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Home AI and Machine Learning Artificial Intelligence (AI) & Machine Learning (ML) Course Syllabus 2024: Curriculum Structure, Subjects, Books

Artificial Intelligence (AI) & Machine Learning (ML) Course Syllabus 2024: Curriculum Structure, Subjects, Books

Mar 6, 2024 3.4K Reads

With the growing integration of artificial intelligence and machine learning technologies in softwares and electronic services, both undergraduate and postgraduate courses in AI and ML have become popular as choices in technological studies. The curriculum of these UG and PG courses related to AI and ML explore the theoretical fundamentals of artificial intelligence principles along with the complex concepts related to it. 

In this blog, we have explored in detail the curricular structure and subjects in the syllabus of various undergraduate and postgraduate courses in artificial intelligence and machine learning. Continue reading to find out further details about the same!

What are the Major Courses in AI and ML? 

Artificial intelligence is a domain of computer science concerned with the creation of softwares and systems that can behave and carry out operations in a manner reflective of human intelligence. AI domains such as machine learning (which is the training and creation of AI models to simulate human intelligence), deep learning, natural language processing etc. are important to the development of strong and advanced AI models capable of handling complex operations in an intelligent fashion. Accordingly, the syllabus and curricula of courses related to AI and ML also include certain common subjects fundamental to the discipline, including machine learning, deep learning, reinforcement learning, neural networks, natural language processing and so on. 

In order to understand the curricula of an AI & ML course better, one needs to assess the level of the course and the complexity of it. Undergraduate courses are more focused on developing a strong base of fundamental concepts involved in artificial intelligence and machine learning, whereas if you pursue a postgraduate course in AI and ML, the course curriculum would develop your knowledge in the domain further with a focus on more applied and complex concepts. 

Enlisted below are a few of the most popular courses in artificial intelligence and machine learning available to be pursued in India.

Undergraduate Courses in AI & ML

Postgraduate Courses in AI & ML 

B.Sc in Artificial Intelligence and Data Science 

MBA in Artificial Intelligence & Machine Learning (AI & ML) 

BCA in Artificial Intelligence & Machine Learning (AI & ML) 

MCA in Artificial Intelligence

BCA in Artificial Intelligence (AI)

MCA in Machine Learning  

BCA in Machine Learning (ML)

MCA in Artificial Intelligence & Machine Learning (AI & ML)

B.Tech in CSE (AI & ML)

MBA in Artificial Intelligence & Business Intelligence 

 

Executive Postgraduate Diploma (PGD) in AI & ML 

 

Postgraduate Diploma (PGD) in AI & ML

 

PG Certification Course in AI & ML 

 

Job-guaranteed Certification Course in Machine Learning

If you are a candidate interested in pursuing a course in artificial intelligence and machine learning, then here are a few important points for you to take note of: 

  • In India, there are AI and ML courses offered in two major modes, the fully online learning mode (OL) and the regular learning mode. 
  •  All the major courses enlisted above (except B.Tech) are available in India in both online and regular mode. 
  • The syllabus and structure of the courses is the same and equivalent in both online and regular learning modes. 
  • The subjects, capstone projects, hands-on practicum and lab lessons in both online learning and regular mode are similar and equivalent. Hence, a student pursuing an online AIML course would study the same subjects and concepts as a student of regular AIML courses. 

Undergraduate Degree Syllabus & Subjects in Artificial Intelligence and Machine Learning 

Explore further details about the most popularly pursued undergraduate courses in AI and ML along with their pertinent details about the course curricula and subjects. 

1 ) BCA in Artificial Intelligence & Machine Learning 

A BCA in AI and ML is a dual specialisation UG degree course which is of a duration of 3 years. The structure of the syllabus of this course is divided into 6 semesters, each of nearly 6 months duration. In most colleges and institutes, the first 2 semesters consist of core subjects common to all specialisations of BCA which introduce the students to the fundamentals of computer applications.

Enroll Today!

