Computer Science Engineering

B.Tech. in Computer Science & Engineering (Artificial Intelligence)
Why take this course?

B. Tech Computer Science and Technology with specialization in Artificial Intelligence (AI) has seen an exponential growth in the last few years. It is fueled by explosion in the use of Internet, extensive penetration of smart phones, increasing use of online services, social media, e-banking and increasing incidents on Human workload. Artificial Intelligence is a well-established exciting specialization of computer science concerned with methods to make computers or machines intelligent. So that they are able to learn from experience to derive implicit knowledge from the one given and to understand natural languages to determine the content of images to work collaboratively.

What will I experience?

Acquire knowledge of fundamental concepts, design strategies, advance technical architecture, progress infrastructural requirements, services, deployment model, tools and techniques.

Accelerate understanding through application-oriented and student-centric learning.

Augment curriculum with pragmatic approach through projects, knowledge exchange forums and sessions by professionals.

What opportunities might it lead to?

By 2020, insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers. Forrester Predictions 2017: Artificial Intelligence will drive the Insights Revolution. NASSCOM says by 2020, the artificial intelligence market will surpass $60 billion. Here are some of the roles an AI professional can look forward to in major organizations.

  • Data Engineer
  • Research Scientist
  • Natural Language Processing Scientist
  • Machine Learning developer
  • Automation and Optimization Engineer
  • Game developer

Pass in PUC / 10+2 examination with Physics and Mathematics as compulsory subjects along with Chemistry / Computer Science / Electronics as one of the subjects and obtained at least 60% marks (55% in case of SC/ST category) in the above subjects taken together.

Study Campus
JGI Global Campus
Faculty of Engineering & Technology
NH-209, Bangalore - Kanakapura Main Road
Jakkasandra Post, Kanakapura Taluk
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
  • Mathematical for Computer Science
  • Artificial Intelligence
  • Data Structures using C
  • Object Oriented Programming with JAVA
  • Digital Electronics
  • Data Structures using C Lab
  • Object Oriented Programming using JAVA Lab
  • Digital Electronics Lab
Mandatory Course
  • Energy Studies
  • Database Management Systems
  • Signal and Systems
  • Operating Systems
  • Business Communication and Presentation skills
  • Computer Organization and Architecture
  • Database Management System Lab
  • Signal and Systems Lab
  • Operating Systems Lab
  • Computer Networks
  • Design & Analysis of Algorithms
  • Logic Programming and Uncertainty in Artificial Intelligence
  • IT Workshop (Python)
  • Organizational Behavior
  • Elective – I
  • Knowledge Representation and Reasoning
  • Computer Human Interface
  • Embedded Systems
  • Computer Networks Lab
  • Design & Analysis of Algorithms Lab
  • Sensor Technologies
  • Elective-II
  • Fuzzy Logic and Application
  • Speech Processing
  • Data Mining
  • Elective-III
  • Natural Language Processing
  • Real Time Data Processing
  • Probabilistic Graphical Methods
  • Open Elective-I
  • Digital Image Processing
  • Computer Graphics
  • Data Visualization
  • Project-1
  • Sensor Technologies Lab
  • Elective - IV
  • Genetic Algorithm and Applications
  • Robotics
  • Graphical Models and Bayesian Networks
  • Elective-V
  • Machine Learning Algorithm
  • NoSQL Databases
  • Design and Analytics of Experiments
  • Open Elective-II
  • Deep Learning
  • Pattern Recognition
  • Advanced Big Data Analytics
  • Elective-IV Lab
  • Project Work-II
  • Open Elective-III
  • Reinforcement Learning
  • Recommender System
  • Time Series Analysis
  • Open Elective-IV
  • Application of AI and ML in Robotics
  • Expert System
  • AI Platforms
  • Internship/ Project work –III