In the past few years, healthcare has witnessed immense growth and advancement, especially after the artificial intelligence (AI) revolution. Recently, AI has expanded into different sectors, including healthcare, content creation, transportation, and more.
Almost all countries have poor and substandard healthcare systems, except for a handful. It needs to be reworked for better accessibility, affordability, and effectiveness. This is where AI comes into play. It can potentially revamp the healthcare industry by improving patient care, diagnosis accuracy, and operational efficiency.
AI is quickly becoming an integral part of the healthcare industry. Not only does it improve patient care, but it also helps healthcare professionals make more informed decisions. Its possibilities are endless, and as a result, many medical professionals are embracing AI and expanding their knowledge base.
Fortunately, there are several AI in healthcare courses available online that can help healthcare professionals learn how to effectively integrate AI into their practice. These courses cover a wide range of topics, from the basics of AI in healthcare to more advanced applications, making it easier for professionals to stay up-to-date with the latest technology trends in the industry.
In this article, we will take a look at some of the top AI in healthcare courses with certifications that you can take to enhance your medical career. Let’s begin.
List of AI in Healthcare Courses with Certifications in 2024
| Course Name | Provided by | Duration | Level | Key Topics | Course Link |
| AI in Healthcare Specialization | Stanford University | 1 month | Beginner | Artificial Intelligence, Clinical Data Analysis, Machine Learning, Applications Of Artificial Intelligence | AI in Healthcare Specialization |
| Artificial Intelligence in Health Care | MIT University | 6 weeks | Intermediate | AI technologies in health care, practical applications of AI in diagnosis, patient monitoring, hospital management, | Artificial Intelligence in Health Care |
| AI in Healthcare | Great Learning Academy | 20 hours | Beginner | Machine Learning, Introduction and Agenda of AI in Health Management, Artificial Intelligence, Deep Learning, Neural Networks | AI in Healthcare |
| Trustworthy AI for Healthcare Management | Goethe University Frankfurt | 3 hours | Beginner | AI in Healthcare, Trustworthy AI, Case Studies of AI in Healthcare | Trustworthy AI for Healthcare Management |
| AI for Healthcare | Udacity | 3 months | Advanced | Applying AI to 2D Medical Imaging Data, Applying AI to 3D Medical Imaging Data, Applying AI to EHR Data, Applying AI to Wearable Device Data | AI for Healthcare |
| The Complete Healthcare Artificial Intelligence Course 2024 | Udemy | 28 hours | Beginner | Deep Learning, Google Colab, Anaconda, Jupiter Notebook, Artificial intelligence in Healthcare, Artificial Neural Network. | The Complete Healthcare AI Course |
| Evaluations of AI Applications in Healthcare | Stanford University | 11 hours | Beginner | Principles and practical considerations for integrating AI into clinical workflows, best practices of AI applications to promote fair and equitable healthcare solutions, challenges of regulating AI applications | Evaluations of AI Applications in Healthcare |
AI in Healthcare Specialization
What We Like:
- Covers essential topics in both supervised and unsupervised learning, as well as practical applications.
- Led by experts in the field, providing valuable insights and real-world examples.
- Available online through Coursera, allowing for self-paced study.
- Accessible to beginners without requiring prior knowledge.
What We Don’t Like:
- While the course materials are free, obtaining a certificate requires a subscription.
- Primarily self-paced with limited direct interaction with instructors.
About the course: The course provides a complete introduction to machine learning basics. It covers different areas of study, from supervised learning methods like neural networks or decision trees to unsupervised methods such as clustering or dimensionality reduction. It aims to give students the hands-on abilities needed for applying machine learning in actual situations. Even with some downsides, such as certification expenses and a demanding workload, this is a very good resource for those who want to enter the area of machine learning.
COURSE DETAILS
| Provider | Stanford University |
| Duration | 1 month |
| Level | Beginner |
| Description | “In this specialization, we’ll discuss the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically.” |
| Key Topics | Artificial Intelligence, Clinical Data Analysis, Machine Learning, Applications Of Artificial Intelligence |
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Artificial Intelligence in Health Care
What We Like
- Provides a variety of learning formats including interactive videos and practice quizzes.