BCA Online In AI and ML

BCA Degree Online

BCA Part Time

BCA Distance Education

From the third semester until the sixth semester, the various specialisation-specific courses of AI and ML are introduced. Some of the common concepts covered in this course include Python programming, data structures and algorithms, introductory papers to artificial intelligence, Java, statistical analyses, RDBMS etc. In addition to the theory papers mentioned herein, it is important to note that this course syllabus also includes practical lab slots wherein the students are taught and tested upon their ability to apply the learnt theoretical concepts in actual development of AI models. 

Details about the generally offered subjects in BCA in AI and ML have been provided below.

Elements of Mathematics 

Introduction to Programming and C

Problem Solving and Algorithmic Thinking

Foundations of Applied Mathematics 

Database Management System

Object Oriented Programming using Java

Data Structures and Algorithms 

C# and .NET Framework

Introduction to VR Programming

Augmented Reality for Marketing and Business Integrations

Designing human computer interfaces

3D interaction design and 3D models for virtual reality

Internet Technologies 

Numerical Analyses and Statistical Techniques 

Web Applications

Fundamentals of AI 

AI Using Azure 

Relational Database Management System

Security of Information Systems

Machine Learning Tools

2 )  B.Tech in Artificial Intelligence and Machine Learning (AI & ML) 

A B.Tech in artificial intelligence and machine learning is a 4-year engineering degree in the umbrella domain of computer science engineering. This course, spanned across 8 semesters of 6 months duration each, consists of a coverage of the basic concepts of engineering, followed by the study of papers specific to CSE and more specifically, AI and ML.

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BTech for Working Professionals

B.Tech After Diploma

BTech Online?

B.Tech Distance Education?

B.Tech course syllabus is heavily focused on the balance between theoretical and practical lessons allowing students to develop well-honed skills in AI and ML programming. Further details about the course syllabus and commonly included subjects are provided below. 

Linear Algebra

Basic Electrical & Electronics Engineering

Programming in C

Introduction to Python Programming

Communication Skills 

Statistics for Data Science

Software Tools for AI & ML

Probability and Random Processes

Data Structures and Algorithms

Application and Use Cases of Machine Learning

Data Reprocessing

Supervised Machine Learning

Database Concepts for Data Science

AI Ethics

Deep Learning

Optimization Techniques for Machine Learning

Generative Adversarial Networks

Natural Language Processing

Data Visualization 

Reinforcement Learning

3 ) B.Sc in Data Science & Artificial Intelligence 

A B.Sc in Data Science and Artificial Intelligence is a 3-year dual specialisation course with a twin focus on domains of data science and analytics as well as AI. The course curriculum is spanned across 6 semesters for this course, with a coverage of common subjects related to computer science including mathematics and statistics, programming etc. in the first and second semesters.

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BSc Online In Data Science and AI

BSc Online In Data Science

BSc Part Time

BSc Distance Education

From the third semester, a coverage of the fundamental concepts of AI and data science, such as machine learning, data visualisation, big data technologies, deep learning, data ethics, applications of AI, generative AI models etc. is focused upon. The general syllabus of B.Sc in Data Science and AI is provided below. 

Mathematics for Data Science 

Programming Fundamentals 

Machine Learning 

Deep Learning 

Data Structures & Algorithms 

Statistics for Data Science 

Fundamentals of AI 

Data Visualisation

Big Data Technologies

Reinforcement Learning 

Computer Vision

Data Ethics & Privacy 

Natural Language Processing 

AI for Business 

Deep Generative Models

AI for Robotics 

Time Series Analysis 

AI for Finance 

AI for Industry Applications 

AI in Research & Development 

Postgraduate Degree Syllabus & Subjects in Artificial Intelligence and Machine Learning 

The most popular postgraduate courses in artificial intelligence and machine learning (AI & ML) include those like an MCA, an M.Tech, an MBA etc. The syllabus details about these courses along with lists of subjects commonly included in them have been provided below. 

1) MCA in Artificial Intelligence & Machine Learning (AI & ML)

A Masters in Computer Applications is a two-year PG degree course that provides detailed education to learners related to key domains of computer applications and principles. 

