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
16,590 already enrolled
Offered By
AI for Medicine SpecializationDeepLearning.AIAbout this Course
13,431 recent views
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 3 of 3 in the
Intermediate Level
We recommend first completing Course 1 and 2 of the AI For Medicine Specialization.
Approx. 23 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
What you will learn
Estimate treatment effects using data from randomized control trials
Explore methods to interpret diagnostic and prognostic models
Apply natural language processing to extract information from unstructured medical data
Skills you will gain
- treatment effect estimation
- machine learning interpretation
- Random Forest
- natural language entity extraction
- question-answering
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 3 of 3 in the
Intermediate Level
We recommend first completing Course 1 and 2 of the AI For Medicine Specialization.
Approx. 23 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Offered by
DeepLearning.AI
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Syllabus - What you will learn from this course
9 hours to complete
Treatment Effect Estimation
In this week, you will learn: How to analyze data from a randomized control trial, interpreting multivariate models, evaluating treatment effect models, and interpreting ML models for treatment effect estimation.
9 hours to complete
12 videos (Total 43 min), 2 readings, 3 quizzes
7 hours to complete
Medical Question Answering
In this week, you will learn how to extract disease labels from clinical reports, and also question answering with BERT.
7 hours to complete
10 videos (Total 32 min)
7 hours to complete
ML Interpretation
In this week, you will learn how to interpret deep learning models, and also feature importance in machine learning.
7 hours to complete
9 videos (Total 29 min), 3 readings, 2 quizzes
Reviews
TOP REVIEWS FROM AI FOR MEDICAL TREATMENT
by KNDec 7, 2020
The assignment for the first week was out of scope for the course in my opinion. It was too much focused on a good handling of pandas which is rather difficult for people who are not experts in pandas
by AAJun 23, 2020
A bit tough, but well laid and well explained.Overall the entire specialization was very good. However it misses in depth theory . But overall a very good course with practical applications
by RBJun 12, 2020
A very nice course and specialization as well. Offers so much to learn even for those who are pure machine learners.Instructors were fantastic.Assignments were challenging but excellent.
by ASJun 7, 2020
Fantastic coursework teaching fundamentals required for analysis of medical domain data. Quality content with great assignments. Level of difficulty is intermediate for the assignments.
About the AI for Medicine Specialization
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 three-course Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.
