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BioMed Certification Programs

AI and Computational Drug Discovery (Training Workshop)

British Pharmacological Society

This novel online training workshop will explore how artificial intelligence (AI) is driving change within drug discovery. We will explore both predictive and generative machine learning approaches. This training course is set to an introductory level for a scientific audience and focuses on the application rather than the coding. Breakout activities will allow you to understand and apply your knowledge using real-life examples from within industry.

AI in Medicine Certificate

University of Illinois Urbana-Champaign

Artificial intelligence (AI) is poised to make a significant impact throughout healthcare systems. The AI in Medicine certificate program offered by the University of Illinois Urbana-Champaign will equip healthcare professionals with a foundational understanding of AI and its applications through real-world medical case studies using machine learning models. This course will help prepare physicians, physician assistants, medical students, nurse practitioners and veterinarians to lead in the era of digital medicine.

Artificial Intelligence and Data Science for Healthcare Innovation

Imperial College London

In the healthcare industry, data science and artificial intelligence (AI) play a pivotal role in bringing together innovation and patient care and they have the potential to transform how healthcare is delivered.

Artificial Intelligence in Healthcare


Artificial intelligence (AI) has transformed industries around the world, and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system -- such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.

Business Applications for AI in Health Care Certificate of Specialization

Harvard Chan School Executive

The Harvard Chan School Executive and Continuing Professional Education Business Applications for AI in Health Care Certificate of Specialization program is for all health care stakeholders, from the doctor’s office to the business suite. Those who will benefit from this certificate include CEOs, CIOs, Chief Medical Informatics Officers, Chief Medical Officers, Clinicians, Data Scientists, Engineers, Finance Professionals, Product and Project Managers, and Venture Capital Investors.

Drug Discovery

University of California San Diego

The University of California San Diego, Skaggs School of Pharmacy and Pharmaceutical Sciences Drug Discovery course brings you lectures from both faculty and industry experts. With this course, recorded on campus at UCSD, we seek to share our access to top people in the field who bring an unprecedented range of expertise on drug discovery.

AI for drug discovery

Queen Mary University of London

Researchers have been assembled with diverse backgrounds in bioinformatics, natural language processing, computer vision, computational chemistry, cell biology, molecular pharmacology, and related specialities.

AI in Medicine for Medical Trainees

Johns Hopkins School of Medicine

Increasingly, the decisions physicians make about how best to treat their patients will be informed by the results of computational analyses of patient data. This increasing reliance on methods of artificial intelligence to guide patient care will not only transform medicine, but will also transform the ways in which physicians are trained. Future physicians will need to understand core principles of data science and be able to apply them to critically evaluate the emerging literature on AI in medicine and to do research in this emerging field.

Artificial Intelligence in Health Care Certificate Program

The Michener Institute

Due to the current technological revolution, more people expect new technologies to replace older ones to make processes more efficient and to reduce errors. Artificial Intelligence’s (AI) primary aim in a health-related environment is to provide clinical decision and diagnostic support by analyzing relationships between treatment options and patient outcomes. AI has also been developed for patient monitoring and care, drug development and disease prevention. This online certificate program will introduce students to the discipline of AI and how it is applied in the healthcare environment. Students will acquire data science and analytic skills, learn how to implement AI solutions and participate in creating an AI solution.

Artificial Intelligence in Healthcare Certificate

Michigan Techonological University

The healthcare industry will produce 2.3 trillion gigabytes of nonstructured data in 2020 alone by some estimates, a figure that increases 48% each year. This flood of data, along with a pressing need to address industry inefficiencies, poises the healthcare industry for a quantum leap in digital Innovation. This exploding Health Informatics sector needs professionals of many kinds to support, implement, assess, teach, and research AI healthcare solutions. The field is young and opportunities are plentiful and well-compensated. New software solutions and cutting-edge research are being developed and implemented now to overcome these challenges, and there is ample room and immediate need for novel ideas and innovation.

Certificate in Biomedical Data Science Program Description

UT Health Science Center San Antonio

The Certificate in Biomedical Data Science (CBDS) program is designed to provide specialized education where students will gain experience to speed the development of Biomedical Data Science strategies, to refine education programs for future leaders in the field of Biomedical Data Science (BDS), and to translate BDS research findings into public health messages.

Fundamentals of AI in (Bio)pharma


The use of Artificial Intelligence (AI) in the pharmaceutical industry is increasing at a rapid pace and will inevitably continue to spread as expertise and understanding also grow. Combining big data with machine learning, AI could have a dramatic impact on costly and lengthy drug development processes such as clinical trials, manufacturing and personalised medicines. Where do you begin when trying to understand this new technology? What does a successful AI strategy look like and how do you begin organising your data so you can draw meaningful conclusions?
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