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MCA Degree Online

MCA Online In Artificial Intelligence

MCA Part Time

MCA Distance Education

The specialisation of AI and ML in an MCA program brings together a blend of both core papers related to fundamentals of computer applications (e.g. computer systems, mathematical foundations involved in computer applications, computer vision etc.) along with specialisation papers related to the technical complexities of AI and ML (e.g. data structures and algorithms, deep learning, NLP, applied predictive analyses, complex network analysis, web analytics etc.). Emphasis is also laid on the development of practical skills and proficiencies in domains of AI and ML. 

Find a list of the subjects and courses generally included in an MCA in AI and ML below. 

Foundations of Computer Systems

Mathematical Foundations for Computer Applications

Data Structures and Algorithms

Cloud Computing

Software Project Management

Research Methodology

Foundations of Machine Learning

Deep Learning for AI

Natural Language Processing

Data Visualization

Applied Predictive Analytics

Business Analytics and Visualization

Data Engineering for AI

Complex Network Analysis

No-SQL Databases

Reinforcement Learning

Artificial Intelligence for Robotics

Applications of Machine Learning

Web Analytics

Computational Statistics

Representation Learning

AI for Drug Discovery and Target Validation

IoT for AI

Medical Signal Processing

Computer Vision

Advanced Software Engineering Principles

Network Security 

Cryptography 

2) MBA in Artificial Intelligence & Machine Learning (AI & ML) 

Unlike an MCA or an M.Tech program, an MBA in AI and ML is focused on the technicalities of artificial intelligence and machine learning from a managerial perspective, with an emphasis on the integration and application of these technologies in the effective management of organisations and business ventures. In this 2-year PG degree program, the first two semesters generally include the coverage of the core papers of management including those like marketing management, business statistics, accounting and financial management, HR management etc.

Enroll Today!

Online MBA In AI and ML

Online MBA Programme

MBA Distance Education

MBA Part Time

MBA for Working Professionals

Executive MBA for Working Professionals

Executive MBA Online

IIM MBA Online

while the third and fourth semesters include a combination of core papers and specialisation-specific courses such as NLP, deep learning, data visualisation, applications of AI in business, performing analytics, R-programming etc. Further details of the papers commonly included in this course have been enlisted below. 

Business Communications

Managerial Economics-Micro and Macro

Organisational Behaviour

Marketing Management

Business Statistics

Accounting for Managers

Technology Transformation for Business

Business Analytics 

Strategic Management

Foundations of Computer Systems

Natural Language Processing

Artificial Intelligence and its Applications

Deep Learning

Advanced Machine Learning

Introduction to Machine Learning

Data Visualization

Entrepreneurship and Innovation

International Business

Consumer Behaviour

Applications of AI in Business 

Machine Learning 

R-Programming for Data Analytics & Data Visualisation

Performing Analytics 

Neural Networks & Machine Learning Algorithms 

3) MBA in AI and Business Intelligence 

An MBA in the specialisation of AI and business intelligence is a management degree focused upon the utilisation of AI principles in business growth and development. The four semesters of the course introduce the student to the foundational domains of management as well as the integration of AI into business ventures and its effective management.

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Online MBA In AI and Business Analytics

Online MBA In Business Analytics

Online MBA In Data Science

Online MBA In IT Management

Some of the main subjects included in this specialisation are DBMS for managers, analytics languages for managers, Tableau and MS Excel, use of analytics in industry, deep learning, machine learning and AI basics, applications of AI etc. The further details about the course are provided below. 

Principles of Economics & Markets

Managerial Effectiveness & Ethics

Accounting & Finance

Quantitative Techniques & Analytics

Marketing Management & Research

Analytics Language for Managers

DBMS for Managers

Mathematical Foundation for Machine Learning

Business Environment & Strategy

Data Analytics and Storytelling using Tableau and Excel

Machine Learning & AI

Introduction to Deep Learning

Application of AI-Speech, Text and Image Processing

Analytics in Industry- Ecommerce, Healthcare and BFSI

NLP Fundamentals for AI

Artificial Intelligence and Deep Learning

4) M.Tech in Artificial Intelligence & Machine Learning (AI & ML) 

An M.Tech in AI and ML is a PG engineering degree course of 2 years divided into 4 semesters. Similar to most PG degree courses, the first and second semesters of the course are dedicated to the coverage of core engineering and CSE topics, while a wide range of specialisation-specific courses are covered through the third and fourth semesters.

