AKTU MCA · ML SPECIALIZATION

MCA · ML

MCA with Machine Learning

A two-year AKTU-approved postgraduate program building expertise in ML algorithms, model deployment, MLOps, and intelligent systems with large datasets.

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Duration2 Years · 4 Semesters
SpecializationML · Value-Added
ApprovedAICTE, New Delhi
AffiliatedAKTU, Lucknow

ABOUT THE PROGRAMME

An MCA that turns ML algorithms into intelligent systems.

MCA Program with Machine Learning is designed to provide in-depth knowledge and practical experience in the field of machine learning — a subset of artificial intelligence. This program typically covers various ML algorithms, techniques, and applications and helps students gain expertise in building intelligent systems using large datasets.

The Master of Computer Applications (MCA) course gives in-depth knowledge about how to develop efficient computer applications and software. It is a two-year professional postgraduate program approved by AKTU. The program is a blend of theoretical and practical training. The institute employs lectures, presentations, seminars, workshops, laboratory sessions, and project work to develop conceptual, analytical, and decision-making skills. Continuous evaluation — assignments, presentations, software experimentation, tests, quizzes, midterm and semester-end examinations — maintains the highest academic standard across theory and practice. Project implementation covers requirement gathering, system analysis, design, and a final presentation to expert evaluators.

Robot hand holding ML hologram representing machine learning

VALUE-ADDED MODULES (AKTU)

Nine modules and five advanced topics — the ML engineer's toolkit.

Value-Added Modules

Introduction to Machine Learning
Data Preprocessing and Feature Engineering
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Natural Language Processing (NLP)
Model Evaluation and Selection
Big Data and Scalable Machine Learning
AI Ethics and Fairness

Advanced Topics

Generative Models
Transfer Learning
Time Series Analysis
AI in Business
Automated Machine Learning (AutoML)

COURSE STRUCTURE

Four semesters. Core foundations, then electives.

Semester I

Subject Code	Subject Name
BMC101	Fundamental of Computers & Emerging Technologies
BMC102	Problem Solving using C
BMC103	Principles of Management & Communication
BMC104	Discrete Mathematics
BMC105	Computer Organization & Architecture
BMC151	Problem Solving using C (Lab)
BMC152	Computer Organization & Architecture (Lab)
BMC153	Professional Communication (Lab)
BMC106	Cyber Security*

Semester II

Subject Code	Subject Name
BMC201	Web Technology
BMC202	Object Oriented Programming
BMC203	Operating Systems
BMC204	Database Management Systems
BMC205	Data Structures & Analysis of Algorithms
BMC251	Web Technology (Lab)
BMC252	Object Oriented Programming (Lab)
BMC253	DBMS (Lab)
BMC254	Data Structures & Analysis of Algorithms (Lab)
BVA251	Sports and Yoga**

Semester III

Subject Code	Subject Name
KCA301	Artificial Intelligence
KCA302	Software Engineering
KCA303	Computer Network
—	Elective – 1
—	Elective – 2
KCA351	Artificial Intelligence Lab
KCA352	Software Engineering Lab
KCA353	Mini Project**

Elective 1

Subject Code	Subject Name
KCA011	Cryptography & Network Security
KCA012	Data Warehousing & Data Mining
KCA013	Software Project Management
KCA014	Cloud Computing
KCA015	Compiler Design

Elective 2

Subject Code	Subject Name
KCA021	Web Technology
KCA022	Big Data
KCA023	Simulation & Modeling
KCA024	Software Testing & Quality Assurance
KCA025	Digital Image Processing

Semester IV

Subject Code	Subject Name
—	Elective – 3
—	Elective – 4
—	Elective – 5
KCA451	Project

Elective 3

Subject Code	Subject Name
KCA031	Privacy & Security in Online Social Media
KCA032	Soft Computing
KCA033	Pattern Recognition
KCA034	Data Analytics
KCA035	Software Quality Engineering

Elective 4

Subject Code	Subject Name
KCA041	Blockchain Architecture
KCA042	Neural Network
KCA043	Internet of Things
KCA044	Modern Application Development
KCA045	Distributed Database Systems

Elective 5

Subject Code	Subject Name
KCA051	Mobile Computing
KCA052	Computer Graphics and Animation
KCA053	Natural Language Processing
KCA054	Machine Learning
KCA055	Quantum Computing

CAREER DEVELOPMENT & PLACEMENT CELL

The CDPC keeps corporates close — and students ready.

IAMR has been in the forefront of activities by bringing corporates and companies closer to the campus, and encouraging them to establish facilities that cater to the needs of students.

The Career Development & Placement Cell enhances employability through specialized training in aptitude, analytical, language, technical, and business skills — plus online mock tests. Sessions are run by in-house faculty and professional trainers from the corporate world. The CDPC also organizes internship sessions before students join their respective industry — a preliminary exposure to what comes next.

ELIGIBILITY & DURATION

Two years, four semesters, blended theory + practice.

Eligibility

Candidates must have passed a bachelor's degree of minimum three years duration from any recognized university with Mathematics as a subject at 10+2 level or graduate level. The candidate must have passed without grace marks with an aggregate of minimum 50% marks (45% for SC/ST).

A candidate shall have passed the qualifying examination of B.C.A. / B.Sc. (CS) / B.Sc. (IT) / B.E.(CSE) / B.Tech.(CSE) / B.E.(IT) / B.Tech.(IT) — or any equivalent graduation (B.E., B.Tech., B.Sc., B.Com., B.A., B.Voc.) preferably with Mathematics, Business Mathematics, or Statistics at 10+2 or graduation level.

Duration

Two years across four semesters. Semesters 2, 3, and 4 include practical sessions. The programme combines practical and theoretical knowledge — students gain a deep understanding of software development, programming languages, database management, and computer networks.

Practical and theoretical training
Industrial training is a mandatory part
Best skill set for students with a knack for computer applications