MCA at
Sharda University
An advanced MCA program with specializations in Software Engineering, AI, Data Science, Cloud Computing, MLOps, Generative AI and Full-Stack Development - building industry-ready tech leaders.
Program Overview
Master Technology.
Lead Innovation.
Program Snapshot
Advanced engineering from Day 1 - systems, AI/ML and cloud, on real-world datasets.
An industry-recognised MCA degree awaits you.
A degree from Sharda Online is recognised globally, and is equivalent to an on-campus program from Sharda University — the same certificate, the same grade card, the same UGC-entitled recognition.
Curriculum
MCA 4-Semester Curriculum
Select a specialisation to view its tailored semester-by-semester curriculum.
Year 1 · Computing Foundations & Core Development
Sem 1 & Sem 2 · 3 projects
- Mathematical Foundations for Computing
- Problem Solving & Computational Thinking (C++)
- Operating System & Unix Shell Programming
- Computer Architecture and Organization
- Data Communication and Computer Networks
- Introduction to Computers & Technology
- Foundations of AI
- Data Structures & Algorithms Fundamentals (C++)
- Database Management Systems
- Software Engineering Fundamentals
- Java Programming Fundamentals
- Logical Skills Building & Soft Skills
- AI Ethics & Responsible Technology
Year 2 · Specialisation Capstone & Industry Projects
Sem 3 & Sem 4 · 3 projects
- Application Programming in Python
- Design & Analysis of Algorithms
- Statistical Methods in Decision Making
- Data Visualization
Specialisations
Choose one learning path
- Big Data Analytics
- Technology Product Management & Agile Delivery (Scrum)
- Research Project / Industry / Open-Dataset Problem
- Artificial Intelligence and Machine Learning
- Neural Networks and Deep Learning
Specialisations
Choose one learning path
- Time Series Analytics
Year 2 Outcomes
Portfolio Ready
P1Federated Learning Privacy Simulator
PySyft / Flower · PyTorch · Python · Matplotlib · FastAPI
P2Autonomous Financial Portfolio Agent
Stable-Baselines3 · FinRL · Pandas · Plotly · FastAPI · PostgreSQL
P3Real-Time Industrial IoT Anomaly Detector
Apache Kafka · TensorFlow · InfluxDB · Grafana · Python · Docker
Year 1 · Computing Foundations & Core Development
Sem 1 & Sem 2 · 3 projects
- Mathematical Foundations for Computing
- Problem Solving & Computational Thinking (C++)
- Operating System & Unix Shell Programming
- Computer Architecture and Organization
- Data Communication and Computer Networks
- Introduction to Computers & Technology
- Foundations of AI
- Data Structures & Algorithms Fundamentals (C++)
- Database Management Systems
- Software Engineering Fundamentals
- Java Programming Fundamentals
- Logical Skills Building & Soft Skills
- AI Ethics & Responsible Technology
Year 2 · Specialisation Capstone & Industry Projects
Sem 3 & Sem 4 · 3 projects
- Application Programming in Python
- Design & Analysis of Algorithms
- Statistical Methods in Decision Making
- Data Visualization
Specialisations
Choose one learning path
- Big Data Analytics
- Technology Product Management & Agile Delivery (Scrum)
- Research Project / Industry / Open-Dataset Problem
- Artificial Intelligence and Machine Learning
- Neural Networks and Deep Learning
Specialisations
Choose one learning path
- Time Series Analytics
Year 2 Outcomes
Portfolio ReadyP1Federated Learning Privacy Simulator
PySyft / Flower · PyTorch · Python · Matplotlib · FastAPI
P2Autonomous Financial Portfolio Agent
Stable-Baselines3 · FinRL · Pandas · Plotly · FastAPI · PostgreSQL
P3Real-Time Industrial IoT Anomaly Detector
Apache Kafka · TensorFlow · InfluxDB · Grafana · Python · Docker
MCA in Data Science — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- Statistical Methods in Decision Making — 4 credits
- Introduction to Data Science — 4 credits
- AI for Data Scientists — 4 credits (AI track)
- Technology and Business Analytics — 4 credits (Data Science track)
- Data Visualization — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- Artificial Intelligence and Machine Learning — 4 credits
- SQL for Data Science — 4 credits
- AI-Driven Data Science — 4 credits (AI track)
- Time Series Analytics — 4 credits (Data Science track)
- Real-Time Data Processing — 4 credits (Technology track)
MCA in AI & Data Science — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- Applied Statistical Methods — 4 credits