Enroll Today!

M.Tech for Working Professionals

M.Tech Part Time

M.Tech Distance Education?

M.Tech Online?

The commonly included subjects in an M.Tech in AI and ML include deep reinforcement learning, machine learning, statistical methods, AI and computational intelligence, AI and ML for robotics, data management in machine learning, distributed systems, big data analytics, advanced data mining etc. Further details about the course syllabus for the program are provided below.

Mathematical Foundations for Machine Learning

Introduction to Statistical Methods

Deep Reinforcement Learning

Machine Learning

Artificial and Computational Intelligence

Design of Algorithms

Computer Vision

Probabilistic Graphical Models

AI and ML for Robotics

Data Management for Machine Learning

Advanced-Data Mining

AI and ML Techniques for Cybersecurity

Advanced Machine Learning

Distributed Systems

AI and ML Research

Big Data Analytics

5) Master of Science (MS) in Artificial Intelligence and Machine Learning (AI & ML)

A Master of Science in AI and ML is an equivalent of the PG degree-M.Tech in AI and ML offered in nations beyond India. This course can, however, also be pursued by students in India through the fully online mode in which it is offered on renowned MOOC platforms like upGrad.

Enroll Today!

MSc Degree Online

MSc Online In Data Science

MSc Distance Education

MSc Part Time

Common subjects included in this course generally are regression analysis, neural networks, NLP, machine learning systems, programming, MLOps, AI models, SQL, inferential statistics etc. More details about the M.Sc in AI and ML have been provided below. 

Intro to Python

Linear Regression Module

Advanced Regression

Logistic Regression

Introduction to Neural Networks

Convolutional Neural Networks

Recurrent Neural Networks

Natural Language Processing (NLP)

Introduction to MLops

Designing Machine Learning Systems

Automating and Orchestrating pipelines with Airflow

Advanced NLP - Introduction to Attention Mechanism

Fundamentals of Generative AI, ChatGPT & Prompt Engineering

Integrating speech using Whisper API

Applications of LLMs to create Embeddings for Large Documents

Introduction to Research and Research Process

Research Design

Research Project Management

Experimenting with Data and Model using MLflow

Gesture Recognition

Tree Models

Unsupervised Clustering

Python for DS

Data Visualisation using Python

Basic SQL

Advanced SQL

Inferential Stats

Hypothesis Testing

Syllabus in Artificial Intelligence & Machine Learning: Certificate Courses 

In addition to a number of UG and PG degree courses, there are a number of postgraduate (and a few undergraduate) courses with a certification provided upon completion. These courses usually have a duration of about 3 months to 24 months and can be taken up by beginners in the domain of AI, graduates in technological fields as well as executives and working professionals who wish to further their expertise in AI and ML. 

While the syllabus and curricula of these courses depend on the duration and the level of the course one is pursuing, a few of the major subjects in these certification courses have been listed below. It must be noted that an AI and ML certificate course is unlikely to include all the subjects mentioned herein, rather, the exact syllabus of a certificate program varies from course to course and institution to institution. 

