About this Course

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Advanced Level
Approx. 19 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.
Advanced Level
Approx. 19 hours to complete
English

Offered by

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IBM

Syllabus - What you will learn from this course

Week
1

Week 1

6 hours to complete

Feedback loops and Monitoring

6 hours to complete
5 videos (Total 19 min), 16 readings, 4 quizzes
5 videos
Feedback Loops and Unit Tests7m
Performance Monitoring and Business Metrics1m
Performance Drift5m
Performance Monitoring Case Study1m
16 readings
Feedback loops and unit tests: Through the eyes of our Working Example3m
Feedback loops4m
Unit tests4m
Unit testing in Python3m
Test-Driven Development (TDD)3m
CI/CD3m
Performance Monitoring: Through the eyes of our Working Example3m
Logging3m
Minimal requirements for log files4m
Logging in Python (hands-on)30m
Model performance drift4m
Performance Drift Notebook Review25m
Security and Machine Learning Models10m
Performance Monitoring Case Study: Through the eyes of our Working Example4m
Getting started (hands-on)2h
Summary/Review6m
4 practice exercises
Check for Understanding30m
Check for Understanding30m
Check for Understanding30m
End of Module Quiz5m
Week
2

Week 2

4 hours to complete

Hands on with Openscale and Kubernetes

4 hours to complete
3 videos (Total 22 min), 6 readings, 3 quizzes
3 videos
Kubernetes Explained10m
Kubernetes vs. Docker: It's Not an Either/Or Question8m
6 readings
Watson OpenScale: Through the eyes of our Working Example4m
Getting started (hands-on)1h
Kubernetes Explained: Through the eyes of our Working Example4m
Introduction to Kubernetes4m
Getting started (hands-on)1h 30m
Summary/Review4m
3 practice exercises
Check for Understanding30m
Check for Understanding30m
End of Module Quiz5m
Week
3

Week 3

3 hours to complete

Capstone: Pulling it all together (Part 1)

3 hours to complete
10 readings
10 readings
Capstone: Through the eyes of our Working Example4m
What is in the Capstone and associated Review?4m
Review of Course 1: Business Priorities and Data Ingestion4m
Review of Course 2: Data Analysis and Hypothesis Testing5m
Review of Course 3: Feature Engineering and Bias Detection5m
Review of Course 4: Machine Learning, Visual Recognition, and NLP12m
Review of Course 5: Enterprise Model Deployment4m
About the data3m
Capstone Assignment 1: Through the eyes of our Working Example4m
Capstone Part 1: Getting Started (hands-on)2h
1 practice exercise
Capstone - Part 1 Quiz30m
Week
4

Week 4

6 hours to complete

Capstone: Pulling it all together (Part 2)

6 hours to complete
4 readings
4 readings
Capstone Assignment 2: Through the eyes of our Working Example4m
Capstone Part 2: Getting started (hands-on)2h
Capstone Part 3: Getting started (hands-on)2h
Solution Files1m
2 practice exercises
Capstone - Part 2 Quiz30m
Capstone - Part 3 Quiz30m

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