Computer Science Engineering

B.Tech (Honours) - Computer Science & Engineering (Data Science)
Why take this course?

The advent of the internet has expanded the digital technology landscape. Our every action online leave a footprint in the digital form. This has completely transformed the business world at a rapid speed. There is a massive explosion of data on daily basis, which is helping organizations to monitor the behavior of their customers. As a result, organizations are giving more prominence for extracting valuable insights from the information available and the responsibility is mainly handled by Computer Science professionals. It has generated an enormous scale of job opportunities for Computer Science professionals in the market. In order to meet this demand, JAIN (Deemed-to-be University) is offering B.Tech (Honours) - Computer Science & Engineering (Data Science), which helps students find better jobs in this sector.

What will I experience?

Learn a set of Computer Science principles, tools, and techniques to solve real-world business problems and also suggest a suitable solution with relevant findings.

Recognize various issues in everyday business; apply Computer Science for better understanding of data-driven management decisions to help organizations get an edge over competition.

Provide insight into leading analytic practices, design and lead iterative learning and development cycles. Knowledge on producing new and creative analytic solutions that will become part of any business core deliverables.

Knowledge on how to improve business results by building data fuelled products that help their customers.

What opportunities might it lead to?

According to NASSCOM, the big data analytics market will reach $16 billion by the year 2025 growing eightfold from its market worth in 2016. And India will require over 200,000 data scientists by 2018 as per various industry insights.

Some of the designations, which students can look forward to in organizations are:

  • Data Engineer
  • Citizen Data Scientist
  • Enterprise Data Analyst
  • Machine Learning Engineer
  • Computer Theory

Student must have passed 10+2 or equivalent examination with Physics, Mathematics and English as compulsory subjects along with Chemistry or Biotechnology or Biology or any technical vocational subjects as optional with a minimum of 60% marks (55% in case of SC/ST) taken together in Physics, Mathematics and any one of the optional subjects.

Study Campus
JGI Global Campus
Faculty of Engineering & Technology
45th km, NH - 209, Jakkasandra Post
Bangalore - Kanakapura Main Road
Ramanagara District - 562 112
+91 80 2757 7200
+91 7337618222
Admissions Office
JGI Knowledge Campus
# 44/4, District Fund Road
Jayanagar 9th Block Campus
Bangalore - 5600 69
+91 7337618222
Curriculum Structure & Teaching
Physics Cycle
  • Engineering Mathematics –I
  • Physics
  • Communicative English
  • Problem Solving Through Programming
  • Engineering Graphics
  • Physics Lab
  • Problem Solving Through Programming Lab
  • Communicative English Lab
Chemistry Cycle
  • Engineering Mathematics – II
  • Chemistry
  • Basics of Electrical Engineering
  • Workshop Practice
  • Sociology and Elements of Indian History for Engineers
  • Chemistry Lab
  • Electrical Engineering Lab
  • Mathematics for Computer Science
  • Economics for Engineers
  • Data Structures and Algorithms
  • Computer Organization and Architecture
  • Object Oriented Programming using Java
  • Digital Electronics
  • Introduction to Data Science
  • Data Structures and Algorithms Lab
  • Object Oriented Programming using Java Lab
  • Digital Electronics lab
Mandatory Course
  • Energy Studies
  • R Programming Language
  • Database Management Systems
  • Signals & Systems
  • Operating Systems Building Blocks
  • Business Communication and Presentation Skills
  • R Programming Language Lab
  • Database Management Systems Lab
  • Signals & Systems Lab
  • Operating Systems Building Blocks Lab
  • Computer Networks
  • Design & Analysis of Algorithms
  • Big Data Analytics
  • Python for Data Science
  • Machine Learning
  • Organizational Behavior
  • Elective – I
  • Data Mining Techniques
  • Multivariate Statistical Analysis
  • Sampling Methods
  • Computer Networks Lab
  • Design & Analysis of Algorithms Lab
  • Big Data Analytics Lab
  • Python for Data Science Lab
  • Machine Learning Lab
  • Advanced Statistical Methods
  • Advanced Machine Learning
  • Statistical Interface
  • Formal Language & Automata Theory
  • Elective - II
  • NoSQL Databases
  • Pattern Recognition
  • Design & Analysis of Experiments
  • Elective - III
  • Advanced Big Data Analytics
  • Recommender System
  • Time Series Analysis
  • Open Elective-I
  • Data Warehousing and ETL
  • Latest Trend in Data Science
  • Reinforcement Learning
  • Advanced Machine Learning Lab
  • Project-I
  • Dimensionality Reduction and Model Validation Techniques
  • Elective-IV
  • Real Time Data Processing
  • Natural Language Programming
  • Probabilistic Graphical Models
  • Elective-V
  • Big Data Analytics on Cloud
  • Artificial Neural Networks
  • Operations Research
  • Open Elective-II
  • Predictive Analytics
  • Data Analytics using SQL
  • Advanced Data mining Techniques
  • Artificial Neural Network
  • Dimensionality Reduction and Model Validation Techniques Lab
  • Project Work-II
  • Elective-VI
  • Data Visualization
  • Deep Learning
  • Exploratory Data Analysis
  • Open Elective-III
  • Advanced Optimization Techniques
  • Security and Privacy for Data Science
  • Simulation Techniques
  • Open Elective-IV
  • Artificial Intelligence
  • Internet of Things
  • Cloud Computing
  • Internship/Project work –III