5m
Week
3

Week 3

2 hours to complete

Automated Feature Engineering and Hyperparameter Optimization

2 hours to complete
9 videos (Total 36 min), 11 readings, 3 quizzes
9 videos
Automated Feature Engineering6m
Cognito - Transforms and the Transformation Graph4m
Cognito - Transformation Graph Exploration3m
Demo Classification: Feature Engineering6m
Demo Regression: Feature Engineering3m
Automated HPO5m
RBFOpt2m
HPO Demo3m
11 readings
Learning Outcomes2m
Building the Prototype: Feature Engineering (graphic)2m
References2m
Feature Engineering Lab (Activity)30m
Summary2m
Learning Outcomes2m
Building the Prototype: HPO (graphic)2m
References2m
Automated HPO Lab (Activity)30m
Summary2m
Summary/Review2m
3 practice exercises
Check for Understanding5m
Check for Understanding5m
End of Module Quiz5m
Week
4

Week 4

2 hours to complete

Evaluation and Deployment of AutoAI-generated Solutions

2 hours to complete
4 videos (Total 8 min), 9 readings, 4 quizzes
4 videos
Evaluation Demo3m
Deployment Demo2m
Course Closing1m
9 readings
Learning Outcomes2m
Evaluation Lab (Activity)10m
References2m
Summary2m
Learning Outcomes2m
Deployment Lab (Activity)15m
Summary2m
Summary/Review2m
More AutoAI Capabilities from IBM / References2m
3 practice exercises
Check for Understanding5m
Check for Understanding5m
End of Module Quiz5m

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