Machine Learning Syllabus: Course-wise Subjects [2024]

With the cutting-edge technology of machine learning transforming the purview of digital and technological operations, a larger number of students are turning to formal education in this domain. Not only are they looking to learn the fundamentals of ML in courses like degrees, diplomas, and certificates, but they are also actively exploring the various subdomains of ML to assess their fit in each domain.

An exploration of the various subjects and curricular structure of ML courses reveals the various pertinent areas of the field one can look to upskill in.

If you are also a student or enthusiast interested in knowing more about machine learning courses with respect to their curriculum and subjects, then this blog is just the spot for you, as we have detailed the various courses in machine learning, their curriculum, and important subject areas that one can look to upskill in.

What are the Major Courses in Machine Learning?

There are a vast number of courses including those at the undergraduate, postgraduate, and executive levels available for students and working professionals to pursue in machine learning. Most of the courses in this field are offered in dual specializations, commonly with interrelated domains of ML-like artificial intelligence, deep learning, data science, NLP, etc.

Similarly, there are a number of degree programs, diplomas, and certification courses on a short-term basis available to be pursued in machine learning.

The most commonly pursued courses in machine learning in India available to be pursued as offline and online learning programs have been listed herein.

Undergraduate Courses in Machine Learning	Postgraduate Courses in Machine Learning
BCA In Artificial Intelligence & Machine Learning Online	MBA in Artificial Intelligence & Machine Learning Online
BCA Data Analytics Online	MCA in Machine Learning Online
B.Tech in CSE (AI & ML)	MCA in Artificial Intelligence & Machine Learning Online
Diploma in Artificial Intelligence & Machine Learning Online	Executive Postgraduate Program In AI & ML Online
	PG Diploma In Data Science Online
	PG Certification Course in AI & ML Online
	Job-guaranteed Certification Course in Machine Learning Online
	Executive PG Certificate in Machine Learning & Deep Learning Online
	Executive PG Certificate in Deep Learning & NLP Online
	PG Diploma in Machine Learning Online

The syllabus of a machine learning course is tailored to meet the dual needs of learning–having strong foundational bases and developing hands-on skills to run ML technologies and develop models. Accordingly, the curricular structure, course pedagogy, syllabus contents, etc. are designed to ensure these learning outcomes in students enrolling for such courses.

Machine learning courses are now available to be pursued in both the on-campus regular mode and full-time online learning (OL) mode. The syllabus and course curriculum of these online ML programs are similar and equivalent to regular courses, and include simulation and lab facilities for practical learning and skill-building as well.

As the UGC-DEB has granted equivalent status to online programs as regular degrees (provided they have been pursued from duly accredited institutes/platforms) the course curriculum of online ML programs is also tailored to ensure equivalent rigor and depth of learning as the regular courses.

Syllabus in Machine Learning & Artificial IntelligenceDegree Courses

There are several highly popular degrees in the machine learning specialization including those like an MCA, an MBA, a BCA, a B.Tech, an M.Tech, a B.Sc, and so on.

Herein, we have outlined the course curriculum and subjects commonly covered in the major undergraduate and postgraduate degree courses in ML. Undergraduate Degree Syllabus & Subjects in Machine Learning and Artificial Intelligence.

 Find more details about the course structure, the syllabus, and important subjects in undergraduate degree courses like BCA, B.Sc, and B.Tech in the specialization of machine learning, etc.

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

A BCA is a technological course in computer applications having a duration of 3 years. The course structure comprises 6 semesters (each approximately lasting 6 months) wherein the fundamental concepts of AI and ML are covered in the first two semesters.

Through semesters 3-6, the students are taught about the nuances of artificial intelligence and machine learning through lectures and relevant practicum sessions and seminars. Hands-on learning is facilitated through regular projects and assignments.

The commonly covered ML subjects in this course include data structures and algorithms, programming in C, applied mathematics for machine learning, statistics for ML, and so on. Click Here | BCA Online Program!

