📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI in Healthcare, from foundations to a certified capstone project.
Outline
Explore the definition and significance of AI in healthcare. • Identify core AI techniques such as ML, NLP, and computer vision. • Discuss data privacy, bias, and ethical considerations.
Outline
Implement AI‑powered diagnostic models for medical imaging. • Build predictive analytics solutions for patient outcomes. • Utilize leading AI libraries and platforms (TensorFlow, Keras, PyTorch, IBM Watson Health, Google Health AI).
Outline
Apply AI to genomics for personalized medicine and drug discovery. • Develop a complete AI solution to predict patient readmission risk. • Explore emerging trends such as AI‑driven mental health, surgical robotics, and telemedicine.
Earn government-registered certification in AI in Healthcare
e-Certificate and e-Marksheet issued on successful completion.
