7 Best Artificial Intelligence Courses for Healthcare You Should Know

Artificial Intelligence plays an important role in Healthcare in various ways like brain tumor classification, medical image analysis, bioinformatics, etc. So if you are interested to learn AI for healthcare, I have collected 7 Artificial Intelligence Courses for Healthcare. I hope these courses will help you to learn Artificial Intelligence for healthcare.

Best Artificial Intelligence Courses for Healthcare in 2023

I have filtered these courses on the following criteria-

Criteria-

1. Rating of these Courses.
2. Coverage of Topics.
3. Engaging trainer and Interesting lectures.
4. Number of Students Benefitted.
5. Good Reviews from various aggregators and forums.

So, without further ado, let’s start finding the best Artificial Intelligence Courses for Healthcare–

1. AI for Healthcare– Udacity

Rating- 4.6/5Time to Complete- 4 months (if you spend 15 hours/week)Level- AdvancedProgramming Language-Python

This AI for Healthcare Nano-Degree Program is dedicated to AI for Healthcare. There are 4 courses and 4 projects in this Nanodegree program.

This Nanodegree is more practical in that means throughout this Nanodegree program, you will work on various hands-on projects.

This is an advanced-level program and not for beginners. To excel in this program, you must have previous intermediate knowledge in Python and Machine Learning.

You will understand U.S. healthcare data security and privacy best practices e.g. HIPAA, and HITECH. This program will also cover 2D medical imaging and 3D medical imaging.

Overall this course is best for advanced learners who want to dive deeper into AI in the healthcare domain. These are the project lists-

Project List-

1. Pneumonia Detection from Chest X-Rays
2. Hippocampus Volume Quantification for Alzheimer’s Progression
3. Patient Selection for Diabetes Drug Testing
4. Motion Compensated Pulse Rate Estimation

Pros-

• You will get a chance to work on real-world projects with Industry Experts.
• You will get Technical mentor support.
• Along with this, you will get career services.

Cons-

• Projects are not easy to complete. A lot of effort is required.
• The Nanodegree Program is expensive compared to other courses.

Who Should Enroll?

• Those who have Intermediate Python and Machine Learning knowledge.

Interested to Enroll?

If yes, then check here- AI for Healthcare

2. AI for Medicine Specialization– deeplearning.ai

Rating- 4.7/5Time to Complete- 3 months (If you spend 7 hours/week)Level- IntermediateProgramming Language-Python

This AI for Medicine Specialization Specialization Program is a brand new program dedicated to Healthcare. There are 3 courses in this program.

The concepts are explained by using real-life scenarios which helps students to understand the complex topics easily. This is also a practical based course.

In the first course, you will work on a practical exercise, “Disease Detection with Computer Vision“. In the second course, you will learn how to build a linear prognostic model using logistic regression.

There are various practical exercises are included in this program such as Measuring Treatment Effects, Segmentation on Medical mages, etc.

These are the 3 courses-

Courses List-

1. AI for Medical Diagnosis
2. AI for Medical Prognosis
3. AI For Medical Treatment

Pros-

• You will get a Shareable Certificate and Course Certificates upon completion.
• You will also get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Cons-

• The first course is a basic introduction course and doesn’t cover the concepts in detail.
• The instructor focused on coding rather than covering theoretical concepts.

Who Should Enroll?

• Those who can program in Python and are comfortable with statistics and probability.

Interested to Enroll?

If yes, then check here- AI for Medicine Specialization

3. AI in Healthcare Specialization– Stanford University

Rating- 4.8/5Time to Complete- 9 Months (If you spend 2 hours/week)Level- BeginnerProgramming Language-Python

This AI in Healthcare Specialization is another specialization program offered by Coursera. There are 5 courses in this specialization program. This program is suitable for beginners and begins with a basic introduction to health care and clinical data.

This program is the perfect balance between theory and practice. There are various practical exercises and videos for learning.

You will learn how to convert messy clinical data into a form where you can analyze something meaningful. The instructors also explain Machine Learning and Deep Learning algorithms and how you can use these algorithms in healthcare.

The last course is the Capstone project where you have to perform all the stages of Machine Learning starting from data collection to model deployment.

Overall this course is good for beginners who want to learn how they can use Artificial Intelligence in the healthcare domain.

These are the 5 courses-

Courses List-

1. Introduction to Healthcare
2. Introduction to Clinical Data
3. Fundamentals of Machine Learning for Healthcare
4. Evaluations of AI Applications in Healthcare
5. AI in Healthcare Capstone

Pros-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Good course to understand the healthcare industry.
• You will work on various practical exercises.
• The pace of teaching is perfect.
• Work on the case study of the current COVID data.

Cons-

• The first course was related to the healthcare industry and not related to AI that’s why AI learners might feel bored in this course.

Who Should Enroll?

• There is no prior experience required. Anyone interested in AI for healthcare can enroll.

Interested to Enroll?

If yes, then check here- AI in Healthcare Specialization

4. Statistical Analysis with R for Public Health Specialization– Imperial College London

Rating- 4.7/5Time to Complete- 4 Months (If you spend 3 hours/week)Level- BeginnerProgramming Language-R

This Statistical Analysis with R for Public Health Specialization program is mainly dedicated to the Statistical Analysis for Public Health. This program has 4 courses and uses R programming to teach Statistics basics.

