B. Tech Artificial Intelligence Syllabus

B. Tech Artificial Intelligence Syllabus

The B. Tech Artificial Intelligence Syllabus emphasizes a thorough grasp of how to write effective, error-free code that allows a machine to carry out tasks with less assistance from a human. B. Tech AI and ML Syllabus comprises eight semesters, which includes projects, seminars, industrial training, practical and laboratory work, and core and elective studies.

The core B. Tech AI and ML Subjects are engineering mechanics, data structures and algorithms, artificial intelligence, big data analytics, machine learning, web technology, deep learning, and so on. Additional courses including Quantum AI, Software Architecture, Pattern Recognition, Human-Computer Interface, and Cognitive Computing are available to students pursuing B. Tech AI and ML courses.

Students can build a career as data scientists, data engineers, software designers, data interpreters, etc. with the help of the B. Tech Artificial Intelligence and Machine Learning course, which helps students acquire technical skills in the fields of artificial intelligence, algorithms, big data analytics, machine learning, etc.

What is Artificial Intelligence and Machine Learning?

The goal of the B. Tech in Artificial Intelligence and Machine Learning program (specialization in CSE) is to give students a hands-on grasp of a variety of AI and ML functions. Nearly every sector and field in the world is changing because of AI and ML. The need for important and wise decision-making across sectors is what's driving the exponential growth in the use of AI and ML technology. There is an unprecedented demand for AI and ML specialists with industries opening up to automation and other cutting-edge technologies. To understand what is artificial intelligence and machine learning and how a career in AI and ML is beneficial, students must pursue this course at top colleges. 

B. Tech Artificial Intelligence and Machine Learning Course Details

The bright future of AI holds tremendous prospects for B. Tech AI and ML graduates who can adapt and use creative solutions to shape the world. Prospective applicants can review the B. Tech Artificial Intelligence and Machine Learning course details by referring to the table below:

Level of Program

Undergraduate

Program Duration

4 Years

Eligibility Criteria

Applicants qualifying for their 10+2 exam from a recognized Board and Science stream (Physics and Mathematics compulsory subjects) are eligible

Admission Process

Merit-Based on 12th grade and Entrance-based Selection

Average B. Tech AI and ML Fees

INR 1,00,000/- to INR 1,50,000/- Annually

Average Starting Salary

Between 10 LPA and 15 LPA

Job Profiles

Data Engineer, Principle Data Scientist, Data Analyst, Data Scientist, Computer Vision Engineer, etc.

 

B.Tech AI and ML Syllabus

B. Tech in AI and Machine Learning syllabus includes many core and elective subjects. Elective courses are first offered to students in their third year of study.

Based on their professional aspirations, personal interests, and future educational objectives, B. Tech AI and ML students must select their elective courses. View the B. Tech AI and ML syllabus in detail below.

Semester 1

Semester 2

Physics

Basic Electronics Engineering

Physics Lab

Basic Electronics Engineering Lab

Mathematics I

Mathematics II

Playing with Big Data

Data Structures with C

Programming in C Language

Data Structures-Lab

Programming in C Language Lab

Discrete Mathematical Structures

Open Source and Open Standards

Introduction to IT and Cloud Infrastructure Landscape

Communication WKSP 1.1

Communication WKSP 1.2

Communication WKSP 1.1 Lab

Communication WKSP 1.2 Lab

Seminal Events in Global History

Environmental Studies

-

Appreciating Art Fundamentals

Semester 3

Semester 4

Computer System Architecture

Introduction to Java and OOPS

Design and Analysis of Algorithms

Operating Systems

Design and Analysis of Algorithms Lab

Data Communication and Computer Networks

Web Technologies

Data Communication and Computer Networks Lab

Web Technologies Lab

Introduction to Java and OOPS

Functional Programming in Python

Applied Statistical Analysis (for AI and ML)

Introduction to Internet of Things

Current Topics in AI and ML

Communication WKSP 2.0

Database Management Systems & Data Modelling

Communication WKSP 2.0 Lab

Database Management Systems & Data Modelling Lab

Securing Digital Assets

Impact of Media on Society

Introduction to Applied Psychology

-

Semester 5

Semester 6

Formal Languages & Automata Theory

Reasoning, Problem Solving and Robotics

Mobile Application Development

Introduction to Machine Learning

Mobile Application Development Lab

Natural Language Processing

Algorithms for Intelligent Systems

Minor Subject 2 – General Management

Current Topics in AI and ML

Minor Subject 3 - Finance for Modern Professiona

Software Engineering & Product Management

Design Thinking

Minor Subject: - 1. Aspects of Modern English Literature or Introduction to Linguistics