- Includes access to a Success Adviser for support.
- Explores practical applications of AI in health care with real-world case studies.
- Covers AI technologies like natural language processing, data analytics, and machine learning.
- Helps develop a framework to assess AI viability in healthcare contexts.
- Guided by MIT faculty and health care experts.
What We Don’t Like
- Requires a significant time commitment of 6-8 hours per week over six weeks.
- Limited interaction with peers and instructors due to self-paced nature.
- Quite expensive for a short course.
About the course: This course provides a thorough understanding of how AI is used in health care, with attention to real-world applications and challenges. Taught by the MIT faculty and healthcare experts, this course will guide you through the use of AI in diagnosis, patient monitoring, and care. It will also delve into how AI may be used to improve healthcare data management. You will also learn how to use an integrated approach to hospital management and optimization, and how to create a framework for evaluating the viability of integrating AI in your healthcare setting.
COURSE DETAILS
| Provider | MIT University |
| Duration | 6 weeks |
| Level | Intermediate |
| Description | “the MIT Sloan School of Management and the MIT J-Clinic aim to equip health care leaders with a grounded understanding of the potential for AI innovations in the health care industry.” |
| Key Topics | AI technologies in health care, practical applications of AI in diagnosis, patient monitoring, hospital management, data management and analytics, natural language processing |
| Correct URL Link to Course | https://www.getsmarter.com/products/mit-sloan-artificial-intelligence-in-health-care-online-short-course?focused=true |
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AI in Healthcare
What We Like
- Covers foundational topics in AI, machine learning, deep learning, and neural networks.
- Includes a practical demo on classification and regression.
- Features a hands-on project building a COVID classification model using X-ray images.
- Accessible to beginners.
What We Don’t Like
- Limited depth in advanced AI and healthcare topics.
- The course may lack interaction with instructors and peers.
- Requires payment to receive a completion certificate.
About the Course: This course by Great Learning Academy, provides a basic overview of how AI combines with healthcare. It includes subjects like machine learning, deep learning, and neural networks and has a practical hands-on project. Even though the course is good for beginners, it might not be detailed enough for advanced students who want a more thorough understanding of AI in healthcare.
COURSE DETAILS
| Provider | Great Learning Academy |
| Duration | 20 hours |
| Level | Beginner |
| Description | “In this free AI in healthcare course, We will be looking into some deep learning concepts like CNN, its various components, how CNN works, How AI is working parallelly with Healthcare, and Applications of AI.” |
| Key Topics | Machine Learning, Introduction and Agenda of AI in Health Management, Artificial Intelligence, Deep Learning, Neural Networks |
| Correct URL Link to Course | https://www.mygreatlearning.com/academy/learn-for-free/courses/ai-in-healthcare |
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Trustworthy AI for Healthcare Management
What We Like
- Focuses on trustworthy and ethical AI applications in healthcare.
- No prior AI knowledge is required, making it accessible to beginners.
- Includes real-world case studies for practical understanding.
- Developed by Goethe University Frankfurt as part of a European Commission research project.
What We Don’t Like
- Potential lack of interactive elements and peer engagement.
- Requires a payment in order to be accessed.
About the Course: This course provides a comprehensive introduction to AI in healthcare. It covers the basic principles of AI, proceeds to discuss moral rules, and finishes by teaching how to practically evaluate trustworthy AI using the Z-Inspection® process. Real-world case studies show how artificial intelligence can be used in healthcare, adding value and practicality to the content.
COURSE DETAILS
| Provider | Goethe University Frankfurt |
| Duration | 3 hours |
| Level | Beginner |
| Description | “It gives an introduction to trustworthy artificial intelligence and its application in healthcare. This includes modules on the basics of artificial intelligence and an introduction to trustworthy and ethical applications of artificial intelligence.” |
| Key Topics | AI in Healthcare, Trustworthy AI, Case Studies of AI in Healthcare |
AI for Healthcare
What We Like
- Focuses on both 2D and 3D medical imaging data.
- Includes real-world projects for practical experience.
- Teaches how to derive clinically relevant insights from medical imaging data using AI.