In this program, you will learn statistics basics such as types of variables, joint distributions, sampling, etc. You will know the Parkinson’s Disease Study Issues.

After that, you will learn R Programming basics and RStudio. Linear Regression and Logistics Regression are also covered in this program.

Throughout this program, you will work on various practical exercises. This program is good for you if you want to work on hands-on practices.

These are 4 courses-

Courses List-

1. Introduction to Statistics & Data Analysis in Public Health
2. Linear Regression in R for Public Health
3. Logistic Regression in R for Public Health
4. Survival Analysis in R for Public Health

Pros-

• You will get a Shareable Certificate and Course Certificates upon completion.
• The instructors are good and explained the topics in a simple and easy-to-understand manner.
• You will also get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Cons-

• The instructor gives too many reading materials in course 1 rather than explaining the concepts in video tutorials.
• The last course covers only the basics of Survival Analysis.

Who Should Enroll?

• Anyone can enroll who has an interest in medicine and statistics. This is a Beginner Level program. No medical, statistical, or R knowledge is assumed.

Interested to Enroll?

If yes, then check out all details here-Statistical Analysis with R for Public Health Specialization

5. Fundamentals of Machine Learning for Healthcare– Stanford University

Rating- 4.9/5Time to Complete- 12 HoursLevel- BeginnerProgramming Language-Python

This Fundamentals of Machine Learning for Healthcare course is part of AI in Healthcare Specialization. The main objective of this course is to explain why Machine Learning plays an important role in healthcare.

Throughout this course, you will learn about Machine Learning and Deep Learning algorithms. This course claims that beginners can enroll in this course, but I thought some previous Machine Learning Knowledge is good to have.

You will learn Neural Networks, CNN, Natural Language Processing Recurrent Neural Networks, etc. Various practical exercises are there in the course.

Pros-

• You will get a Course Certificate upon completion.
• The course material is well-structured.
• You will also get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Cons-

• Without having some previous knowledge of Machine Learning, it’s quite hard to understand the concepts.

Who Should Enroll?

• This is a beginner-level course, so anyone can enroll who wants to know an overview of Machine learning in healthcare.

Interested to Enroll?

If yes, then check out all details here- Fundamentals of Machine Learning for Healthcare

6. AI for Medical Diagnosis– deeplearning.ai

Rating- 4.7/5Time to Complete- 19 HoursLevel- IntermediateProgramming Language-Python

This AI for Medical Diagnosis course is part of AI for Medicine Specialization. This is a short course to learn how to use Computer Vision and Convolutional Neural networks in Medical Image Diagnosis.

The instructor explains how CNN is used in Eye Disease and Cancer Diagnosis. And there is one practical exercise related to Disease Detection with Computer Vision.

The Confusion Matrix is also covered in this course. The Confusion Matrix is a way to find how many predicted categories or classes were correctly predicted and how many were not.

You will use MRI Images to perform Image Segmentation.

Pros-

• You will get a Course Certificate upon completion.
• You will understand these complex topics easily with the help of good visual representation.
• Andrew NG taught some topics.

Cons-

• The structure of this course is not up to the mark and it may confuse you.

Who Should Enroll?

• Those who have a working knowledge of deep neural networks, and are comfortable in Python programming.

Interested to Enroll?

If yes, then check out all details here-AI for Medical Diagnosis

7. Biostatistics in Public Health Specialization– Johns Hopkins University

Rating- 4.8/5Time to Complete- 4 months( If you spend 4 hours/week)Level- BeginnerProgramming Language-NA

This Biostatistics in Public Health Specialization is the perfect program to learn statistical concepts used in Public health. This program is math heavy program.

Throughout this program, you will learn various statistical concepts such as Samples Versus Population, Normal Distribution, Sampling Distribution, Confidence Intervals, Hypothesis Testing, etc.

Along with that, you will also learn Simple Linear Regression, Simple Logistic Regression, Simple Cox Regression, Multiple Logistic Regression, and Multiple Cox Regression.

There are 4 courses in this specialization program and various practical exercises to check your understanding. These are the 4 courses-

Courses Include-

1. Summary Statistics in Public Health
2. Hypothesis Testing in Public Health
3. Simple Regression Analysis in Public Health
4. Multiple Regression Analysis in Public Health

Pros-

1. You will earn a Shareable Certificate.
2. The pace of teaching is good and the instructor uses visual representation for teaching the concepts.
3. A good and well-structured course to learn Statistics.
4. You will also get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Cons-

• Some of the lecture videos are not clear.

Who Should Enroll?

• This program requires mathematical ability up through and including basic algebra, including logarithms and the equation of a line.

Interested to Enroll?

If yes, then check out all details here- Biostatistics in Public Health Specialization

And that’s all…So, these are the 7 Best Artificial Intelligence Courses for Healthcare in 2023.

Now, it’s time to wrap up.

Conclusion

I hope these listed courses will help you to learn Artificial Intelligence for Healthcare. I aim to provide you with the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.

Tell me in the comment section, which course you like.

All the Best!

Happy Learning!

NOTE- Some of the links in the post are Affiliate Links. This means if you click on the link and purchase the course, I will receive an affiliate commission at no extra cost to you😊.