About this Course

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Flexible deadlines
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Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Advanced Level

Working knowledge of ML & Python, familiarity with Jupyter notebook & stat, completion of the Deep Learning & AWS Cloud Technical Essentials courses

Approx. 11 hours to complete
English

What you will learn

  • Store and manage machine learning features using a feature store

  • Debug, profile, tune and evaluate models while tracking data lineage and model artifacts

Skills you will gain

ML Pipelines and MLOpsModel Training and Deployment with BERTModel Debugging and EvaluationFeature engineering and feature storeArtifact and lineage tracking
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Advanced Level

Working knowledge of ML & Python, familiarity with Jupyter notebook & stat, completion of the Deep Learning & AWS Cloud Technical Essentials courses

Approx. 11 hours to complete
English

Offered by

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DeepLearning.AI

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Amazon Web Services

Syllabus - What you will learn from this course

Week
1

Week 1

4 hours to complete

Week 1: Feature Engineering and Feature Store

4 hours to complete
11 videos (Total 40 min), 1 reading, 3 quizzes
Week
2

Week 2

3 hours to complete

Week 2: Train, Debug, and Profile a Machine Learning Model

3 hours to complete
8 videos (Total 38 min), 1 reading, 2 quizzes
Week
3

Week 3

4 hours to complete

Week 3: Deploy End-To-End Machine Learning pipelines

4 hours to complete
8 videos (Total 63 min), 3 readings, 2 quizzes

Reviews

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About the Practical Data Science Specialization

Practical Data Science

Frequently Asked Questions

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