Artificial intelligence is one of the emerging and in-demand fields in computer science. The artificial intelligence syllabus focuses on providing you with a strong understanding of AI principles and tools and how they can be applied to solve real-world problems. Artificial Intelligence courses are offered at various levels with BTech courses being one of the most popular choices.
In the artificial intelligence syllabus, you will learn about topics like data structures, programming, algorithms, machine learning, deep learning, neural networks and more. The curriculum is also updated regularly to include the latest advancements. The syllabus generally consists of core and elective subjects along with practical learning through laboratories and internships.
- What is the syllabus of Artificial Intelligence?
1.2 What is the best way to learn Artificial Intelligence for a beginner?
- What is the syllabus for UG courses in Artificial Intelligence?
2.1 What is the syllabus for a BTech in Artificial Intelligence and Data Science?
2.2 What is the syllabus of the BTech Artificial Intelligence and Machine Learning Course?
2.3 What is the syllabus of a BE in AI and ML?
2.4 How much is the difference between the syllabus of CSE and CSE (AI and ML) BTech?
- What is the syllabus for Artificial Intelligence in IIT?
- What is the syllabus for PG courses in Artificial Intelligence?
4.1 What is the syllabus for an MTech in Artificial Intelligence?
4.2 What is the syllabus of the MTech Artificial Intelligence and Machine Learning Course?
4.3 What is the syllabus of the MBA Artificial Intelligence and Data Science Course?
- What are the best books for Artificial Intelligence Courses?
- Artificial Intelligence Course Syllabus: FAQs
What is the syllabus of Artificial Intelligence?
The artificial intelligence syllabus covers basic and advanced topics related to AI and its related specialisations like machine learning, data science, data analytics and more. During the initial years, you will learn about core subjects like programming, algorithms, DBMS and data structures. The following years build upon the knowledge and will introduce advanced topics like NLP, deep learning and more to provide you with a comprehensive education in artificial intelligence.
Is AI a hard subject?
Artificial Intelligence is considered to be challenging because of its complex topics and reliance on mathematical concepts. You should have a strong foundation in computer science to understand different programming languages and handle topics like machine learning, deep learning, neural networks and more. With proper dedication, resources and effective strategy, you can easily manage the course and understand topics effectively.
What is the best way to learn Artificial Intelligence for a beginner?
To learn artificial intelligence as a beginner, you must start by learning programming languages like Python, Java and C. You are also required to have a thorough understanding of mathematical concepts like linear algebra, probability, calculus and more. You can also explore introductory courses on online platforms like Udemy, Coursera and edX. These courses also include project-based learning that can help you build a strong foundation in artificial intelligence. There are also AI books aimed at beginners.
What is the syllabus for UG courses in Artificial Intelligence?
The undergraduate courses for artificial intelligence generally cover topics related to computer science and artificial intelligence. Computer science topics include data structures, algorithms, programming languages, and mathematics, which form the core of the curriculum. Topics related to artificial intelligence include machine learning, deep learning, neural networks and more. You can check the syllabus of some of the top undergraduate courses covering artificial intelligence in the following sections.
What is the syllabus for a BTech in Artificial Intelligence and Data Science?
BTech in Artificial Intelligence and Data Science is one of the most popular courses in the field. The general curriculum remains the same in all colleges. Differences can occur in the coverage of some topics or the availability of electives. You can check the syllabus below.
| BTech in Artificial Intelligence and Data Science syllabus | |
|---|---|
| Ist Semester | IInd Semester |
| Physics | General Biology |
| Chemistry | Problem Solving by Programming |
| Fundamentals of Programming Languages | Computational Statistics |
| Basic Electronics and Electrical Engineering | Engineering Graphics and Design |
| Mathematics | Engineering Mechanics |
| Communication Skills | Project-Based Learning - I |
|
– |
Laboratory - Workshop and Manufacturing Practices |
| IIIrd Semester | IVth Semester |
| Data Structures and Algorithms | Foundations of Data Science |
| Software Engineering and Project Management | R Programming |
| Discrete Structure | Computer Networks |
| Database Management Systems | Artificial Intelligence |
| Project-Based Learning - I | Digital Logic Design and Processor Architecture |
| Universal Human Values |
– |
| Vth Semester | VIth Semester |
| Machine Learning | Deep Learning |
| Big Data Analytics | Advanced Databases |
| Web Technology | Machine Learning and Network Security |
| Design and Analysis of Algorithm | Information Retrieval |
| Elective I | Elective II |
| Skill Enhancement Course I | Skill Enhancement Course II |
| VIIth Semester | VIIIth Semester |
| Skill Enhancement Course III | Skill Enhancement Course IV |
| Project I/Internship | Project II/Internship |
What is the syllabus of the BTech Artificial Intelligence and Machine Learning Course?
