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B.Tech. in Artificial Intelligence and Data Science(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.


The Department of Computer Science and Engineering at REVA UNIVERSITY proudly launches an innovative B. Tech in Artificial Intelligence and Data Science programme during the academic year 2021–2022. Due to the exploration of the Internet, AI and DS deliver data-driven solutions using computational principles, methods, and systems for extracting information from data and modern computational systems that reveal capabilities of insight, way of thinking, learning, and action that are typical of human intelligence. This course to create motivated, innovative, creative thinking graduates to fill ICT positions across sectors who can conceptualize, design, analyse, and develop ICT applications to meet modern-day requirements.

B. Tech in Artificial Intelligence & Data Science Programme prepares students with the skills to perform intelligent data analysis which is a key component in numerous real-world applications. During the past ten years, data science has emerged as one of the most high-growth, dynamic, and lucrative careers in technology. This course aims at providing not only the core technologies such as artificial intelligence, data mining, and data modelling but also gives intensive inputs in areas of machine learning and big data analytics. Through this course, the students will gain cross-disciplinary skills across fields such as statistics, computer science, machine learning, and logic, data scientists and may have career opportunities in healthcare, business, e-commerce, social networking companies, climatology, biotechnology, genetics, and other important areas. The major focus of this programme is to equip students with statistical, mathematical reasoning, machine learning, knowledge discovery, and visualization skills.

The course covers the core principles of Data Science, the process of ethically acquiring, engineering, analysing, visualizing, and ultimately monetizing data. It equips it with the basic tools and techniques of data handling, exploratory data analysis, data visualization, and data-based inference.

The course also introduces the fundamentals of Artificial Intelligence – state-space representation, search strategies, and learning algorithms. The course motivates students to work closely with data and make data-driven decisions in the field of study. The course also touches upon the ethical issues in Data Science and Artificial Intelligence and motivates students to explore the cutting-edge applications related to Big Data, Neural Networks, and Deep Learning. Applications like Alexa/Siri, Erica/Sophia, Tesla’s driverless car, Chatbot, etc. are becoming common. AI-powered Robots can take over human life-endangering jobs like firefighting, deep-sea oil drilling, mining works with high mortality rates, etc.

The B. Tech., in Artificial Intelligence and Data Science curriculum developed by the faculty at the Department of Computer Science and Engineering, is outcome-based and it comprises required theoretical concepts and practical skills in the domain. By undergoing this programme, students develop critical, innovative, creative thinking and problem-solving abilities for a smooth transition from academic to the real-life work environment. In addition, students are trained in interdisciplinary topics and attitudinal skills to enhance their scope. The above-mentioned features of the programme, advanced teaching, and learning resources, and the experience of the faculty members with their strong connections with the ICT sector make this programme unique.

Course Curriculum

01Multivariable Calculus and Linear Algebra

02Physics for Computer Science

03Introduction to Data Science

04Programmeming for Problem Solving

05Practical /Term Work / Practice Sessions/ MOOCs:

  • Entrepreneurship
  • IoT and Applications (Innovation)
  • Computer Aided Engineering Drawing

01Probability and Statistics

02Engineering Chemistry

03Introduction to Python Programmeming

04Basics of Electrical and Electronics Engineering

05Basics of Civil and Mechanical Engineering

06Practical /Term Work / Practice Sessions/ MOOCs:

  • Biology for Engineers
  • Design Thinking (Entrepreneurship)

01Analog and Digital Electronics.

02Programmeming with JAVA (Innovation)

03Data Structures

04Discrete Mathematics and Graph Theory

05Agile Software Development and Devops (Entrepreneurship)

06Practical /Term Work / Practice Sessions/ MOOCs:

  • Communication Skills
  • Indian Constitution and Professional Ethics
  • Universal Human Values

01Design and Analysis ofAlgorithms

02Unix Operating System

03Database Management System

04Computer Organization and Architecture

05Numerical Techniques and Optimization Methods

06Practical /Term Work / Practice Sessions/ MOOCs:

  • Management Science (Entrepreneurship)
  • Environmental Science
  • Basics of Kannada / Advanced Kannada

01Artificial Intelligence and Applications (Innovation and Entrepreneurship)

02Neural Networks and Deep Learning (Innovation and Entrepreneurship)

03Machine Learning (Innovation)

