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PULAT 2020

School of Engineering

Computer Engineering [Artificial Intelligence and Machine Learning]

Program Overview

B. Tech in Computer Science and Technology (Spl. in AI and ML) is an undergraduate programme with advanced learning solutions imparting knowledge of advanced innovations like machine learning, often called deep learning and artificial intelligence.

This specialisation is designed to enable students to build intelligent machines, software, or applications with a cutting-edge combination of machine learning, analytics and visualisation technologies.
The main goal of artificial intelligence (AI) and machine learning is to program computers to use example data or experience to solve a given problem.

This programme discusses AI methods based in different fields, including neural networks, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions.

B. Tech in Computer Science and Technology (Spl. in AI and ML) is an undergraduate programme in the cutting-edge technologies of AI & ML. The programme provides advance inputs like deep learning, computer vision, expert systems and neural networks. This specialisation is designed to build expertise in intelligent machines, natural language processing and applications in cyber physical systems.

This programme cover AI methodologies based in different fields, including Algorithms for intelligent system, natural language parsing, knowledge engineering and predictive analytics control in order to present a unified treatment of machine learning problems and solutions.

Why AI and ML?

AI and ML is a hot topic in the tech industry. Perhaps more than our daily lives Artificial Intelligence (AI) is impacting the business world more.

There was about $300 million in venture capital invested in AI startups in 2014, a 300% increase than a year before (Bloomberg).

AI is everywhere, from gaming stations to maintaining complex information at work. Computer Engineers and Scientists are working hard to impart intelligent behavior in the machines making them think and respond to real-time situations.

Tech giants like Google and Facebook have placed huge bets on AI and ML and are already using it in their products.

But this is just the beginning, over the next few years, we may see AI steadily glide into one product after another.

Features

1. COLLABORATION:
Designed in collaboration with Xebia with curriculum designed by PU Faculty along with Xebia Industry Experts.​

2. PROJECT WORK:
(i) Students do two minor projects in 3rd year in Algorithm implementation through C , C++ and Java as coding mechanism with prime moto of understanding the core areas of Computer Science and Engineering.
(ii) Major Projects in 7th and 8th Semester purely on AI and ML specific projects which enables the students to understand natural language processing, vision, computational Intelligence, Robotics and social networks analysis.

3. SKILLS:
Imparting Skills in students through-
(i) Personality Development Program
C, C++, Core JAVA, .Net, Python, Note JS, Angular JS, LISP , Prolog , Data Analytics tools

4. WORKSHOPS:
Extensive and in-depth workshops relevant to Deep Learning, Machine Learning, Statistical tools and Business Intelligence Tools.

Advantages

CONCEPTUAL KNOWLEDGE:
(i) Thorough understanding of the concepts of AI and ML.

(ii) Deep knowledge in the field of data analytics and data science.​

2. DEMAND:
(i) The students are highly sort after as they are market ready. ​

(ii) High acceptability and quick deployment in the core sector.​

3. WORKSHOPS:
Help blend the content into the curriculum.

Benefits

1. HIGH MARKET ACCEPTANCE

2. HIGHER STUDIES:
Students are also highly accepted by foreign Universities for Higher Education. ​

3. HIGH DEMAND:
(i) For professionals in this domain for Software Developer, Consultancy, Business Analysist, Data Scientist, AI developer etc.

(ii) Demand for AI & ML skills among Automation industry players.

ELIGIBILITY CRITERIA for B.Tech

Pre-University / Higher Secondary /10+2 examination Pass with Physics and Mathematics as compulsory subjects along with either Chemistry / Biotechnology / Biology / Technical Vocational subject

Obtained at least 45% marks (40% in case of candidates belonging to Reserved Category) in the above subjects taken together

Appeared for JEE (Main); JEE (Advanced); Karnataka CET; COMED-K; PUEET-2020 or any other State-level Engineering Entrance Examination.

Program Structure* 'subject to changes by the Academic Council'

SEMESTER I                                                               SEMESTER II     
Subject Credits Subject Credits
Mathematics I 3 Mathematics II 3
Physics 3 Basic Electronics Engineering 3
Programming in C Language 3 Data Structures with C 3
Overview of Big Data 2 Discrete Mathematical Structures 3
Urban Sociology 2 Introduction to Psychology 2
Web Technologies 3 Spoken Technical English 2
Written Technical English 3 Environmental Studies 2
 PRACTICAL    PRACTICAL  
Physics Lab 1 Basic Electronics Engineering Lab 1
Programming in C Language Lab 1 Data Structures-Lab 1
TOTAL 21 TOTAL 20
SEMESTER III   SEMESTER IV     
Subject Credits Subject Credits
Design and Analysis of Algorithms 3 Data Communication and Computer Networks 3
Mathematics III 3 Operating Systems 3
Computer System Architecture 3 Introduction to Java and OOPS 2
Functional Programming in Python 3 Database Management Systems & Data Modelling 3
Introduction to IT and Cloud Infrastructure Landscape 3 Applied Statistical Analysis (for AI and ML) 2
Emerging Trends in AI & ML  1 2 Introduction to Internet of Things 3
Introduction to Machine Learning 3 Emerging Trends in AI & ML  2 2
Technical Report writing 2 Appreciating Art Fundamentals 2
Placement Related Communication 1
 PRACTICAL    PRACTICAL  
Design and Analysis of Algorithms Lab 1 Data Communication and Computer Networks Lab 1
Web Technologies Lab 1 Introduction to Java and OOPS Labs 1
Database Management Systems & Data Modelling Lab 1
Operating Systems Lab 1
TOTAL 24 TOTAL 25
SEMESTER V   SEMESTER VI  
Subject Credits Subject Credits
Formal Languages & Automata Theory 3 Machine Learning Classification 2
Software Engineering & Product management 3 Natural Language Processing 3
Algorithms for Intelligent Systems 3 Sensor Technology & Instrumentation 3
Emerging Trends in AI & ML  3 1 Probabilistic Graphical Models 3
Reasoning and Problem Solving 3 Emerging Trends in AI & ML  4 1
Knowledge Engineering 3 Design Thinking 2
Effective Communication 2 Machine Learning Clustering 2
Being Corporate Ready 1
 PRACTICAL    PRACTICAL  
Software Engineering & Project Management Lab 1 Minor Project 2 4
Minor Project 1 4 Machine Learning Lab 1
TOTAL 23 TOTAL 22
SEMESTER VII   SEMESTER VIII  
Subject Credits Subject Credits
Expert Systems 3 Current Applications of AI 4
Deep Neural Networks 4 Professional Ethics 2
Data mining & Predictive Modelling 3 Leadership in a Dynamic Business Environment 2
Computer Vision and Image Processing 4 Entrepreneurship and Product Development 2
Fuzzy Logic and Neural Networks 4
Placement Boot Camp 1
 PRACTICAL    PRACTICAL  
Major Project I 4 Major Project 2 6
TOTAL 23 TOTAL 16

*The above program structure is indicative in nature. The academic council of Presidency University reserves the rights to change, modify, or alter the curriculum structure and courses as per contemporary demand of the industry.

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