Computer-based solutions are getting smarter due to recent advances in machine learning, often called deep learning. This specialization is designed to enable students to build intelligent machines with a cutting-edge combination of machine learning, analytics and visualization technologies.
 

Program Outcomes

 
Program Outcomes

Acquire ability to explain and apply key ideas in artificial intelligence and machine learning and how they are being used in IBM, Google, Amazon, Facebook, etc.

 

Program Outcomes

Gain knowledge of related fields such as natural language processing, text mining, robotics, reasoning and problem solving

Program Outcomes

Acquire ability to design intelligent solutions to problems in a variety of domains and business applications

 
Program Outcomes

Attain insights required to compare and choose different methods for machine learning and intelligent reasoning

Program Outcomes

Gain hands-on experience in implementing scalable solutions with AI and machine leaning components, technologies and tools

 
Artificial Intelligence and Machine Learning
 

Course Content

 
Semester 1
Theory Practical
Mathematics I    
Physics Physics Lab
Programing in C Language Programing in C Language Lab
Playing with Big Data    
Open Source and Open Standards    
Communication WKSP 1.1 Communication WKSP 1.1 Lab
Seminal Events in Global History    
Semester 2
Theory Practical
Mathematics II    
Basic Electronics Engineering Basic Electronics Engineering Lab
Data Structures with C Data Structures-Lab
Discrete Mathematical Structures    
Introduction to IT and Cloud Infrastructure Landscape    
Communication WKSP 1.2 Communication WKSP 1.2 Lab
Environmental Studies    
Appreciating Art Fundamentals    
Semester 3
Theory Practical
Design and Analysis of Algorithms Design and Analysis of Algorithms Lab
Computer System Architecture    
Web Technologies Web Technologies Lab
Functional Programming in Python    
Introduction to Internet of Things    
Securing Digital Assets    
Communication WKSP 2.0 Communication WKSP 2.0 Lab
Introduction to Applied Psychcology    
Semester 4
Theory Practical
Data Communication and Computer Networks Data Communication and Computer Networks Lab
Operating Systems    
Introduction to Java and OOPS Introduction to Java and OOPS Labs
Database Management Systems & Data Modelling Database Management Systems & Data Modelling Lab
Applied Statistical Analysis (for AI and ML)    
Current Topics in AI and ML    
Impact of Media on Society    
Semester 5
Theory Practical
Formal Languages & Automata Theory    
Software Engineering &  Product management    
Mobile Application Development Mobile Development Lab
Algorithms for Intelligent Systems    
Current Topics in AI and ML    
Minor Subject 1: Finance for Modern Professionals    
Logical and Critical Thinking (Philosophy)    
Aspects of Modern English Literature or Introduction to Linguistics (Choose any one)    
    Minor Project I
Semester 6
Theory Practical
Introduction to Machine Learning Introduction to Machine Learning Lab
Reasoning, Problem Solving and Robotics    
Natural Language Processing    
Current Topics in AI and ML    
Minor Subject 2    
Minor Subject 3    
Design Thinking    
Communication WKSP 3.0 Communication WKSP 3.0 Lab
    Minor Project II
    Industrial Visit
Semester 7
Theory Practical
Business Process Management    
Data mining & Predictive Modeling    
Computer Vision and Image Processing    
Minor Subject 4    
Business Economics    
    Major Project I
    Summer Internship Report Presentation
Semester 8
Theory Practical
Soft Computing    
Current Applications of AI    
Minor Subject 5    
Professional Ethics    
    Major Project-2 Submission and Presentation
 

Career Opportunities

 
  • Machine Learning Engineer
  • Data Scientist - Machine Learning
  • Research Engineer - Artificial Intelligence
  • Big Data & AI Architect
  • Big Data and AI Consultant
  • Robotics Professional

Potential Recruiters

 
Google
amazon
 
facebook
PHILIPS
 

Admissions at a Glance

 
Approaching Deadline

Approaching Deadline

Session Starts August 2018!

Minimum Eligibility

Minimum Eligibility

B.Tech - Class XII – CBSE/State Board/ISCE 70%; IB 30 points

Application Fees

Application Fees

Rs. 1,500

key Links

key Links

Admissions

 
Sijo Kuruvilla George

"21st century skills are the ones that are valued at the workplace today. Great Lakes provides a good platform and an environment to develop those skills. Only a handful of schools in India provide you with an opportunity to have such diverse group of people with industry experience as your batch mates at Great Lakes."

- Sijo Kuruvilla George, PGPM Class of 2009

CEO, Startup Village

Please visit the Admissions page for further information.