Further details about the course subjects of machine learning in a BCA degree are provided below :

Course subjects of machine learning
Introduction to Programming and C	Database Management System
Foundations of Applied Mathematics	Data Structures and Algorithms
C# and .NET Framework	Object Oriented Programming using Java
Designing human-computer interfaces	Numerical Analyses and Statistical Techniques
Internet Technologies	Fundamentals of AI
Web Applications	Relational Database Management System
Web Applications	Machine Learning Tools
AI Using Azure	Elements of Mathematics

2) BCA in Machine Learning (ML) & Data Science 

Another popular ML specialization available in BCA is the dual specialization in machine learning and data science. This course brings a course of subjects including a blend of fundamentals of both ML and data science principles, such as mathematics and statistics, big data analytics, systems analysis, programming foundations for both the domains, data structures, and algorithms, fundamentals of AI, data ethics and privacy and so on. This course is also divided into 6 semesters across 3 years, during which several theoretical foundations, as well as hands-on skill-building, are built-in for students.

Further details about the course subjects and syllabus are provided below :

Programming Fundamentals	Machine Learning
Deep Learning	Mathematics for Data Science
Statistical Foundations for Data Science	Object Oriented Programming Using C++
Programming Foundation	Data Structures & Algorithms
System Analysis & Design	Operating System & Shell Programming
AI for Business	Fundamentals of AI
AI for Robotics	Reinforcement Learning
Data Handling and Visualization	Machine Learning
Big Data Technologies	Data Ethics & Privacy
Computer Vision	Natural Language Processing
Deep Generative Models	AI for Industry Applications
Time Series Analysis	AI in Research & Development

3) B.Tech in CSE (AI & ML)

A B.Tech in Computer Science Engineering (CSE) is one of the most popular specialization domains of engineering course in India. While most institutes provide an overview of courses in computer science engineering in the CSE specialization, some institutes provide the course with a specific focus on artificial intelligence and machine learning.

A B.Tech in CSE (AI & ML) is a 4-year course divided into 8 semesters, with the first two semesters focusing on the foundations of engineering, followed by a detailed coverage of topics and subjects related to artificial intelligence and machine learning.

A characteristic feature of a B.Tech degree is that it lays a strong emphasis on practical skill-building and working knowledge of ML needed to sustain in the IT industry. The commonly included subjects related to AI and ML in a B.Tech course include Python programming, algebra, applications and use cases of machine learning, data structures and algorithms, probability and random processes, reinforcement learning, etc. Click Here | BTech After Diploma!

The details of the course syllabus are provided below for reference :

Linear Algebra	Introduction to Python Programming
Statistics for Data Science	Software Tools for AI & ML
Application and Use Cases of Machine Learning	Probability and Random Processes
Communication Skills	Data Structures and Algorithms
Supervised Machine Learning	Reinforcement Learning
Optimization Techniques for Machine Learning	Data Visualization
AI Ethics	Database Concepts for Data Science
Deep Learning	Natural Language Processing
Generative Adversarial Networks	Data Reprocessing
AI Ethics	Programming in C

4) BCA in Data Science & Big Data Analytics

A BCA in data science and big data analytics, while not directly pertaining to machine learning, is a field closely related to machine learning, as the underlying principles of machine learning and data science both rely on mathematical and statistical principles and foundations for systematic data analysis and insight development.

The course covers a range of subjects including database management, data structures, Java, Python programming, foundations of artificial intelligence, information system management, and their security, system programming, and so on through the 6 semesters of the degree. The focus on hands-on skill building is also quite high in this course, considering it is a technical course.

More relevant details about the subjects and courses in a BCA program in data science and big data analytics are provided below :

Introduction to IT & Programming in C	Database Management System
Data Structures	C Programming
Internet Technologies	Software Engineering
Object-Oriented Programming in C	Basics of Cloud Using Azure
Introduction to Data	Java
Fundamentals of AI	Computer System Architecture
Programming in .NET Using C++	Python Programming
Machine Learning	Data Visualisation in Business Intelligence
Security of Information System	Introduction to Management Information System (MIS)
Relational Database Management System (RDBMS)	System Programming

5) B.Sc in Data Science & AI

A Bachelor of Science in Artificial Intelligence and Data Science is another undergraduate course relevant to machine learning that includes courses related to machine learning, principles of AI, ML and data science, deep learning, advanced data analytics, NLP, applications of AI, time series analysis, and so on.

The course structure comprises 6 semesters spanned across 3 years of the course, integrating several pedagogies to promote skill-based and industry-relevant learning for professional competency. This course curriculum is designed to hone the skills of students in not only data science and artificial intelligence but also machine learning, deep learning, and applications of AI in various industries, thus promising a holistic perspective development in the field. Click Here | B.Sc Online Course!

