Close Search

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 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.

Good score in REVA University Common Entrance Test (REVA CET ) or CET / COMED-K / Uni-GAUGE or any other equivalent examination conducted by recognized Institute / Agency. (for lateral entry and for more details log on to University website


The B.Tech. in Artificial Intelligent and Data Science curriculum developed by the Faculty at the School of Computer Science and Engineering is outcome-based prepares students to perform intelligent data analysis which is a key component in real-world applications. In the last decade, Data Science has emerged as one of the high-growth, dynamic, and lucrative careers in the field of technology. This programme not only makes students adept at core technologies such as artificial intelligence, data mining, and data modeling but gives in-depth knowledge in Machine Learning and Big Data analytics. 

Students who enroll for this programme will gain cross-disciplinary skills across fields such as statistics, computer science, machine learning, and logic, data scientists, and the major focus of this programme is to equip students with statistical, mathematical reasoning, machine learning, knowledge discovery, and visualization skills.

The four-year programme covers core principles of Data Science, the process of ethically acquiring, engineering, analysing, visualising, and ultimately monetizing data. 

The programme 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.

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 Applications
  • 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

01Analog and Digital Electronics.

02Programmeming with JAVA

03Data Structures

04Discrete Mathematics and Graph Theory

05Agile Software Development and Devops

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
  • Environmental Science
  • Basics of Kannada / Advanced Kannada

01Artificial Intelligence and Applications

02Neural Networks and Deep Learning

03Machine Learning

04Professional Elective-I

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

05Open Elective-I

  • Database Management systems

6Practical /Term Work / Practice Sessions/Online/MOOC

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

01Theory of Computation

02Big Data analytics

03Iot and Cloud

04Professional Elective - II

  • Cognitive Computing
  • Business Intelligence
  • Industrial and Medical IoT
  • 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
  • Mobile Application Development
  • Technical Documentation

01Natural Language Processing

02Digital Image Processing and Computer Vision

03Professional Elective - III

  • Blockchain Technology
  • Embedded Systems Design
  • Advanced Web Technology

04Professional Elective - IV

  • Advanced Machine Learning
  • Communication Technologies For IoT
  • Cloud Computing and DevOps

05Professional Elective - V

  • Data Science Using R
  • Virtual and Augmented Reality
  • Cloud Security

06Open Elective-III

  • Java Programmeming

07Practical /Term Work / Practice Sessions/ MOOCs:

  • Capstone-Project Phase-1
  • Summer Internship/Global Certification

01Capstone-Project Phase-2

02Open Elective - IV:

  • R Programmeming Language

03Practical /Term Work / Practice Sessions/ MOOCs:

04Practical /Term Work / Practice Sessions/ MOOCs:

05Practical /Term Work / Practice Sessions/ MOOCs:

06Practical /Term Work / Practice Sessions/ MOOCs:

07Professional Elective-I

08Open Elective-I

09Practical /Term Work / Practice Sessions/Online/MOOC

10Professional Elective - II

11Open Elective-II

12Practical /Term Work / Practice Sessions/Online/MOOC

13Professional Elective - III

14Professional Elective - IV

15Professional Elective - V

16Open Elective-III

17Practical /Term Work / Practice Sessions/ MOOCs:

18Open Elective - IV:

Programme Educational Objectives (PEOs)

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


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


Develop code and solutions to industry in a rapidly changing technology 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 programme, the graduates of B.Tech. in Artificial Intelligence & Data Sciences programme will be able to:

PO 1

Apply the knowledge of mathematics, science, engineering fundamentals for the solution of complex problems in Artificial Intelligence& Data Sciences.

PO 2

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 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

Use research-based knowledge 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 teams, and multidisciplinary settings.

PO 10

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

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

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. in Artificial Intelligence & Data Sciences programme 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 Sciences.

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