- Covers important topics such as feature engineering and medical regulations.
What We Don’t Like
- Requires prior knowledge in data cleaning, machine learning frameworks, and supervised machine learning
About the Course: The AI for Healthcare is a nano degree program made for knowledgeable learners wanting to use AI in medical imaging data. It includes two full courses: one that concentrates on 2D imaging data and another emphasizing 3D imaging data. This course will teach you important skills like feature engineering, medical regulations, and different types of imaging modalities. It offers hands-on projects such as teaching a CNN to sort chest X-rays and making an FDA approval plan.
COURSE DETAILS
| Provider | Udacity |
| Duration | 3 hours |
| Level | Beginner |
| Description | “The AI for Healthcare program offers two courses that apply AI to 2D and 3D medical imaging data.” |
| Key Topics | Applying AI to 2D Medical Imaging Data, Applying AI to 3D Medical Imaging Data, Applying AI to EHR Data, Applying AI to Wearable Device Data |
| Correct URL Link to Course | https://www.udacity.com/course/ai-for-healthcare-nanodegree–nd320 |
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The Complete Healthcare Artificial Intelligence Course 2024
What We Like
- Comprehensive coverage of AI, machine learning, and deep learning topics
- Includes practical exercises based on real-life healthcare problems
- No prerequisites are required, it is suitable for beginners with basic Python knowledge
- Lifetime access to course materials.
- Includes a wide range of tools and technologies such as Pandas, Matplotlib, Keras, and NLP.
- Offers a certificate of completion
What We Don’t Like
- The course is too broad, making it difficult for learners to focus on specific areas of interest.
- Requires payment in order to be accessed.
About the Course: The course gives a comprehensive introduction to AI, machine learning as well as deep learning with a special focus on applying them to real-life healthcare situations. The course has 28.5 hours of on-demand video, 2 articles, and 103 downloadable resources covering different topics such as activation functions, classifiers, data visualization, and handling missing data. You will get involved in practical projects such as predicting taxi fares, classifying DNA, and diagnosing coronary artery disease. The course is for beginners so you only need a basic understanding of Python.
COURSE DETAILS
| Provider | Udemy |
| Duration | 28 hours |
| Level | Beginner |
| Description | “A step-by-step guide into Machine Learning, Artificial Intelligence, and Deep Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.” |
| Key Topics | Deep Learning, Google Colab, Anaconda, Jupiter Notebook, Artificial intelligence in Healthcare, Artificial Neural Network. |
| Correct URL Link to Course | https://www.udemy.com/course/the-complete-healthcare-artificial-intelligence-course-2021/?couponCode=LETSLEARNNOWPP |
Evaluations of AI Applications in Healthcare
What We Like
- Comprehensive overview of AI applications in healthcare.
- Focus on ethical considerations and regulatory challenges.
- 22 quizzes to reinforce learning.
- No prior experience is required; beginner-friendly
What We Don’t Like
- The broad range of topics might require significant time commitment to fully grasp all concepts.
About the course: The course “Evaluations of AI Applications in Healthcare” is provided by Stanford Medicine’s AI in Healthcare Specialization. The class, led by Tina Hernandez-Boussard and Mildred Cho, introduces you to the principles and real-world factors related to incorporating AI into clinical workflows. It highlights the best ways to promote fair and equitable healthcare solutions. The course has 22 quizzes for gauging your understanding and provides a flexible schedule to learn at your own speed.
COURSE DETAILS
| Provider | Stanford University |
| Duration | 11 hours |
| Level | Beginner |
| Description | “This course explores the principles of AI deployment in healthcare and the framework used to evaluate downstream effects of AI healthcare solutions.” |
| Key Topics | Principles and practical considerations for integrating AI into clinical workflows, best practices of AI applications to promote fair and equitable healthcare solutions, challenges of regulating AI applications |
The Bottom Line
The courses we have listed above are some of the best in the field of AI in healthcare. These courses are available to learners of all levels, from beginners to advanced professionals, and provide a comprehensive understanding of how AI can be applied to healthcare data for improved outcomes. If you are looking to advance your career in the medical field, then give these courses a try.
Recommended reading:
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