Course Structure Overview
The B.Tech in Health Informatics at Iihmr University Jaipur is structured over eight semesters, with a balanced blend of core engineering subjects, science electives, departmental electives, and hands-on laboratory sessions. Each semester carries a specific credit load designed to ensure a progressive learning curve.
| Semester | Course Code | Full Course Title | Credit Structure (L-T-P-C) | Prerequisite |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming | 3-0-2-4 | - |
| 1 | MATH101 | Calculus and Linear Algebra | 3-0-2-4 | - |
| 1 | PHYS101 | Physics for Engineers | 3-0-2-4 | - |
| 1 | CHEM101 | Chemistry for Engineering | 3-0-2-4 | - |
| 1 | BIO101 | Introduction to Biology | 3-0-2-4 | - |
| 1 | ENGL101 | English Communication Skills | 2-0-0-2 | - |
| 2 | CS201 | Data Structures and Algorithms | 3-0-2-4 | CS101 |
| 2 | MATH201 | Probability and Statistics | 3-0-2-4 | MATH101 |
| 2 | PHYS201 | Electromagnetism and Waves | 3-0-2-4 | PHYS101 |
| 2 | BIO201 | Anatomy and Physiology | 3-0-2-4 | BIO101 |
| 2 | HIST101 | History of Medicine | 2-0-0-2 | - |
| 3 | CS301 | Database Systems | 3-0-2-4 | CS201 |
| 3 | MATH301 | Mathematical Modeling | 3-0-2-4 | MATH201 |
| 3 | BIO301 | Cellular Biology | 3-0-2-4 | BIO201 |
| 3 | HINF301 | Introduction to Health Informatics | 3-0-2-4 | - |
| 3 | ENGL201 | Technical Writing and Presentation | 2-0-0-2 | ENGL101 |
| 4 | CS401 | Machine Learning | 3-0-2-4 | CS301, MATH301 |
| 4 | BIOM401 | Bioinformatics Fundamentals | 3-0-2-4 | BIO301 |
| 4 | HINF401 | Health Data Analytics | 3-0-2-4 | HINF301 |
| 4 | ENGL301 | Professional Ethics in Healthcare | 2-0-0-2 | - |
| 5 | CS501 | Medical Image Processing | 3-0-2-4 | CS401, BIOM401 |
| 5 | HINF501 | Health Information Security | 3-0-2-4 | HINF401 |
| 5 | BIOM501 | Genomics and Proteomics | 3-0-2-4 | BIOM401 |
| 5 | RESE501 | Research Methodology | 3-0-2-4 | - |
| 6 | CS601 | Advanced AI for Healthcare | 3-0-2-4 | CS501, HINF501 |
| 6 | HINF601 | Telemedicine Systems | 3-0-2-4 | HINF501 |
| 6 | BIOM601 | Pharmacogenomics | 3-0-2-4 | BIOM501 |
| 6 | ENGL401 | Business Communication | 2-0-0-2 | ENGL201 |
| 7 | HINF701 | Capstone Project I | 3-0-2-4 | - |
| 7 | RESE701 | Advanced Research Topics | 3-0-2-4 | RESE501 |
| 8 | HINF801 | Capstone Project II | 3-0-2-4 | - |
| 8 | RESE801 | Final Thesis | 3-0-2-4 | RESE701 |
Advanced Departmental Electives
The department offers a rich selection of advanced elective courses designed to cater to various interests and career paths within health informatics.
- Medical Image Processing: This course explores techniques for analyzing, enhancing, and interpreting medical images using computational methods. Students learn about image segmentation, feature extraction, and deep learning models tailored for medical imaging tasks.
- Health Information Security: Focuses on safeguarding sensitive health data against unauthorized access, breaches, and cyber threats. Topics include encryption standards, risk assessment frameworks, and compliance with regulations like HIPAA and GDPR.
- Genomics and Proteomics: Delves into the analysis of genetic and protein structures to understand disease mechanisms and develop personalized treatment plans. Students gain hands-on experience with tools used in genomic data analysis.
- Telemedicine Systems: Examines the design and implementation of remote healthcare delivery systems, including mobile health apps, wearable sensors, and virtual consultation platforms.
- AI for Drug Discovery: Covers how artificial intelligence is revolutionizing pharmaceutical research by accelerating compound identification, predicting drug interactions, and optimizing clinical trial designs.
- Digital Therapeutics: Explores the development of software-based interventions that can treat medical conditions without traditional medications, focusing on behavior change, symptom monitoring, and adherence improvement.
- Public Health Data Analytics: Teaches students how to collect, analyze, and interpret large-scale public health datasets to inform policy decisions and track epidemiological trends.
- Healthcare Policy & Management: Provides insights into the economic, legal, and administrative aspects of healthcare systems, preparing students for leadership roles in health organizations.
- Biostatistics for Clinical Research: Offers advanced statistical methods applied to clinical trials and observational studies, emphasizing data interpretation and hypothesis testing in healthcare settings.
- Clinical Decision Support Systems: Introduces students to the design and evaluation of systems that assist clinicians in making informed decisions based on patient data and evidence-based guidelines.
Project-Based Learning Philosophy
Project-based learning is central to the program's philosophy, emphasizing experiential education and practical skill development. Mini-projects are introduced starting from the second year, allowing students to apply theoretical concepts in real-world scenarios.
Mini-projects typically last 6-8 weeks and involve small teams of 3-5 students working under faculty supervision. These projects are evaluated based on criteria such as innovation, technical feasibility, documentation quality, and presentation skills.
The final-year capstone project is a comprehensive endeavor that spans the entire semester. Students select their own research topics or propose innovative solutions to existing problems in healthcare delivery. They work closely with faculty mentors and industry advisors to refine their ideas and develop prototypes or models.
Each student selects their project based on their interests, career goals, and available resources. Faculty mentors are assigned according to expertise alignment, ensuring optimal guidance throughout the process. Projects are often submitted for publication or patent consideration, providing students with tangible achievements that enhance their professional profiles.