Communication WKSP 3.0

Minor Project I

Minor Project II

Semester 7

Semester 8

Program elective

Robotics and Intelligent Systems

Web Technologies

Major Projects 2

Major Project- 1

Program Elective-5

Comprehensive Examination

Program Elective-6

Professional Ethics and Values

Open Elective - 4

Industrial Internship

Universal Human Value & Ethics

Open Elective - 3

-

CTS-5 Campus to corporate

-

Introduction to Deep Learning

-

 

B. Tech AI and ML Subjects

Programming with C – Among B. Tech AI and ML subjects, programming in C will teach students how to write C programs by utilizing fundamental programming constructs and teaching them how to handle files and input/output in C. This covers subjects like pointers, arrays and structures, general problem-solving ideas, and the different kinds of operators and expressions in the C language.

Data Structures: Data Structures is one of the most detailed B. Tech AI and ML subjects. This covers the applications of different linear and nonlinear data structures using the principles of List ADT. Students will learn about sorting, searching, and hashing methods from this.

Python Functional Programming: Upon mastering B. Tech AI and ML subjects in Python, students will be able to read and write data to and from files, execute Python programs in both script and interactive modes, and implement Python programs with conditionals and loops.

Advanced Engineering Mathematics: This covers topics such as Formulation of Design Problems as Mathematical Programming Problems, Random Variables, Linear Programming, and Classical Optimization using Differential Calculus.

Technical Communication: This course covers technical writing, grammar and editing, comprehension of technical texts and materials, information design and development, advanced technical writing, and an introduction to technical communication.

Managerial Economics and Financial Accounting: Basic economic principles, production and cost analysis, market structure and pricing theory, financial statement analysis, etc. are some of the topics covered in managerial economics and financial accounting.

Concepts in Artificial Intelligence: Students will learn in-depth information on topics such as semantic networks, game-playing strategies, introduction to genetic algorithms, and the meaning and concept of artificial intelligence.

B. Tech AI and ML Syllabus in AKTU

Students who wish to pursue engineering at AKTU must review the B. Tech AI and ML syllabus in AKTU colleges to get an idea of what they are about to study. Check out the below table which includes all the core and elective B. Tech AI and ML subjects for a better understanding of the B. Tech AI and ML syllabus:   

Semester 1

Semester 2

Mathematics – I

Mathematics - II

Chemistry

Applied Physics

Basic Electrical Engineering

Programming for Problem Solving

Engineering Workshop

Engineering Graphics

English

Applied Physics Lab

Engineering Chemistry Lab

Programming for Problem-Solving Lab

English Language and Communication Skills Lab

Environmental Science

Basic Electrical Engineering Lab

-

Semester 3

Semester 4

Discrete Mathematics

Formal Language and Automata Theory

Data Structures

Software Engineering

Mathematical and Statistical Foundations

Operating Systems

Computer Organization and Architecture

Database Management Systems

Python Programming

Object Oriented Programming using Java

Business Economics & Financial Analysis

Operating Systems Lab

Data Structures Lab

Database Management Systems Lab

Python Programming Lab

Java Programming Lab

Gender Sensitization Lab

Constitution of India

Semester 5

Semester 6

Design and Analysis of Algorithms

Artificial Intelligence

Machine Learning

DevOps

Computer Networks

Natural Language Processing

Compiler Design

Professional Elective – III

Professional Elective - I

Artificial Intelligence and Natural Language Processing Lab

Professional Elective - II

DevOps Lab

Machine Learning Lab

Professional Elective - III Lab

Computer Networks Lab

Environmental Science

Advanced Communication Skills Lab

-

Intellectual Property Rights

-

Semester 7

Semester 8

Neural Networks & Deep Learning

Organizational Behaviour

Reinforcement Learning

Professional Elective - VI

Professional Elective - IV

Open Elective - III

Professional Elective - V

Project Stage - II

Open Elective - II

-

Deep Learning Lab

-

Industrial-Oriented Mini Project/ Summer Internship

-

Seminar

-

Project Stage

-

 

B. Tech AI and ML Courses Structure

Students must know about the B. Tech AI and ML course structure to get a strong understanding of the Foundations of Computational Mathematics, important computer science topics, and the most recent advancements in AI and ML. This will help students as they create solutions and applications for the world we live in. The B. Tech in AI and ML course structure is as follows:

  • 8 semesters
  • Project work
  • Internship
  • Experiments
  • Core Subjects
  • Elective Subjects

 

Diploma in Artificial Intelligence Syllabus

A diploma in Artificial Intelligence syllabus includes mathematics such as statistics, linear algebra, etc., core machine learning concepts such as supervised and unsupervised learning, data visualization tools and techniques, etc. You will have the chance to become an expert in one of computer science's most exciting and rapidly expanding fields by taking this course. Through the Diploma in Artificial Intelligence syllabus, students will be able to progress in their careers during the period of rapidly expanding AI-ML applications.

