About this Course

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Flexible deadlines
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Shareable Certificate
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Coursera Labs
Includes hands on learning projects.
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Advanced Level

• Some knowledge of AI / deep learning 

• Intermediate Python skills

• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)

Approx. 23 hours to complete
English

What you will learn

  • Apply techniques to manage modeling resources and best serve batch and real-time inference requests.

  • Use analytics to address model fairness, explainability issues, and mitigate bottlenecks.

Skills you will gain

  • Explainable AI
  • Fairness Indicators
  • automl
  • Model Performance Analysis
  • Precomputing Predictions
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.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs External Link
Advanced Level

• Some knowledge of AI / deep learning 

• Intermediate Python skills

• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)

Approx. 23 hours to complete
English

Offered by

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DeepLearning.AI

Syllabus - What you will learn from this course

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Week1
Week 1
6 hours to complete

Week 1: Neural Architecture Search

6 hours to complete
10 videos (Total 40 min), 4 readings, 6 quizzes
Week2
Week 2
4 hours to complete

Week 2: Model Resource Management Techniques

4 hours to complete
13 videos (Total 91 min), 6 readings, 3 quizzes
Week3
Week 3
5 hours to complete

Week 3: High-Performance Modeling

5 hours to complete
6 videos (Total 57 min), 4 readings, 4 quizzes
Week4
Week 4
4 hours to complete

Week 4: Model Analysis

4 hours to complete
12 videos (Total 69 min), 8 readings, 4 quizzes

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About the Machine Learning Engineering for Production (MLOps) Specialization

Machine Learning Engineering for Production (MLOps)

Frequently Asked Questions

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