Find more details about the course subjects for B.Sc in data science and AI provided below :

Machine Learning	Reinforcement Learning
Cloud Computing	Natural Language Processing
Deep Learning	Data Ethics & Privacy
Advanced-Data Analytics	AI in Business
IoT and Data Science	Deep Generative Models
Time Series Analysis	AI & Ethics
AI in Research & Development	AI for Robotics
Big Data Technologies	Computer Vision

Postgraduate Degree Syllabus & Subjects in Machine Learning and Artificial Intelligence

Course details including course structure, syllabus, and important conceptual areas for various postgraduate degree courses in machine learning have been elaborated upon below. While the major subjects and conceptual arenas of the specializations of these courses are often similar to those in undergraduate courses, the major difference lies in the degree of depth and advanced level in which they are explored at the PG level through both theoretical concept-building and practical skill-building.

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

A Masters in Business Administration (MBA) in artificial intelligence and machine learning is a two-year degree course consisting of 4 semesters that guide the student through the foundations of management as well as management in the specific context of AI and ML technologies. Thus, this course emphasizes the nuanced aspects of using AI and ML in managerial operations and functions.

The prominent subjects in this course include technology transformation in business, business analytics, NLP, deep learning, applications of AI in business, data visualization, machine learning, neural networks, reinforcement learning, and so on.

The common learning provisions to facilitate hands-on learning in an MBA (AI & ML) include seminars and industry interactions, hands-on skill-building activities, case studies, practicum papers, and so on. Generally, the course curriculum is designed to provide a foundational overview of management in the first two semesters and cover the specialization courses of AI and ML in the third and fourth semesters. Click Here | Online MBA Program!

Find further details about the MBA in AI and ML given here :

Business Communications	Organizational Behaviour
Accounting for Managers	Technology Transformation for Business
Business Analytics	Managerial Economics-Micro and Macro
Natural Language Processing	Deep Learning
Introduction to Machine Learning	Applications of AI in Business
Advanced Machine Learning	Artificial Intelligence and its Applications
Data Visualization	Machine Learning
Performing Analytics	R-Programming for Data Analytics & Data Visualisation
Neural Networks & Machine Learning Algorithms	Foundations of Computer Systems

2) MCA in Machine Learning  (ML)

An MCA in machine learning is a 2-year PG degree that is available to be pursued in the offline regular mode as well as in the fully online learning mode in India. It is a course designed to equip students with advanced skills in computer applications and IT, with a specialized focus on machine learning technologies (as covered in the third and fourth semesters).

This course covers in-depth the major functional areas of machine learning including those like deep learning, neural networks, natural language processing, time series analysis, reinforcement learning, data structures and algorithms, data visualization, programming in languages like Python, C++, and so on. Click Here | Online MCA Program!

Find details about the major subjects covered in an MCA in machine learning provided below :

Introduction to Machine Learning	Reinforcement Learning
Deep Learning	Neural Networks
Time Series Analysis	Natural Language Processing
Data Structures & Algorithms	Applied Mathematics for ML
Applications of Machine Learning	Unsupervised and Supervised Machine Learning
Complex Network Analysis	Data Visualization
Programming in Python	Programming Using C++

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

An MCA in AI and ML is a dual specialization course that covers several fundamental areas of these two closely related fields of computer science. The course is structured into 4 semesters across 2 years covering domains ranging from foundations of computer applications like computer systems, business analytics and visualization, software development, shell programming, etc.

to the specialization courses in AI and ML including data structures and algorithms, data visualization, reinforcement learning, AI for robotics, applications of ML, NLP, complex network analysis, predictive analytics, etc.

More details about the syllabus and subjects in this course are provided below :

Foundations of Computer Systems	Data Structures and Algorithms
Deep Learning for AI	Data Visualization
Data Engineering for AI	Business Analytics and Visualization
Foundations of Machine Learning	Mathematical Foundations for Computer Applications
Artificial Intelligence for Robotics	Reinforcement Learning
Cloud Computing	Applications of Machine Learning
Complex Network Analysis	Natural Language Processing
Representation Learning	Applied Predictive Analytics
Advanced Software Engineering Principles	Network Security

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

An M.Tech in AI and ML is a 2-year postgraduate degree in engineering that is centered on the coverage of advanced concepts of artificial intelligence and machine learning through the 4 semesters into which the course is divided. This course is often divided into core subject papers and elective papers, the latter of which includes a host of specialization-relevant courses from which a student can select courses they wish to pursue.

