Artificial Intelligence (AI) technology integration in cancer could increase diagnostic accuracy, time, improve clinical decision-making, and result in improved patient outcomes. AI-guided clinical treatment has the ability to make a significant contribution to the reduction of health inequalities, especially in low-resource settings.
This Specialization will equip you with the knowledge of the cellular and molecular basis of cancer and AI and/or machine learning in medicine. To stay competitive in the field of cancer research, universities and organizations need qualified cancer experts with knowledge and understanding of AI and machine learning who use cutting-edge AI methods for detecting patterns in huge amounts of data, extracting associations between complex data features, and finding characteristics in data (including images) that the human brain cannot perceive.
This 16-week Specialization is designed to equip you with the knowledge you need to use AI and machine learning in cancer research. It will train you to perform research in an international research environment.
Through the virtual internship programme, you’ll gain the essential knowledge and skills required to participate in AI and cancer and immunology research. This Specialization aims to provide knowledge of cancer biology and advances in AI.
The online distance-learning delivery of the course will provide opportunities to receive expertise from the Cambridge Centre for Innovation and Development (CamCID) researchers, material from our partners, and guest lectures. This specialization includes two Professional Certificates (PCerts), 4 -week Researchers Training Programme, and a virtual internship.
This 4-week PCert course will provide you the knowledge of the cellular and molecular basis of cancer. It will provide you with the skills to participate in cancer research projects.
Further details are mentioned on PCert - Cancer Biology and Immunology Research page.
This 4-week PCert course is designed to equip you with the knowledge you need to apply AI in medicine. You will learn about the history of AI and the components of machine learning.
Further details are mentioned on PCert - AI in Medicine page.
This unique 4-week online training programme is designed to equip you with the knowledge you need to succeed in your career as a researcher in Biomedical Science.
This 4 weeks virtual training will provide you a learning opportunity from researchers at CamCID. It will provide you opportunities to gain research skills with weekly research-based tasks. You will participate in research activities (tasks and analysis) remotely and apply your knowledge of AI in medicine and cancer research.
UK and International: £379 (including electronic certificate and internship).
Reduced fee option:
If you have already completed any of our online PCert courses included in this specialization, fill this form to get a reduced fee payment link. £79 is reduced from the overall cost of the specialization for every PCert you have completed before (copy of your PCert(s) will be required).
This specialization starts with a beginner level and progresses towards the mid and advanced level. However, no prior programming experience is required.
This specialization is designed for all levels of students (Undergraduate students, Master's degree students, or Ph.D.). It is suitable for people with a background in either biology, biochemistry, biomedical science, bioscience, medicine, computer science, or similar areas.
All our online courses are taught in English. You must have good English language skills.
This specialization is designed to aid professional development in the field of AI in cancer biology, immunology, enabling you to further your expertise within an existing career path or to change career direction, for example, into a cancer researcher with expertise in AI.
After successfully completing all 4 parts of this Specialization, you will be provided with an e-certificate of completion and a virtual internship at Cambridge Centre for Innovation and Development (CamCID).
CamCID Research Team and Guest Lecturers (faculty members from multiple universities).
May include additional material by our partners
Start Date: 30 Aug 2022
Places available: 03
Duration and Delivery: 16 weeks (Online)
Workload: 5-6 hours per week
Entry requirements: For all levels of students (Undergraduate students, Master's degree students, or Ph.D.). Basic knowledge of biology, medicine, biochemistry, or other relevant areas is recommended.
Fees: £379 (UK and International)
Registration: Register Now