The syllabus of BTech in Artificial Intelligence and Machine Learning is mostly the same as most of the artificial intelligence curriculum. The differences occur in specialisation like data science, machine learning and more. You can check the syllabus in the following table.
| BTech in Artificial Intelligence and Machine Learning syllabus | |
|---|---|
| Ist Semester | IInd Semester |
| Engineering Physics I | Engineering Physics II |
| Engineering Chemistry | Mathematics II |
| Mathematics I | Engineering Graphics |
| Python Programming and Problem Solving | C Programming |
| Technical English I | Environmental Science and Engineering |
| Basic Civil and Mechanical Engineering | Professional Skills I |
|
– |
Basic Electrical and Electronics Engineering |
| IIIrd Semester | IVth Semester |
| Data Structures in Python | Artificial Intelligence I |
| Object Oriented Programming | Machine Learning I |
| Computer Organisation and Architecture | Operating System Concepts |
| Design and Analysis of Algorithms | Software Engineering |
| Digital Principles and Systems Design | Database Design and Management |
| Linear Algebra and Discrete Mathematics | Probability and Statistics |
| Professional Skills II | Professional Skills III |
| Vth Semester | VIth Semester |
| Artificial Intelligence II | Data Exploration and Visualisation |
| Machine Learning II | Big Data Management |
| Data Mining and Analytics | Web Technology |
| Optimisation Techniques | Healthcare Analytics |
| Data Communication and Networking | Professional Elective II |
| Professional Elective I | Professional Elective III |
| Professional Skills IV |
– |
| VIIth Semester | VIIIth Semester |
| Artificial Intelligence and Robotics | Software Project Management |
| Natural Language Processing | Professional Elective V |
| Deep Learning Techniques | Open Elective II |
| Professional Elective IV |
– |
| Open Elective I |
– |
What is the syllabus of a BE in AI and ML?
BE courses are also offered in the artificial intelligence discipline with different specialisations. You can check the BE Artificial Intelligence and Machine Learning syllabus in the table below.
| BE in Artificial Intelligence and Machine Learning syllabus | |
|---|---|
| Ist Semester | IInd Semester |
| Engineering Physics | Elements of Civil Engineering and Mechanics |
| Engineering Chemistry | Engineering Visualisation |
| Advanced Calculus and Numerical Methods | Elements of Mechanical Engineering |
| Calculus and Differential Equations | Communicative English |
| Problem Solving through Programming | Basic Electrical Engineering |
| Basic Electronics and Communication Engineering | Scientific Foundations of Health/Innovation and Design Thinking |
| Ability Enhancement Course I | Ability Enhancement Course II |
| IIIrd Semester | IVth Semester |
| Data Structures and its Applications | Biology for Engineers |
| Computer Organisation and Architecture | Operating System |
| Analog and Digital Electronics | Design and Analysis of Algorithms |
| Transform Calculus, Fourier Series and Numerical Techniques | Mathematical Foundations for Computing |
| Object Oriented Programming with Java | Microcontroller and Embedded Systems |
| Ability Enhancement Course III | Python Programming |
|
– |
Ability Enhancement Course IV |
| Vth Semester | VIth Semester |
| Computer Networks | Machine Learning |
| Database Management Systems | Data Science and its Applications |
| Automata Theory and Compiler Design | Software Engineering and Project Management |
| Principles of Artificial Intelligence | Professional Elective I |
| Environmental Studies | Open Elective I |
| Research Methodology and Intellectual Property Rights | Mini Project |
| Ability Enhancement Course V |
– |
| VIIth Semester | VIIIth Semester |
| Cloud Computing | Research Internship/Industry Internship |
| Advanced AI and ML | Technical Seminar |
| Professional Elective II |
– |
| Professional Elective III |
– |
| Open Elective II |
– |
| Project Work |
– |
How much is the difference between the syllabus of CSE and CSE (AI and ML) BTech?
