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Artificial Intelligence in Healthcare Fundamentals and Applications
Online
8 Weeks
2,650 USD Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Virtual Classroom | Video and Text Based |
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | MIT Cambridge |
The fees for the course is :
| Fees components | Amount |
| Original fees | US$2,650 |
| Discounted fees | US$2,438 |
The Syllabus
- Discover the four stages of designing an AI product. Learn how to identify the desired AI behavior, assess business and technical requirements, measure value, and generate a software development plan. In addition, understand how to identify the long-term advantages of a product and analyze the three types of AI cancer and their impact.
- Explore machine learning, and its various algorithms, classifiers, decision trees (along with the advantages of training), and validation and testing sets. Analyze how to easily identify the best algorithms for different applications.
- Examine deep learning, neural networks, and their applications in drug discovery and cancer research. Learn to run implementations on convolutions and deep and recurrent neural network algorithms while gaining an understanding of Python and artificial neurons.
- Acquire a 360º approach to designing AI solutions with an understanding of superhuman targets, software methodologies, tool development, research, ethical responsibilities, and possible challenges to these applications. Learn about the Committee on the Use of Humans as Experimental Subjects (COUHES) and Institutional Review Board (IRB) approval processes, formulate crowdsourcing data strategies, and understand the extraordinary intelligence used in AI products and services.
- Gain a thorough understanding of how the Peloton framework helped facilitate applications, including modern ingestible robots. Develop your own ideas for ingestible robots to help solve healthcare problems.
- Deep dive into advanced prosthetics, proprioception, and exoskeletons. Understand their history, research, development, and current limitations, and learn how communication is crucial for the development of some of them.
- Identify the immediate challenges and possibilities in the field of healthcare technologies, including business applications, maintenance challenges, various sources of inspiration, the potentials of electromagnetic waves, and the use of radio frequency identification (RFID) chips. In addition, design and develop an AI product for healthcare.
- Explore how transformer-based models like ChatGPT work, including tokenization, attention, and output generation. Explore real-world applications and limitations of generative AI through case studies, including healthcare scenarios. Identify common AI challenges, including hallucinations and verbosity, learn strategies like retrieval augmentation and personalization to improve model performance, and examine emerging tools, such as BloombergGPT and DALL·E, to understand the future potential and risks of generative AI across industries.
Instructors
Articles
8 Sep'25, 12:53 PM
7 Aug'25, 10:34 AM
7 Jul'25, 07:34 AM
12 Jun'25, 11:58 AM
24 Apr'25, 10:09 AM
27 Feb'25, 06:16 AM
9 Jan'25, 11:23 AM
9 Jan'25, 11:23 AM
8 Sep'25, 12:53 PM
7 Aug'25, 10:34 AM
7 Jul'25, 07:34 AM
12 Jun'25, 11:58 AM
24 Apr'25, 10:09 AM
27 Feb'25, 06:16 AM
9 Jan'25, 11:23 AM