Commonly offered subjects in an M.Tech program in AI & ML include deep neural networks, mathematical foundations of machine learning, deep reinforcement learning, advanced deep learning, NLP and its applications, ML operations (MLOps), data mining and data management, graph neural networks and so on. Click Here | M.Tech for Working Professionals!

Find further details provided below :

Mathematical Foundations for Machine Learning	Deep Neural Networks
Machine Learning	Deep Reinforcement Learning
Advanced Deep learning	Introduction to Statistical Methods
ML System Optimization	Graph Neural Networks
Natural Language Processing (NLP)	Fair, Accountable, Transparent Machine Learning
NLP Applications	Information Retrieval
MLOps	Computer Vision
Advanced-Data Mining AI and ML Techniques for Cyber Security	Data Management for Machine Learning
Probabilistic Graphical Models	Video Analytics

Syllabus in Machine Learning & Artificial Intelligence: Diploma Courses 

In addition to degree courses in machine learning, there are also several diploma programs offered in the subject area of machine learning to meet the learning needs of students who want to pursue a relatively shorter course equipping them with the central skill areas and concepts of ML.

Diploma courses, whether at the UG, PG, or executive levels, are designed to meet this academic need, as they cover important domains of ML including those like probability and statistics for data science and ML, ML algorithms, NLP, decision modeling, data visualization, data analytics, etc. within an approximate period of 10 to 18 months. Click Here | Online Diploma Programs!

Find a few of the major subjects and papers covered in diploma programs of machine learning listed here :

Probability & Statistics for Data Science	Data Visualisation
Digital & Social Media Analytics	Decision Modelling
Methods & Algorithms in Machine Learning	AI & Decision Sciences
Economics for Analytics	Programming in Python
Behavior Science & Analytics	Natural Language Processing

Syllabus in Machine Learning & Artificial Intelligence: Certificate Courses

In addition to degrees and diplomas, certifications in machine learning are a beneficial educational option to take up when you want to upskill and increase proficiency in a specific subdomain of artificial intelligence and machine learning. Depending upon the duration of the certificate course, the course program might be covered in one or two semesters.

The commonly covered subjects in such certificate programs include types of machine learning, applications of AI and ML, data mining, big data analytics, deep learning, NLP, model deployment in machine learning, computer vision, regression, clustering for machine learning, programming and development using R, C++, Python and so on.

Relevant subjects and courses of machine learning certificate programs have been enlisted here :

AI & ML: An Imperative for Digital Business	Introduction to Deep Learning Algorithms
Unsupervised Machine Learning	Foundations of Reinforcement Learning
Practising Machine Learning	Applications of AI & ML
Introduction to Artificial Intelligence	Data Mining & Big Data Analytics
Natural Language Processing	Feature Engineering & Selection
Model Deployment & Selection	Computer Vision
Understanding Supervised Learning	Machine Learning Applications
Data Mining: Decision Trees & Random Forest	Linear & Logistic Regression
Clustering Techniques of Data Mining	Data Visualisation
Data Manipulation Using R	Data Analytics Foundation

Recommended Books & Course Materials in AI & ML

Provided below are a few of the important books for reference and study materials for machine learning and related domains like artificial intelligence, deep learning, programming and development, etc.

Books	Author(s)	Publisher
Python Machine Learning	S. Raschka	Packt Publishing Ltd.
Artificial Intelligence: A Modern Approach	S. Russell, P. Norvig	Berkeley Edu.
Deep Learning	I. Goodfellow, Y. Bengio, A. Courville	MIT Press
Fundamentals of Data Structures in C	E. Horowitz, S. Sahni, S. A. Freed	Universities Press
Machine Learning Yearning	A. NG	Andrew NG ©
Artificial Intelligence and Machine Learning	V. Chandra S. S., A. Hareendran S.	PHI Learning
Advanced Programming in the UNIX Environment	W.R. Stevens	Pearson Education
Core Python Programming	Wesley J. Chun	Pearson Education

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Conclusion

As can be seen from the blog, the course syllabi of various degree, diploma, and certificate programs in machine learning cover a range of foundational subjects of the discipline and emphasize the development of practical and hands-on skill development. Both online courses and on-campus programs help students develop a strong skill set necessary to thrive in the ever-evolving ITES industry through the curriculum. Such upskilling courses can set the stepping stone in enhancing one's career in machine learning.