Semester I

Semester II

Mathematics Essential

Data Science Applications of NLP

Introduction to Artificial Intelligence

Deep Learning

Machine Learning

Robotics & AI

Programming in Python

Game Theory & Artificial Intelligence

Computer Graphics and Animation

Distributed Systems & Cloud Computing

Programming in Python – Lab

Robotics & AI – Lab

Computer Graphics and Animation – Lab

Distributed Systems & Cloud Computing – Lab

-

Project Work

 

B. Tech AI and ML Syllabus: Teaching Methods

During the first few semesters of their B. Tech AI and ML syllabus, students are taught Mathematics and Physics in a modular fashion. The curriculum then concentrates on subjects that are essential to artificial intelligence. This will help advance research abilities and innovative project development in the domains of AI, ML, DL, networking, security, web development, and data science, which is beneficial to society. The course's overall teaching methods consist of the following:

  • Case Studies
  • Experiments
  • Real-time Projects
  • Internships
  • Practical Sessions

 

B. Tech AI and ML Syllabus: Experiments

These practical experiments will help students write programs that handle real-world problems using OOP techniques and the Java Collection Framework. This will enhance the capacity to develop useful and modern applications, such as Web applications, discrete event simulations, and TCP/IP network programming.

  • Write a program utilizing tree traversal techniques.
  • Write a Java application that sorts a list of names alphabetically using the Quick Sort algorithm;
  • Create a program that uses the graph traversal techniques.
  • Create a Java program to do the subsequent tasks: Make an element list that is doubly linked. Remove a specific element from the list above.
  • Create a Python program that demonstrates using dictionaries.
  • Use C programming to demonstrate the aforementioned IPC techniques.
  • Pipes
  • FIFOs
  • Message Queues
  • Shared Memory
  • Create a Python program to demonstrate working with dictionaries

 

B. Tech AI and ML Books

We have put up a list of the top B. Tech AI and ML books to assist you in navigating this complex field of study. These publications provide insights into the future of these fascinating subjects and cover a wide range of topics, from basic concepts to sophisticated techniques.

Books

Author

Discrete Mathematics and its Applications with Combinatorics and Graph Theory

Kenneth H Rosen, 7th Edition, TMH.

Discrete Mathematics

Richard Johnsonbaugh, 7ThEdn., Pearson Education.

Fundamentals of Data Structures in C

E. Horowitz, S. Sahni and Susan Anderson Freed, Universities Press

Computer System Architecture

M. Moris Mano, Third Edition, Pearson/PHI.

Core Python Programming

Wesley J. Chun, Second Edition, Pearson.

Software Engineering, A Practitioner’s Approach

Roger S. Pressman, 6th edition, Mc Graw Hill International Edition

Advanced programming in the UNIX environment,

W.R. Stevens, Pearson education.

Database System Concepts

Silberschatz, Korth, Mc Graw hill, V edition.

Advanced programming in the Unix environment,

W. R. Stevens, Pearson education.

 

Also read : 

Engineering colleges in Greater Noida

Engineering Colleges in Delhi with low fees

Artificial Intelligence in Btech

Best Engineering Colleges in Uttar Pradesh

 

B. Tech Artificial Intelligence Syllabus FAQs

Q1. Which companies hire the most students in artificial intelligence?

Top hiring firms for professionals with degrees in artificial intelligence include Google, TCS, Capgemini, Samsung, Amazon, and so forth.

 

Q2. Is studying AI and ML for a B. Tech in computer science a good idea?

The field of artificial intelligence and machine learning is expanding due to technological advancements and innovation. Shortly, there will be more work opportunities. It is what we urgently need.

 

Q3. What is the B. Tech artificial intelligence syllabus for first-year?

The B. Tech artificial intelligence syllabus for the first year is:

  • Mathematics for Intelligent Systems – I
  • Computational Engineering Mechanics- I
  • Object Oriented programming
  • Elements of Computing System-I
  • Introduction to Electrical Engineering
  • Introduction to Digital Manufacturing
  • Introduction to Drones

 

Q4. Do courses in artificial intelligence have a growing career potential?

Yes, the field of artificial intelligence has grown significantly during the past few decades. By working in roles like artificial intelligence researcher, computer scientist, data scientist, AI gadget developer, etc., candidates can undoubtedly have a bright future in artificial intelligence.

 

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