• Code20223
  • DeliveryFull-time
  • Length4 Years
  • CredentialBachelor of Technology - (Computer Science & Engineering) AI&ML in Association with IBM

Program Description

The course is designed to give the students enough exposure to the variety of applications that can be built using techniques covered under this program. They shall be able to apply AI/ML methods, techniques and tools to the applications. They shall be able to acquire the ability to design intelligent solutions for various business problems in a variety of domains and business applications. The students shall be exploring fields such as neural networks, natural language processing, deep learning, reasoning and problem-solving. The key objective is to identify logic and reasoning methods from a computational perspective, learn about agent, search, probabilistic models, perception and cognition, and machine learning.

Key Highlights and Common Features:

  • Co-Designed, Co-Delivered, and Co-Certified curriculum
  • Relevant Professional Certificate / Badges
  • “T” Skill sets / Dual Specialization
  • Industry interface right from the 1 st year
  • Job Ready/ Higher studies/ entrepreneurship
  • Project-based Lab exercises
  • 2 Minor and 2 Major Projects
  • Industry and Social Internships

PROGRAMME OUTCOMES

PO1: Engineering knowledge: To apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO2: Problem analysis: To identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO3: Design/development of solutions: To design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

PO4: Conduct investigations of complex problems: T use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PO5: Modern tool usage: To 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 the limitations.

PO6: The engineer and society: To apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

PO7: Environment and sustainability: To understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

PO8: Ethics: To apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO9: Individual and Team Work: To function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO10: Communication: To communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

PO11: Project Management and Finance: To demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO12: Life-long Learning: To recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

PROGRAMME SPECIFIC OUTCOMES

PSO1: To understand and apply the principles of systems which can perform airthmatic and logic using the concepts of computing System, logical modelling, software development and networks for communication.

PSO2: To apply the technological knowledge in the domain of Artificial Intelligence & Machine Learning, Data Science and Cyber Security for providing solutions to real life problems in the field of information technology, which meet the desired needs of industry and society.

PSO3: Graduates would expertise in successful careers based on their understanding of formal and practical methods.

Exit policy for students (* as per NEP) :

a.  After the completion of 1st Year - Certificate in Computer Application / Relevant Engineering
along with Industry Certificates

b.  After the completion of 2nd Year - Diploma in Software Engineering / Relevant Engineering
along with Industry Certificates

c.  After the completion of 3rd Year - Bachelor of Computer Application* / Advance Diploma in
Relevant Engineering* *“with specialization in XYZ”

Tuition Fee

Yearly

Semester

  • 1st Year ₹3,30,000
  • 2nd Year ₹2,80,000
  • 3rd Year ₹2,80,000
  • 4th Year ₹2,80,000
  • 1st Sem ₹1,90,000
  • 2nd Sem ₹1,40,000
  • 3rd Sem ₹1,40,000
  • 4th Sem ₹1,40,000
  • 5th Sem ₹1,40,000
  • 6th Sem ₹1,40,000
  • 7th Sem ₹1,40,000
  • 8th Sem ₹1,40,000

B.Tech. Computer Science and Engineering - (with Specialization in AI&ML) (in Association with IBM)
Admission Process

B.Tech. Computer Science and Engineering - (with Specialization in AI&ML) (in Association with IBM)
Admission Requirement

Passed the 10+2 examination with Physics and Mathematics as compulsory courses and any one course from Chemistry/ Computer Science/Electronics/Information Technology/ Biology/Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies/Entrepreneurship. Obtained at least 50% marks in the above 2 compulsories and any one selected (from list of 12) subjects taken together. OR Passed min. 3 years Engineering Diploma examination with at least 50% marks.

Our FacilitiesResearch & Laboratory Facilities

Computer Lab

Computer Lab

Computer Lab

Frequently Asked Questions

There are many benefits of pursuing a B.Tech. in Artificial Intelligence and Machine Learning. Some of them are listed as follows: 1. B.Tech. in Artificial Intelligence and Machine Learning prepares students for in- demand jobs in the tech industry. 2. Graduates possess knowledge of cutting-edge technology, algorithms, and programming languages. 3. AI and ML professionals are highly sought after and command high salaries. 4. Students gain valuable skills in data analysis, problem-solving, and critical thinking. 5. The field offers diverse opportunities for specialization and innovation, such as in robotics, natural language processing, and computer vision.

To enrol for the B.Tech. CSE specialization in AI&ML in association with IBM Admission, students must have passed the 10+2 examination with Physics and Mathematics as compulsory subjects and obtained an aggregate 50% marks in the compulsory subjects along with the selected technical subject taken together. Or to pursue B.Tech. in Artificial Intelligence and Machine Learning, students should have passed a minimum 3 years engineering diploma examination with at least 50% marks.

For B.Tech. in Artificial Intelligence and ML, some of our past placements have been in some of the most revered corporations including GKN Driveline Dyson Ltd. Swiss Military AAA Watches, Essar Projects India Ltd, JBM Group, Esctors Limited, and more.

Some of the skills required for pursuing a B.Tech. in Artificial Intelligence and Machine Learning are mathematics, computer programming, critical thinking, problem-solving, data analysis, and communication skills.

Graduates completing B.Tech. in Artificial Intelligence and ML have a wide range of job opportunities, such as data scientist, machine learning engineer, AI researcher, natural language processing expert, robotics engineer, and computer vision specialist.

Career Opportunities

  • Artificial Intelligence / Machine Learning Developer
  • Lead Artificial Intelligence / Machine Learning Engineer
  • Artificial Intelligence / Machine Learning Architect
  • Data Scientist
  • Research scientist
  • Data Analyst
  • Business Analyst
  • NLP Engineer
  • Business Intelligence Developer
  • Full Stack ML Developer
  • Product manager
  • Software Architect.

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