A comprehensive understanding of how to build efficient, error-free code that enables a machine to perform tasks with less help from a person is emphasized in the B.Tech Artificial Intelligence Syllabus. B.Tech in AI syllabus depends on the specializations you choose.
If you choose B.Tech AI and ML syllabus, then the course will be more focused on automation and robotics, while B.Tech AI and Data Science are more focused on data analysis.
The eight semesters of the B.Tech AI and ML syllabus include projects, seminars, industrial training, laboratory and practical work, and core and elective courses. Some of the key subjects are mechanics, artificial intelligence, data structures and algorithms, machine learning, big data analytics, deep learning, web technology, and so forth.
Students pursuing the B.Tech AI and Data Science syllabus will learn about software engineering, data structures and algorithms, programming languages, database administration, data mining, data warehouses, scripting languages, machine learning, big data analytics, etc.
B.Tech Artificial Intelligence syllabus can help you build careers as data scientists, data engineers, software designers, data interpreters, etc.
An Intro to B.Tech Artificial Intelligence Syllabus
A subfield of computer science called artificial intelligence (AI) focuses on building robots that are capable of learning, reasoning, problem-solving, perception, and language comprehension—tasks that normally require human intelligence.
Key Statistics of the B.Tech AI and ML
The bright future of AI offers amazing opportunities for B.Tech AI and ML graduates who can adapt and deploy innovative ideas to change the world. The table below allows prospective students to examine the specifics of the B.Tech AI and ML subjects:
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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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Candidates who meet the requirements for their 10+2 exam from an accredited Board and Science stream (compulsory topics in mathematics and physics) are qualified.
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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 Scientist, Data Engineer, Data Scientist, Data Analyst, Computer Vision Engineer, etc.
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Foundational Subjects in B.Tech Artificial Intelligence Syllabus
Core Subjects in Artificial Intelligence
An introduction to AI principles, its history, and ethical issues are all part of the basic curriculum of an artificial intelligence course.
Statistics and Mathematics
Linear algebra, calculus, probability, and statistics are all crucial for comprehending algorithms and data evaluation in artificial intelligence (AI).
Machine Learning
The study of methods and algorithms that let computers learn from data and come to conclusions or predictions.
NLP, or natural language processing
Methods for comprehending and interpreting human language are employed in speech recognition and translation applications.
Computers Vision
Techniques like object identification and picture recognition for processing and evaluating visual data.
Robotics:
The use of artificial intelligence (AI) methods in the creation of autonomous systems and robots.
Semester-Wise B.Tech AI and ML Subjects
Numerous core and elective courses are included in the B.Tech AI and ML syllabus. Third-year students are the first to be offered elective courses.
B.Tech AI and ML students must choose their elective courses based on their future educational goals, personal interests, and career aspirations. See the detailed syllabus for the B.Tech in AI and ML 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 the 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 Professional
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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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-
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Introduction to Deep Learning
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-
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Semester-Wise B.Tech in AI and Data Science Syllabus
The curriculum is intended to give students a solid foundation in data science, AI, and machine learning. Typically, the B.Tech AI and Data Science syllabus consists of the following:
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Semester
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Core Subjects
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1st
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Mathematics for AI, Programming Fundamentals, Physics, and Engineering Graphics
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2nd
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Data Structures, Probability & Statistics, Computer Organisation, Database Management Systems
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3rd
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Machine Learning, Artificial Intelligence, Big Data Analytics, Operating Systems
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4th
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Deep Learning, Cloud Computing, Internet of Things (IoT), Natural Language Processing
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5th
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Reinforcement Learning, Neural Networks, AI in Healthcare, Ethics in AI
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6th
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Research Methodology, AI Project Development, Business Analytics, Robotics
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7th & 8th
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Industrial Training, Capstone Project, Advanced AI Topics, Electives
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B.Tech AI and ML Syllabus in AKTU
The B.Tech AI and ML syllabus in AKTU colleges must be reviewed by students who want to pursue engineering at AKTU in order to gain a sense of what they will be studying. For a better understanding of the B.Tech AI and ML syllabus, look at the table below, which lists all of the required and elective courses:
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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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-
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Intellectual Property Rights
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-
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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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Diploma in Artificial Intelligence Syllabus
Mathematical topics like statistics and linear algebra, as well as fundamental machine learning ideas like supervised and unsupervised learning, data visualization tools and methods, and more, are all included in a diploma program in artificial intelligence.
By enrolling in this course, you will have the opportunity to become an expert in one of the most fascinating and quickly developing areas of computer science. Students will be able to advance in their employment during the time of rapidly growing AI-ML applications, thanks to the Diploma in Artificial Intelligence syllabus.
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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 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, 7th Edn., Pearson Education.
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Fundamentals of Data Structures in C
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E. Horowitz, S. Sahni, and Susan Anderson Freed, University 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, McGraw-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, McGraw 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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Best Books for B.Tech AI and Data Science Syllabus
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“Data Mining: Concepts and Techniques” by Arun K. Pujari
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“Fundamentals of Artificial Intelligence” by V. K. Jain
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“Data Science and Big Data Analytics” by EMC Education Services (Indian Edition)
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“Artificial Intelligence: A Modern Approach” by Stuart Russell & Peter Norvig
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“Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow” by Aurélien Géron
Conclusion
A four-year undergraduate program called the B.Tech in Artificial Intelligence is intended for students who wish to establish a solid foundation in advanced computers and intelligent systems.
This program offers organized learning across artificial intelligence, machine learning, and data science with a strong focus on real-world applications, making it ideal for candidates considering which university is best for artificial intelligence.
B.Tech Artificial Intelligence colleges teach fundamental concepts to assist students in comprehending the extent of artificial intelligence and its increasing relevance across industries.
Also read :
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.