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B.Tech. Computer Science and Engineering (Artificial Intelligence and Machine Learning) ( B.Tech. )

Course Duration

8 Semesters
(4 Years)

Eligibility Criteria

Pass in PUC / 10+2 examination with Physics and Mathematics as compulsory subjects along with one of the subjects - Chemistry / Biotechnology / Biology / Computer Science / Electronics / Technical Vocational subjects and obtained at least 45% marks (40% in case of candidate belonging to SC/ST category) in the above subjects taken together, of any Board recognized by the respective State Governments / Central Government / Union Territories or any other qualification recognized as equivalent thereto.

FeeApplication Fee
  • Indian / SAARC Nationals₹ 1000
  • NRI Fee ₹ 2000
  • Foreign NationalsUS$ 50

Career Opportunities

Artificial Intelligence and Machine Learning professionals are among the most strategically valued individuals in the global workforce. Graduates of this programme at REVA University are positioned to lead, build, and govern the agentic AI systems, large language models, and autonomous intelligence pipelines that are reshaping every industry sector.

  • Generative AI Engineer (LLM / Diffusion Models)
  • Agentic AI Systems Developer
  • Large Language Model (LLM) Fine-Tuning Specialist
  • Retrieval-Augmented Generation (RAG) Engineer
  • Multimodal AI Engineer (Text + Vision + Audio)
  • AI Red Teaming and Safety Researcher
  • Foundation Model Trainer
  • Machine Learning Operations (MLOps) Engineer
  • Autonomous Vehicle Perception Engineer
  • AI-Powered Drug Discovery Researcher
  • Reinforcement Learning from Human Feedback (RLHF) Specialist
  • Neural Architecture Search (NAS) Researcher
  • Edge AI / TinyML Engineer
  • AI Chip and Hardware Optimisation Engineer
  • Humanoid Robotics AI Developer
  • AI Governance and Ethics Officer
  • Synthetic Data Generation Engineer
  • Federated Learning Engineer
  • AI-Powered Cybersecurity Analyst
  • Spatial AI / 3D Scene Understanding Engineer

Overview

The future of businesses depends on Artificial Intelligence and Machine Learning, and now is the right time to pursue a programme in the field that will fundamentally alter the trajectory of any business or technological venture. The B.Tech. programme in Artificial Intelligence and Machine Learning at REVA University is advanced, futuristic, and industry-resilient. This programme contains an extensive array of courses related to intelligent computation, including design and analysis of algorithms, computer programming languages, software design, and computer hardware. The specialisation trains students to develop smart, autonomous machines through a cutting-edge combination of AI and Data Science technologies. Core subjects include Artificial Intelligence, Machine Learning, Data Science and Statistics, Big Data Analytics, Computer Vision, Business Intelligence, Deep Learning and Reinforcement Learning, Robotics, Predictive Analytics, Swarm and Bio-inspired Intelligence, Robotic Process Automation, Genetic Algorithms, Fuzzy Logic and Systems, and Natural Language Processing. Graduates emerge as highly skilled professionals capable of building the intelligent systems and applications that will define the next generation of technology and business.

Course Curriculum

01Multivariable Calculus & Linear Algebra

02Engineering Chemistry

03Communication Skills

04Programming with C

05Elements of Mechanical Engineering

06IoT and Applications (Innovation)

07Design Thinking (Entrepreneurship)

08Programming with C Lab

09Engineering Workshop

01Probability & Statistics

02Physics for Computer Science

03Introduction to Accounting

04Introduction to Data Science

05Basics of Electrical & Electronics Engineering

06Elements of Civil Engineering & Mechanics

07Computer Aided Engineering Drawing

08Data Science Lab

09Basic Electrical & Electronics Engineering Lab

10Skill Development Course - I

01Discrete Mathematics & Graph Theory

02Professional Ethics

03Entrepreneurship

04Indian Constitution

05Programming with Python

06Data Structures using C

07Analog and Digital Electronics

08Computer Organization & Architecture

09Python Lab

10Data Structures Lab

11Analog & Digital Electronics Lab

01Numerical Methods and Optimization Techniques

02Human Values

03Technical Documentation/writing (Intellectual Property)

04Environmental Science

05Artificial Intelligence (Innovation)

06Design and Analysis of Algorithms

07Database Management Systems

08Programming with JAVA (Innovation)

09Design and Analysis of Algorithms Lab

10Database Management Systems Lab

11Programming with JAVA (Innovation)

12Skill Development course

01Open Elective 1 (General)

02Indian Heritage and Culture

03Machine Learning (Innovation)

04Computer Networks

05Web Technology (Entrepreneurship)

06Operating Systems

07Professional Elective I

08Professional Elective II

09Machine Learning Lab

10Computer Networks Lab

11Operating Systems Lab

12Skill Development Course

01Open Elective 2 (Multidisciplinary)

02Neural Networks and Deep Learning (Innovation)

03Cloud Computing

04Information and Network Security

05Professional Elective III

06Professional Elective IV

07Neural Networks and Deep Learning Lab

08Cloud Computing Lab

09Information and Network Security Lab

10Mini Project – Research Based (Innovation and Intellectual Property)

01Open Elective 3 - MOOC

02Open Elective 4

03Professional Elective V

04Skill Development course (MOOC)

05Internship

06Project – Phase I / Startup (Intellectual Property and Entrepreneurship)

01Project – Phase II / Startup (Intellectual Property and Entrepreneurship)

Programme Educational Objectives (PEOs)

After few years of graduation, the graduates of B.Tech. CSE (Artificial Intelligence & Machine Learning) will be able to:

PEO-1

Demonstrate technical skills, competency in AI & ML and exhibit team management capability with proper communication in a job environment.

PEO-2

Support the growth of economy of a country by starting enterprise with a lifelong learning attitude.

PEO-3

Carry out research in the advanced areas of AI & ML and address the basic needs of the society.

Programme Outcomes (POs)

On successful completion of the programme, the graduates of B.Tech. CSE (Artificial Intelligence & Machine Learning) programme will be able to:

PO 1

Apply the knowledge of mathematics, science, engineering fundamentals, and solve problems in the computer science and engineering specialization in Artificial Intelligence & Machine Learning.

PO 2

Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO 3

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.

PO 4

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.

PO 5

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.

PO 6

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.

PO 7

Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

PO 8

Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO 9

Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO 10

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.

PO 11

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.

PO 12

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

On successful completion of the programme, the graduates of B.Tech. CSE (Artificial Intelligence & Machine Learning) programme will be able to:

  • PSO-1 Demonstrate the knowledge of human cognition, Artificial Intelligence, Machine Learning and data engineering for designing intelligent systems.
  • PSO-2 Apply computational knowledge and project development skills to provide innovative solutions.
  • PSO-3 Use tools and techniques to solve problems in AI & ML.
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