AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
This course is part of the AI for Medicine Specialization
Offered By


About this Course
You’re comfortable with Python programming, statistics, and probability. The Deep Learning Specialization is recommended but not required.
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 Learning
- Machine Learning
- time-to-event modeling
- Random Forest
- model tuning
You’re comfortable with Python programming, statistics, and probability. The Deep Learning Specialization is recommended but not required.
Offered by
Syllabus - What you will learn from this course
Linear Prognostic Models
Prognosis with Tree-based Models
Survival Models and Time
Build a Risk Model Using Linear and Tree-based Models
Reviews
- 5 stars78.54%
- 4 stars15.95%
- 3 stars3.30%
- 2 stars1.51%
- 1 star0.68%
TOP REVIEWS FROM AI FOR MEDICAL PROGNOSIS
This course was great and more challenging that I have expected. More focus on statistics and survival data which is important for prognosis. Course has a good flow and valuable content.
Excellent course that teaches you complex concepts in an easy to understand manner. The assignments are challenging, while at the same time teaching you advanced stuff!
Nicely and very thought fully organized course. This will definitely help me in apply my skills at my job. Thanks DeepLEarning.ai
the coding assignments were not that hard sadly, but the knowledge about techniques and methods and formulas to interpret the prognosis is very helpful
About the AI for Medicine Specialization

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