BTech CSE and BTech CSE (AI and ML) have common topics during the initial years. Core subjects like data structures, databases, operating systems, programming languages and mathematical concepts are covered in both the curriculum.
Differences occur during the later years when BTech CSE (AI and ML) courses will cover specific topics related to the specialisation. You will learn about machine learning, NLP, deep learning, reinforcement learning and more. With BTech CSE, you will be introduced to broader topics like software engineering and more.
What is the syllabus for Artificial Intelligence in IIT?
IITs are known for their rigorous curriculum and quality education. Many IITs have included artificial intelligence courses in their curriculum in recent years. IIT Madras, IIT Kharagpur, IIT Roorkee, IIT Hyderabad and IIT Guwahati are some of the top IITs for pursuing artificial intelligence courses. You can check the syllabus of the BTech Artificial Intelligence and Data Analytics course which was introduced by IIT Madras in 2025 below.
| BTech in AI and Data Analytics syllabus | |
|---|---|
| Ist Semester | IInd Semester |
| Programming and Data Structures | Probability and Statistics for Engineers |
| Programming Laboratory | Introduction to Computational Chemistry |
| Basics of Engineering Principles | Optimisation for Engineers |
| Foundations of Linear Algebra | Computational Methods for DS |
| Calculus for Engineers | Life Skills II |
| Ecology and Environment | Recreation II |
| Workshop I | NSO/NCC/NSS |
| Life Skills I | Optimisation Lab |
| NSO/NCC/NSS |
– |
| Recreation I |
– |
| IIIrd Semester | IVth Semester |
| Introduction to Computational Physics | Artificial Intelligence |
| Introduction to Computational Biology | Introduction to Computer Systems |
| Machine Learning I | Algorithms for Data Science |
| Data Curation and Visualisation | Physics Elective |
| Entrepreneurship Course | Free (Unallotted) Elective |
| Machine Learning Lab | AI Lab |
| Vth Semester | VIth Semester |
| Machine Learning II | Humanities Course |
| Databases | Free (Unallotted) Elective |
| Deep Learning | Free (Unallotted) Elective |
| Core Basket I | Free (Unallotted) Elective |
| Dept. Elective | Free (Unallotted) Elective |
| ML ops Lab |
– |
| DL Lab |
– |
| VIIth Semester | VIIIth Semester |
| Responsible AI | Project II/Elective |
| Online and Reinforcement Learning | Elective |
| Core Basket II | Professional Ethics |
| Dept. Elective | Humanities Elective |
| Humanities Elective |
– |
| Project I |
– |
What is the syllabus for PG courses in Artificial Intelligence?
Postgraduate courses in artificial intelligence have more advanced and complex syllabi compared to undergraduate courses. Emphasis is given to research and projects often include the use of AI in real-world applications. Advanced machine learning, natural language processing (NLP), advanced computer vision and deep learning are some of the common core topics. You can check the syllabus of some of the top postgraduate courses covering artificial intelligence in the following sections.
What is the syllabus for an MTech in Artificial Intelligence?
MTech in Artificial Intelligence builds upon the foundation you gained during your undergraduate artificial intelligence course. It will introduce you to advanced topics along with covering some of the previous topics in more detail. You can check the MTech AI syllabus below.
| MTech Artificial Intelligence syllabus | |
|---|---|
| Ist Semester | IInd Semester |
| Introduction to Artificial Intelligence | Deep Learning |
| Machine Learning | Applied Statistics and Probability |
| Mathematical Foundations for Machine Learning | Optimisation Techniques for Machine Learning |
| Python Programming | Elective II |
| Elective I | Deep Learning Lab |
| Machine Learning | Exploratory Data Analysis Lab |
| Python Programming Lab |
– |
| IIIrd Semester | IVth Semester |
| Advanced Deep Learning | Dissertation Phase II |
| Deep Reinforcement Learning |
– |
| Research Methodology |
– |
| Elective III |
– |
| Elective IV |
– |
| Dissertation Phase I |
– |
What is the syllabus of the MTech Artificial Intelligence and Machine Learning Course?
