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:
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Level of Program
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Undergraduate
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Program Duration
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4 Years
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Eligibility Criteria
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Applicants qualifying for their 10+2 exam from a recognized Board and Science stream (Physics and Mathematics compulsory subjects) are eligible
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Admission Process
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Merit-Based on 12th grade and Entrance-based Selection
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Average B. Tech AI and ML Fees
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INR 1,00,000/- to INR 1,50,000/- Annually
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Average Starting Salary
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Between 10 LPA and 15 LPA
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Job Profiles
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Data Engineer, Principle Data Scientist, Data Analyst, Data Scientist, Computer Vision Engineer, etc.
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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.
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Semester 1
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Semester 2
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Physics
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Basic Electronics Engineering
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Physics Lab
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Basic Electronics Engineering Lab
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Mathematics I
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Mathematics II
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Playing with Big Data
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Data Structures with C
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Programming in C Language
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Data Structures-Lab
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Programming in C Language Lab
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Discrete Mathematical Structures
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Open Source and Open Standards
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Introduction to IT and Cloud Infrastructure Landscape
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Communication WKSP 1.1
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Communication WKSP 1.2
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Communication WKSP 1.1 Lab
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Communication WKSP 1.2 Lab
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Seminal Events in Global History
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Environmental Studies
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-
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Appreciating Art Fundamentals
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Semester 3
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Semester 4
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Computer System Architecture
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Introduction to Java and OOPS
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Design and Analysis of Algorithms
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Operating Systems
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Design and Analysis of Algorithms Lab
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Data Communication and Computer Networks
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Web Technologies
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Data Communication and Computer Networks Lab
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Web Technologies Lab
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Introduction to Java and OOPS
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Functional Programming in Python
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Applied Statistical Analysis (for AI and ML)
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Introduction to Internet of Things
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Current Topics in AI and ML
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Communication WKSP 2.0
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Database Management Systems & Data Modelling
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Communication WKSP 2.0 Lab
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Database Management Systems & Data Modelling Lab
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Securing Digital Assets
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Impact of Media on Society
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Introduction to Applied Psychology
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-
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Semester 5
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Semester 6
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Formal Languages & Automata Theory
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Reasoning, Problem Solving and Robotics
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Mobile Application Development
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Introduction to Machine Learning
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Mobile Application Development Lab
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Natural Language Processing
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Algorithms for Intelligent Systems
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Minor Subject 2 – General Management
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Current Topics in AI and ML
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Minor Subject 3 - Finance for Modern Professiona
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Software Engineering & Product Management
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Design Thinking
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Minor Subject: - 1. Aspects of Modern English Literature or Introduction to Linguistics
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Communication WKSP 3.0
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Minor Project I
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Minor Project II
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Semester 7
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Semester 8
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Program elective
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Robotics and Intelligent Systems
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Web Technologies
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Major Projects 2
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Major Project- 1
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Program Elective-5
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Comprehensive Examination
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Program Elective-6
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Professional Ethics and Values
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Open Elective - 4
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Industrial Internship
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Universal Human Value & Ethics
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Open Elective - 3
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-
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CTS-5 Campus to corporate
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Introduction to Deep Learning
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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:
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Semester 1
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Semester 2
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Mathematics – I
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Mathematics - II
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Chemistry
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Applied Physics
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Basic Electrical Engineering
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Programming for Problem Solving
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Engineering Workshop
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Engineering Graphics
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English
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Applied Physics Lab
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Engineering Chemistry Lab
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Programming for Problem-Solving Lab
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English Language and Communication Skills Lab
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Environmental Science
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Basic Electrical Engineering Lab
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-
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Semester 3
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Semester 4
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Discrete Mathematics
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Formal Language and Automata Theory
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Data Structures
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Software Engineering
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Mathematical and Statistical Foundations
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Operating Systems
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Computer Organization and Architecture
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Database Management Systems
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Python Programming
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Object Oriented Programming using Java
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Business Economics & Financial Analysis
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Operating Systems Lab
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Data Structures Lab
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Database Management Systems Lab
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Python Programming Lab
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Java Programming Lab
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Gender Sensitization Lab
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Constitution of India
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Semester 5
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Semester 6
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Design and Analysis of Algorithms
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Artificial Intelligence
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Machine Learning
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DevOps
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Computer Networks
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Natural Language Processing
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Compiler Design
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Professional Elective – III
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Professional Elective - I
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Artificial Intelligence and Natural Language Processing Lab
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Professional Elective - II
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DevOps Lab
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Machine Learning Lab
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Professional Elective - III Lab
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Computer Networks Lab
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Environmental Science
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Advanced Communication Skills Lab
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Intellectual Property Rights
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Semester 7
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Semester 8
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Neural Networks & Deep Learning
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Organizational Behaviour
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Reinforcement Learning
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Professional Elective - VI
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Professional Elective - IV
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Open Elective - III
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Professional Elective - V
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Project Stage - II
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Open Elective - II
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Deep Learning Lab
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Industrial-Oriented Mini Project/ Summer Internship
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Seminar
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Project Stage
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-
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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:
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8 semesters
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Project work
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Internship
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Experiments
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Core Subjects
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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.
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Semester I
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Semester II
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Mathematics Essential
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Data Science Applications of NLP
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Introduction to Artificial Intelligence
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Deep Learning
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Machine Learning
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Robotics & AI
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Programming in Python
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Game Theory & Artificial Intelligence
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Computer Graphics and Animation
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Distributed Systems & Cloud Computing
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Programming in Python – Lab
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Robotics & AI – Lab
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Computer Graphics and Animation – Lab
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Distributed Systems & Cloud Computing – Lab
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Project Work
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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:
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Case Studies
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Experiments
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Real-time Projects
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Internships
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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.
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Write a program utilizing tree traversal techniques.
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Write a Java application that sorts a list of names alphabetically using the Quick Sort algorithm;
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Create a program that uses the graph traversal techniques.
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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.
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Create a Python program that demonstrates using dictionaries.
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Use C programming to demonstrate the aforementioned IPC techniques.
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Pipes
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FIFOs
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Message Queues
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Shared Memory
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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.
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Books
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Author
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Discrete Mathematics and its Applications with Combinatorics and Graph Theory
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Kenneth H Rosen, 7th Edition, TMH.
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Discrete Mathematics
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Richard Johnsonbaugh, 7ThEdn., Pearson Education.
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Fundamentals of Data Structures in C
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E. Horowitz, S. Sahni and Susan Anderson Freed, Universities Press
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Computer System Architecture
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M. Moris Mano, Third Edition, Pearson/PHI.
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Core Python Programming
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Wesley J. Chun, Second Edition, Pearson.
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Software Engineering, A Practitioner’s Approach
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Roger S. Pressman, 6th edition, Mc Graw Hill International Edition
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Advanced programming in the UNIX environment,
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W.R. Stevens, Pearson education.
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Database System Concepts
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Silberschatz, Korth, Mc Graw hill, V edition.
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Advanced programming in the Unix environment,
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W. R. Stevens, Pearson education.
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Also read :
Engineering colleges in Greater Noida
Engineering Colleges in Delhi with low fees
Artificial Intelligence in Btech
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:
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Mathematics for Intelligent Systems – I
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Computational Engineering Mechanics- I
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Object Oriented programming
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Elements of Computing System-I
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Introduction to Electrical Engineering
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Introduction to Digital Manufacturing
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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.