B.Tech in Bioinformatics (Specialization in Artifical Intelligence)

01

To provide strong foundations in biological sciences, bioinformatics, computational methods, and artificial intelligence, enabling students to understand and analyze complex biological and biomedical systems.

02

To develop competencies in programming, data science, machine learning, deep learning, and AI-driven bioinformatics tools for analyzing large-scale biological datasets such as genomic, proteomic, and multi-omics data.

03

To equip students with the ability to design and implement computational models, algorithms, and intelligent systems for applications in healthcare, drug discovery, molecular diagnostics, and precision medicine.

04

To promote innovation, research orientation, and interdisciplinary problem-solving skills through project-based learning, internships, and exposure to emerging technologies in bioinformatics and artificial intelligence.

05

To nurture professional ethics, teamwork, leadership, and lifelong learning, preparing graduates to contribute responsibly to advancements in biotechnology, healthcare technologies, and data-driven life sciences.

01

Engineering and Biological Knowledge: Apply knowledge of mathematics, biological sciences, computing, engineering fundamentals, and bioinformatics to analyze and solve complex problems in life sciences, biotechnology, and healthcare systems. (WK1, WK2, WK3, WK4)

02

Problem Analysis: Identify, formulate, review research literature, and analyze complex bioinformatics and biomedical data problems by integrating biological knowledge with computational and AI based approaches. (WK1–WK4)

03

Design and Development of Solutions: Design, develop, and evaluate bioinformatics pipelines, databases, and AI-enabled computational systems for applications in genomics, drug discovery, diagnostics, and precision medicine while considering public health, sustainability, and real-world constraints. (WK4, WK5, WK6)

04

Investigation of Complex Problems: Conduct investigations using research methodologies, experimental design, computational modeling, statistical analysis, and machine learning techniques to generate evidence-based conclusions for biological and biomedical problems. (WK2, WK8)

05

Modern Tool Usage: Select, develop, and apply appropriate bioinformatics software, AI frameworks, databases, cloud platforms, and computational tools to analyze biological and healthcare datasets while understanding their capabilities and limitations. (WK3, WK6)

06

The Engineer and the World: Assess the societal, environmental, healthcare, and economic impacts of bioinformatics and AI technologies, addressing issues of data privacy, healthcare accessibility, regulatory compliance, and sustainable development. (WK1, WK5, WK7)

07

Ethics: Apply ethical principles and demonstrate professional responsibility, scientific integrity, data governance, and regulatory compliance in bioinformatics research and AI-enabled healthcare applications. (WK9)

08

Individual and Collaborative Teamwork: Function effectively as an individual, team member, or leader in multidisciplinary teams involving biologists, clinicians, data scientists, and engineers to achieve common research or technological goals.

09

Communication: Communicate effectively with scientific, industrial, and societal stakeholders through technical reports, research publications, software documentation, and professional presentations.

10

Project Management and Finance: Apply project management principles, entrepreneurship concepts, and techno-economic analysis to plan and manage bioinformatics and AI-driven projects in research organizations, biotechnology industries, and healthcare enterprises.

11

Life-Long Learning: Recognize the need for and engage in independent and lifelong learning, adapting to rapid advancements in bioinformatics, artificial intelligence, biotechnology, and healthcare technologies. (WK8)

01

Professional Practice: Build successful careers in bioinformatics, biomedical data science, artificial intelligence, healthcare technology, and allied interdisciplinary domains by applying integrated knowledge of biology, computation, and AI.

02

Higher Studies and Research: Pursue advanced education and research in bioinformatics, computational biology, biomedical AI, and related fields, contributing to scientific discovery and technological innovation.

03

Innovation and Problem Solving: Analyze complex biological and healthcare challenges and develop AI-enabled and data-driven computational solutions for applications in genomics, drug discovery, diagnostics, and precision medicine.

04

Professionalism and Lifelong Learning: Demonstrate ethical responsibility, teamwork, leadership, and adaptability, while engaging in continuous learning to address emerging technological and societal challenges.