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Computer Science Engineering


M.Tech. in Artificial Intelligence
Why take this course?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving. The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal. Masters in Artificial Intelligence course at JAIN (Deemed-to-be University) is designed as classroom-lab model. The hackathons, workshops, online course exposures enables the students to understand and learn better. The course gives hands on experience for the students making them ready to face the industry demands.

What will I experience?

Enables you to be with familiar with concepts, processes and technology in Artificial Intelligence.

Prepares you to implement the technology in various domains like real estate, marketing and sales, banking, healthcare, education and more.

Includes advanced level courses like data analysis, machine learning, language processing, computer vision etc.

What opportunities might it lead to?

There are numerous opportunities for candidates after completing M. Tech in Artificial Intelligence. It is a unique professional course adhering to the global demand for quality engineers in the stream of artificial intelligence. The candidates can work in different vertical in the software industry. Some of the employment areas for candidates after completing M. Tech in Artificial Intelligence are listed below:

  • AI Engineer
  • AI Research Scientist
  • Robotics Scientist
  • Game Programmer
  • AI Specialist
  • Data Mining Analyst
  • Software Engineer

Companies who are looking on AI (Artificial Intelligence) on related technology are Facebook, Google, Apple, Microsoft, IBM, Amazon, Spotify and many more.

Eligibility

B.E / B.Tech / AMIE in Computer Science Engineering/ Information Science/ Electronics and Communications/ Electrical and Electronics/ Medical Electronics/ Electronics and Telecommunication/ Electronics and Instrumentation / Instrumentation and Control Engineering.

The qualification required to apply for the program is a minimum of 50% marks (45% marks in case of candidate belonging to reserved category) in the respective bachelor’s degree from a recognized university.

Study Campus
Faculty of Engineering & Technology
45th km, NH - 209
Jakkasandra Post
Bangalore - Kanakapura Main Road
Ramanagara District - 562 112
Admissions Office
JGI Knowledge Campus
# 44/4, District Fund Road
Jayanagar 9th Block Campus
Bangalore - 5600 69
+91 80 4665 0130
Curriculum Structure & Teaching
  • Mathematical Foundations for AI
  • Machine Learning with Python
  • Image Processing and Computer Vision
  • Research Methodology
  • Program Specific Elective-I
    1. Fuzzy Logic and Applications
    2. Inferential Statistics and Data Analysis
    3. Embedded Systems
  • Program Specific Elective-II
    1. Genetic Algorithm and Application
    2. Probabilistic Graphical Model
    3. Sensor Technology
  • Machine Learning with Python LAB
  • Image Processing and Computer Vision Lab
  • Fundamentals of Innovation and venture development entrepreneurship 1
  • Big Data Management
  • Advanced Machine Learning
  • Bio-Inspired Computing
  • Program Specific Elective-III
    1. Artificial Neural Network and Deep Learning
    2. Data Analytics using SQL
    3. Digital Signal Processing
  • Program Specific Elective-IV
    1. Natural Language Processing
    2. Data Visualization with Tableau
    3. AI platforms
  • Program Specific Elective - V
    1. Reinforcement Learning
    2. Chat Bot Development
    3. Cloud Web services
  • Advanced Machine Learning Lab
  • Fundamentals of Innovation and venture development entrepreneurship 2
  • Open Elective - I
  • Open Elective - II
  • Open Elective - III
  • Project Centric Learning 3
  • Project Phase - I
  • Dissertation Project
  • Project Centric Learning 4