MTech in Artificial Intelligence with a specialisation in Machine Learning is a popular course amongst postgraduate students. Mentioned below is the syllabus as offered by the BITS Pilani.
| MTech Artificial Intelligence and Machine Learning syllabus | |
|---|---|
| Ist Semester | IInd Semester |
| Machine Learning | Deep Neural Networks |
| Artificial and Computational Intelligence | Deep Reinforcement Learning |
| Introduction to Statistical Methods | Elective I |
| Mathematical Foundations in Machine Learning | Elective II |
| IIIrd Semester | IVth Semester |
| Elective III | Dissertation |
| Elective IV |
– |
| Elective V |
– |
| Elective VI |
– |
Electives include topics from deep learning specialisation, natural language processing (NLP) specialisation and general electives.
What is the syllabus of the MBA Artificial Intelligence and Data Science Course?
Artificial intelligence courses are also offered in MBA format. It will provide you with the knowledge and skills to leverage artificial intelligence tools for business growth, better performance and problem-solving. The course combines business principles with artificial intelligence technologies. You can check the MBA Artificial Intelligence and Data Science syllabus in the following table.
| MBA Artificial Intelligence and Data Science syllabus | |
|---|---|
| Ist Semester | IInd Semester |
| Marketing Management | Operations Management |
| Managerial Economics and Indian Economy Policy | Human Resources Management |
| Organisational Behaviour and Design | Corporate Finance |
| Financial Reporting, Statement and Analysis | Legal and Business Environment |
| Information Management | Indian Ethos and Corporate Strategy |
| Statistics and Quantitative Techniques | Entrepreneurship |
| Managerial Skills and Communication | Business Analytics |
| Professional Upskilling I | Research Methods in Business |
|
– |
Professional Upskilling II |
| IIIrd Semester | IVth Semester |
| Introduction to Machine Learning | Advanced Machine Learning |
| Artificial Intelligence and its Application | Deep Learning II |
| Natural Language Processing | Big Data Management and Security |
| Data Visualisation | Business Intelligence |
| Analytics Toolkit for Decision Sciences | Project |
| Deep Learning I |
– |
| Summer Internship |
– |
What are the best books for Artificial Intelligence Courses?
There are many books that you can consider for your artificial intelligence courses. These can be helpful in course preparation as they cover the foundational as well as advanced topics. You can check some of the top books in the following table.
| Book | Author |
|---|---|
| Computer Architecture: A Quantitative Approach | Hennesey and Patterson |
| Computer Networks | Forouzan |
| Database Systems | Elmasri and Nawathe |
| Digital Design | Morris Mano |
| Introduction to Algorithms | Thomas Cormen, Charles Leiserson, Ronal Rivest, Clifford Stein |
| Introduction to Automata Theory, Languages and Computation | John Hopcroft, Rajeev Motwani, J D Ullman |
| Modern Operating Systems | Andrew Tanenbaum |
| Operating Systems Concepts | Galvin and Gagne |
| Artificial Intelligence: A Modern Approach | Stuart Russell, Peter Norvig |
| Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow | Aurelien Geron, |
| Cognitive Computing and Big Data Analytics | Hurwitz, Kaufman, Bowels |
| Embedded Systems and Robots | S Ghoshal |
| Neural Networks | Siman Haykin |
| Artificial Intelligence and Intelligent Systems | NP Padhy |
| Artificial Intelligence: A Guide for Thinking Humans | Melanie Mitchell |
Artificial Intelligence Course Syllabus: FAQs
Ques. Do I have to learn programming languages for artificial intelligence courses?
Ans. Learning programming languages is essential for artificial intelligence courses. Python and Java are some of the popular languages that are generally included in artificial intelligence courses. Programming languages will help you implement AI solutions with ease and is an important part of AI development.
Ques. Do artificial intelligence courses need maths?
Ans. Artificial intelligence has topics like machine learning, deep learning, neural networks and more which require a strong grasp of mathematical concepts. A good knowledge of mathematics can help you understand complex algorithms allowing you to generate more effective algorithms. Linear algebra, calculus, statistics and probability are some of the most commonly used mathematical concepts in AI.
Ques. I am from a non-computer science background. How can the AI syllabus help me to understand topics?
Ans. Most of the artificial intelligence courses cover the foundational topics during the initial years. You will learn about data structures, algorithms, operating systems and more that can help build a strong base. This ensures that you have a good knowledge of core concepts before moving to advanced topics.
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