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

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.

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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.

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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.

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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.

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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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