Intro to Git & Github

Inferential Statistics

Linear Regression Module

Logistic Regression

Naive Bayes

Model Selection

Advanced Regression

Tree Models

Unsupervised Clustering

Introduction to Neural Networks 

Convolutional Neural Networks

Recurrent Neural Networks

Designing Machine Learning Systems

Automating and Orchestrating pipelines with Airflow

MLOps 

Advanced NLP 

Fundamentals of Generative AI, ChatGPT & Prompt Engineering 

Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python

Fundamentals of Multimodal LLMS 

Applications of Vectorstores

Scaling & Deployment of Generative AI Systems

Future Developments of Generative AI 

Exploratory Data Analysis

Cloud Essentials

Natural Language Processing: Lexical Processing, Syntactic Processing

Natural Language Processing: Semantic Processing

Syllabus in Artificial Intelligence & Machine Learning: Diploma Courses

Lastly, similar to degree courses in AI and ML, there are a number of undergraduate and postgraduate diploma courses available to be pursued in this field as well. Diploma courses in artificial intelligence and machine learning are shorter programs than degree courses and usually last between 12 to 18 months. Depending upon the duration of the course, they are divided into 2 to 3 semesters. Diploma courses generally include a melange of foundational courses in computer science and subjects specific to AI and ML in addition to practical classes for hands-on learning. Depending upon whether you take up a PG diploma, an executive diploma or a UG diploma course, the common subjects are likely to vary slightly. Mentioned below are a few of the major subjects and papers that are included in a diploma program in AI and ML. 

Intro to Git & Github

Inferential Statistics

Linear Regression Module

Logistic Regression

Advanced Regression

Introduction to Neural Networks 

Convolutional Neural Networks

Recurrent Neural Networks

Exploratory Data Analysis

Cloud Essentials

Natural Language Processing

Data Science using Excel and SPSS

Regression and Time Series Modeling using R

Machine Learning and Deep Learning using Python

Unsupervised Machine Learning using R

Tableau Masterclass

Recommendations for Books & Course Materials in AI & ML 

Mentioned below are a few of the resources and books one can refer to for strengthening their knowledge base and foundation in artificial intelligence and machine learning. 

Books 

Author(s) 

Publisher 

Artificial Intelligence: A Modern Approach 

S. Russell, P. Norvig 

Berkeley Edu.

Deep Learning 

I. Goodfellow, Y. Bengio, A. Courville 

MIT Press

Python Machine Learning 

S. Raschka

Packt Publishing Ltd. 

Machine Learning Yearning

A. NG

Andrew NG © 

Fundamentals of Data Structures in C

E. Horowitz, S. Sahni, S. A. Freed

Universities Press

Advanced Programming in the UNIX Environment

W.R. Stevens

Pearson Education

Core Python Programming

Wesley J. Chun

Pearson Education

Artificial Intelligence and Machine Learning

V. Chandra S. S., A. Hareendran S. 

PHI Learning

Kindly note that the aforementioned books are suggested readings for strengthening one’s expertise in artificial intelligence and machine learning and are by no means prescribed readings for any course. 

Conclusion

Thus, the course curricula of AI and ML programs usually require the learner to have a strong foundation in mathematics and statistics along with knowledge of programming and computer softwares. The syllabus of such courses focuses on domains related to AI model development, ML model development, training and reinforcement learning, deep learning, NLP principles etc. The course structure usually incorporates practical hands-on lab classes in addition to the theoretical classes.

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FAQs (Frequently Asked Questions)

While there are a number of courses and subjects in AI and ML that do not require core mathematics, a significant number of papers and domains in it require the knowledge of mathematics, especially algebra, statistics, basic calculus, probability etc.

If one has a firm foundation in domains like computer programming, mathematics, statistics, algebra, calculus etc. then the syllabus would not be very difficult for a student. However, some concepts in AI and ML can be quite complex, including those like advanced regression, model training and reinforcement learning, NLP, machine learning algorithms etc. The experienced difficulty of an AI and ML course can also vary as per the level of the course (UG versus PG versus Executive).

The CSE syllabus includes a number of subjects common across various domains of software engineering including AI and ML as a subdomain. Commonly included subjects in the syllabus of CSE include programming and coding, data structures, operating systems, computer architecture etc. On the other hand, the syllabus of CSE AIML is more focused specifically on machine learning and artificial intelligence and includes subjects such as deep learning, reinforcement learning, neural networks, natural language processing etc.

Fundamental knowledge in mathematics, including domains like linear algebra, matrix algebra, calculus, statistics, probability etc. is required to excel in a field like artificial intelligence and machine learning, as many major subjects in this domain require mathematical operations and conceptual knowledge.

The major subjects in AI and ML include deep learning, machine learning algorithms, data structures, data visualisation, AI models,

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