04Professional Elective-I

  • Web and Text Mining (Innovation and Entrepreneurship)
  • Pattern Recognition
  • Security in IoT
  • Advanced IoT Programmeming (Innovation and Entrepreneurship)
  • Object Oriented Concepts with C++/JAVA
  • UI/UX design And Data Visualization

05Open Elective-I

  • Database Management systems

06Practical /Term Work / Practice Sessions/Online/MOOC

  • Predictive Analytics and Data Visualization Tools
  • Indian Tradition and Culture

01Theory of Computation

02Big Data analytics (Innovation and Entrepreneurship)

03Iot and Cloud (Innovation and Entrepreneurship)

04Professional Elective - II

  • Cognitive Computing
  • Business Intelligence (Entrepreneurship)
  • Industrial and Medical IoT (Innovation and Entrepreneurship)
  • Cyber Physical Systems
  • Advanced Computer Architecture
  • Parallel Computing and High Performance Computing

05Open Elective-II

  • Data Structures

06Practical /Term Work / Practice Sessions/Online/MOOC

  • Research Based Mini Project (Innovation and Intellectual Property)
  • Mobile Application Development (Entrepreneurship)
  • Technical Documentation ( Intellectual Property)

01 Professional Elective-V

02 Open Elective-III

03Capstone-Project Phase-1 (Innovation and Intellectual Property)

04 Internship/Global Certification

01 Capstone-Project Phase-2 (Innovation and Intellectual Property)

02 Internship/Global Certification

03 MOOC / Competitive Exam

04 Open Elective-IV

Programme Educational Objectives (PEOs)

After few years of graduation, the graduates of B. Tech in Artificial Intelligence& Data Science will be able to:


Have a successful professional career in industry, government, academia and defence as an innovative engineer in a team.


Develop a code and solutions to industry and societal needs in a rapid changing technological environment and communicate with clients as an entrepreneur.


Pursue higher studies and continue to learn by participating in conferences, seminars, etc.

Programme Outcomes (POs)

On successful completion of the program, the graduates of B. Tech. (Computer Science and Engineering) program will be able to:

PO 1 Engineering knowledge:
Apply the knowledge of mathematics, science, engineering fundamentals for the solution of complex problems in Artificial Intelligence & Data Science.
PO 2 Problem analysis:
Identity, formulate, research literature, and analyze engineering problems to arrive at substantiated conclusions using first principles of mathematics, natural, and engineering sciences.
PO 3 Design/development of solutions:
Design solutions for complex engineering problems and design system components, processes to meet the specifications with consideration for public health and safety, and the cultural, societal, and environmental considerations.
PO 4 Conduct investigations of complex problems:
Use research-based knowledge including design of experiments, analysis, and interpretation of data, and synthesis of the information to provide valid conclusions.
PO 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 the limitations.
PO 6 The Engineer and society:
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 Environment and sustainability:
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 Ethics:
Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO 9 Individual and team work:
Function effectively as an individual, and as a member or leader in teams, and multidisciplinary settings.
PO 10 Communication:
Communicate effectively with the engineering community and with society at large. Be able to comprehend and write effective report documentation. Make effective presentations, and give and receive clear instructions.
PO 11 Project management and finance:
Demonstrate knowledge and understanding of engineering and management principles and apply these to one’s work, as a member and leader in a team. Manage projects in multidisciplinary environments.
PO 12 Life-long learning:
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 program, the graduates of B. Tech in Artificial Intelligence & Data Science program will be able to:

  • PSO-1 Understand, analyze and develop essential proficiency in the areas related to data science and artificial intelligence in terms of underlying statistical and computational principles and apply the knowledge to solve practical problems.
  • PSO-2 Ability to implement Artificial Intelligence and data science techniques such as search algorithms, neural networks, machine learning, and data analytics for solving a problem and designing novel algorithms for successful career and entrepreneurship.
  • PSO-3 Use modern tools and techniques in the area of Artificial Intelligence& Data Science.

Career Opportunities

  •  Machine Learning Engineers 
  • Data Scientist
  • DevOps Engineer 
  • Artificial Intelligence Engineer
  • Data Analyst
  • Machine Learning Architect
  • Software Engineer
  • Systems Engineer
  • System Analyst
  • Business/ Domain Analyst
  • Systems Administrator
  • Project Manager
  • Network Engineer
  • Government Departments 
  • Private Sectors
  • Railways
  • Defence 
  • R&D
  • Educational Institutions
  • Entrepreneurship
  • Indian / SAARC Nationals₹ 1000
  • NRI Fee₹ 2000
  • Foreign NationalsUS$ 50