About this Course

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Flexible deadlines
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Shareable Certificate
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100% online
Start instantly and learn at your own schedule.
Course 2 of 3 in the
Intermediate Level

You’re comfortable with Python programming, statistics, and probability. The Deep Learning Specialization is recommended but not required.

Approx. 31 hours to complete
English

What you will learn

  • Walk through examples of prognostic tasks

  • Apply tree-based models to estimate patient survival rates

  • Navigate practical challenges in medicine like missing data  

Skills you will gain

Deep LearningMachine Learningtime-to-event modelingRandom Forestmodel tuning
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.
Course 2 of 3 in the
Intermediate Level

You’re comfortable with Python programming, statistics, and probability. The Deep Learning Specialization is recommended but not required.

Approx. 31 hours to complete
English

Offered by

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DeepLearning.AI

Syllabus - What you will learn from this course

Content RatingThumbs Up97%(2,605 ratings)Info
Week
1

Week 1

9 hours to complete

Linear prognostic models

9 hours to complete
11 videos (Total 28 min), 3 readings, 3 quizzes
Week
2

Week 2

7 hours to complete

Prognosis with Tree-based models

7 hours to complete
15 videos (Total 41 min)
Week
3

Week 3

6 hours to complete

Survival Models and Time

6 hours to complete
16 videos (Total 38 min)
Week
4

Week 4

8 hours to complete

Build a risk model using linear and tree-based models

8 hours to complete
24 videos (Total 69 min), 3 readings, 2 quizzes

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About the AI for Medicine Specialization

AI for Medicine

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