AI in Healthcare Certificate
Develop, implement and evaluate AI algorithms and technologies for improving health care delivery and management
The AI in Healthcare Certificate program emphasizes the use of artificial intelligence and data science concepts, techniques, and implementations for applications in both clinical and public health care settings.
Program Overview
This Certificate Program is specifically designed to quickly build up competencies in this exciting new field especially for those seeking a professional advancement, consultancy opportunities or topical knowledge for their research projects and grants.
The AI in Healthcare Certificate (AIHC) degree program is geared towards individuals who wish to enhance their current professional competencies and skills with adequate and hands-on knowledge of AI and Data science concepts and techniques for leadership, research, consultancy positions. Graduates of the program will be able to communicate and collaborate effectively on AI projects with health personnel, computer scientists, engineers, health researchers, policy makers, as well as patients and consumers alike.
This program will be offered as both completely on-campus and as a completely online program mode using state of the art learning technologies, course management systems and video conferencing sessions.
AI in Healthcare Certificate program will enable its graduates to:
- Leverage artificial intelligence concepts and techniques across several core areas, including information management, pharmaceutical and hospital processes and statistics, data analytics and clinical decision making.
- Develop, implement and evaluate AI algorithms and technologies for improving health care delivery and management
- Describe the structure, roles and capabilities of Artificial Intelligence in various biomedical and health care systems.
- Demonstrate competency by using theories and methods of AI and data science algorithms, and programming.
- Review current implementations of AI (including generative AI, machine learning) in diverse clinical areas.
- Apply good practice to ensure the design, implementation, and adoption of AI technologies and systems appropriately mitigating the risk of inadvertent harm to patients and organizations.
- Exhibit Professionalism in the coursework, class projects and interactions within and outside of the program.
- Design and implement a suitable organizational level AI program or intelligent decision making system for solving a health informatics problem.
- Evaluate and report on the performance of a suitable organizational level AI program or decision making system for solving a health informatics problem with clear explanations as to its logic, syntax and operations.
According to the Bureau of Labor Statistics (BLS) [4], employment for data scientists (including AI) is expected to grow by 35% from 2022 to 2032. They believe it stems from an increased demand for data-driven decisions and the need therefore for organizations, including healthcare, to hire more data scientists to mine and analyze the large amounts of information and data collected for making informed decisions and improve their business processes, to design and develop new products, and to better position themselves in the market for their products.
Indeed, the market watch site Statista [5] projected the global healthcare AI market to be around 188 billion U.S. dollars by 2030 and growing at a compound annual growth rate of 37% between 2022 and 2030. A Morgan Stanley Research [6] Survey echoes a similar note as to the demand and places of application of AI in healthcare in the US. Accordingly, healthcare professionals already with strong clinical and professional skills would need to pursue specialized certificate degrees like ours to gain specialized technology skills such as AI in this case and position themselves for top-level executive positions in hospitals, health centers, research institutions, and clinics.
Questions?
Please contact the Office of Admissions at 973-972-5454.
Admissions Criteria
Applicants will elect to choose either of those two modes in their applications for admission into the program. International Students intending to come to the United States on a F1 Student Visa will only be allowed to choose the on-campus mode.
Admissions Requirements
- Minimum GPA of 3.0 at least from an Undergraduate Degree program accredited in the US or its equivalent
- Students who have graduated from a foreign institution must submit a WES or ECE evaluation of their coursework and TOEFL scores along with an official transcript.
- A Personal Statement
- Curriculum Vitae/Resume
- Three Letters of Recommendation from applicant’s previous academic institution or workplace
Tuition & Fees
SHP Tuition and Fees
For Tuition and Fees, please see the Graduate Tuition and Fees.
(Scroll down to 2024-2025 Rutgers Health Tuition and Fee Rates and click on School of Health Professions)
Curriculum
Total Credits Required to Graduate: 18 credits
Full-Time Mode: Students must register for at least 3 courses (9 credits) each Fall and Spring from the following list of courses.
Part-Time Mode: Students must register for at least 2 courses (6 credits) each Fall and Spring from the following list of courses.
International Students: Students must register for at least 3 courses (9 credits) each Fall and Spring from the following list of courses. Of the three at least two should be on-campus while the third can be online.
| Course Number | Course Title |
|---|---|
| CORE – Choose any 3 for 9 Credits | |
| BINF5403 | Python Programming – 3 cr |
| BINF5325 | Clinical Decision Support Systems – 3 cr |
| BINF5040 | Biomedical Information Processing (R Programming) – 3 cr |
| BINF5020 | Data Science – 3cr |
| BINF5210 | Health Data Analytics with SAS – 3 cr |
| ELECTIVES – Choose any 3 for 9 Credits | |
| BINF7592 | Clinical Data Mining – 3 cr |
| BINF5125 | Machine Learning – 3 cr |
| BINF5030 | Visualization in Health Informatics (Tableau) – 3 cr |
| BINF5550 | Generative AI and Language Models |
| BINF5312 | Health Information Processing (NLP) – 3 cr |
| BINF5900 | Data Science Programming – 3 cr |
| BINF5060 | Linear Algebra for AI and Data Science |
| BINF5513 | Cybersecurity |
| BINF7510 | Clinical Decision Making & Decision Analysis – 3 cr |
Total Credits: 18
Core courses are designed to provide the very essential AI/Data Science programming skills and software that they would need to better understand and work with AI models and projects. The Core courses are designed to quickly build up good programming skills in Python/R/SAS and SPSS as also get a thorough understanding of clinical decision making and decision support systems.
Elective courses provide the necessary and appropriate depth in a specific aspect of Artificial Intelligence/Data Science such as Generative AI modeling, Machine Learning, Neural Networks and so on.
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