B.Tech Computer Science in Association with IBM

Bachelor of Technology in Computer Science Engineering with a Specialization in Artificial Intelligence & Machine Learning

A Bachelor of Technology in Computer Science Engineering, specializing in Artificial Intelligence & Machine Learning, is one of the premier career choices of this decade. Technology is a constantly evolving field, characterized by continuous innovations and experiments.

Artificial Intelligence aims to simulate human intelligence and behavior, while Machine Learning, a subset of AI, enables computer systems to make predictions or decisions based on historical data without explicit programming.

Research indicates that about 30% of all B2B companies will employ AI to enhance at least one of their sales processes, highlighting the high job demand in this field. Graduates with a B.Tech in AI & ML can expect significantly higher returns compared to traditional engineering fields.

Course Features

• Comprehensive Learning: In-depth content on emerging technologies.
• Hands-on Approach: Strong emphasis on projects, labs, and case study-based learning.
• Industry Alignment: Focus on industry-aligned curriculum and continuous industry interaction.
• Collaborative Platform: The ‘Industry-Academia Collaboration Framework’ fosters learning, collaboration, and discovery.
• Competitive Edge: Opportunities for student participation in intra-college, inter-college, and global competitions.

Program Outcomes

1. Engineering Knowledge: Apply knowledge of mathematics, science, engineering fundamentals, and specialization to solve complex engineering problems.
2. Problem Analysis: Identify, formulate, review research literature, and analyze complex engineering problems to reach substantiated conclusions using principles of mathematics, natural sciences, and engineering sciences.
3. Solution Design/Development: Design solutions for complex engineering problems and system components or processes that meet specified needs, considering public health, safety, and cultural, societal, and environmental factors.
4. Research and Investigation: Use research-based knowledge and methods, including experimental design, data analysis, and information synthesis, to provide valid conclusions.
5. Modern Tool Usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modeling, to complex engineering activities with an understanding of their limitations.
6. Societal Impact: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues and responsibilities relevant to professional engineering practice.
7. Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate the knowledge of and need for sustainable development.
8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.
9. Teamwork: Function effectively as an individual and as a member or leader in diverse, multidisciplinary teams.
10. Communication: Communicate effectively on complex engineering activities with the engineering community and society, including writing reports, designing documentation, making presentations, and giving and receiving clear instructions.
11. Project Management and Finance: Demonstrate knowledge and understanding of engineering and management principles and apply them to manage projects in multidisciplinary environments.
12. Life-long Learning: Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broad context of technological change.