- AI + DS Integrated Fundamentals — 4 credits
- Data Visualization — 4 credits (AI track)
- BI for Data Science — 4 credits (Data Science track)
- AI-Data Platforms Introduction — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- Artificial Intelligence and Machine Learning — 4 credits
- Neural Networks and Deep Learning — 4 credits
- AI-Driven Data Science — 4 credits (AI track)
- NLP for Data Science — 4 credits (Data Science track)
- Predictive Analytics using Machine Learning — 4 credits (Technology track)
MCA in Software Engineering — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- AI Software Architecture — 4 credits
- AI in Software Testing & QA — 4 credits
- ML for Software Engineers — 4 credits (AI track)
- Software Data Analytics — 4 credits (Data Science track)
- Technology and Business Analytics — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- Data Pipeline for Software Systems — 4 credits
- Internet of Things — 4 credits
- DevOps Data Engineering — 4 credits (AI track)
- ML for Software Engineers — 4 credits (Data Science track)
- C# with ASP.NET — 4 credits (Technology track)
MCA in Cyber Security — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- Cryptography and Network Security — 4 credits
- AI in Cyber Security — 4 credits
- Object Oriented Modelling and Design Pattern — 4 credits (AI track)
- Network Traffic Data Analysis — 4 credits (Data Science track)
- Cyber Threat Intelligence — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- Security Intelligence & Analytics Systems — 4 credits
- Cyber Security: Concept and Practices — 4 credits
- AI-Powered Penetration Testing — 4 credits (AI track)
- Cloud Infrastructure and Service — 4 credits (Data Science track)
- Internet of Things — 4 credits (Technology track)
MCA in Cloud Computing — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- Cloud Fundamentals — 4 credits
- Cloud Infrastructure & Services — 4 credits
- MLOps on Cloud Platforms — 4 credits (AI track)
- Fundamentals of Cloud Security — 4 credits (Data Science track)
- Cloud Service Management — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- AI Deployment on Cloud — 4 credits
- Serverless AI Applications — 4 credits
- Real-Time Cloud Analytics — 4 credits (AI track)
- Cloud DevOps & Automation — 4 credits (Data Science track)
- Cloud Data Science Platforms — 4 credits (Technology track)
MCA in Generative AI & LLMs — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- LLM Engineering Fundamentals — 4 credits
- Prompt Engineering & Fine-Tuning — 4 credits
- Generative AI Analytics Foundations — 4 credits (AI track)
- Generative AI Frameworks & Deployment Tools — 4 credits (Data Science track)
- Multimodal GenAI Applications — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- AI-Generated Insights & Reporting — 4 credits
- Agentic AI Development — 4 credits
- Advanced LLM Engineering — 4 credits (AI track)
- Generative AI Data Analytics — 4 credits (Data Science track)
- LLM Analytics Applications — 4 credits (Technology track)
MCA in MLOps & AI Engineering — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- Data Pipeline for ML Systems — 4 credits
- MLOps Analytics Foundations — 4 credits
- AI DevOps Fundamentals — 4 credits (AI track)
- Containerisation for ML Workloads — 4 credits (Data Science track)
- ML Deployment Automation — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- Kubernetes for ML — 4 credits
- Model Analytics & Reporting — 4 credits
- AI Deployment on Cloud — 4 credits (AI track)
- MLOps Analytics Platform — 4 credits (Data Science track)
- ML Performance Analytics — 4 credits (Technology track)
MCA in Full-Stack Development — full curriculum
Semester 1 · Computing Foundations — 19 credits
- Mathematical Foundations for Computing — 3 credits
- Problem Solving & Computational Thinking (C++) — 3 credits
- Operating System & Unix Shell Programming — 3 credits
- Computer Architecture and Organization — 4 credits
- Data Communication and Computer Networks — 2 credits
- Introduction to Computers & Technology — 2 credits
- Foundations of AI — 2 credits
Semester 2 · Core Development — 18 credits
- Data Structures & Algorithms Fundamentals (C++) — 4 credits
- Database Management Systems — 4 credits
- Software Engineering Fundamentals — 2 credits
- Java Programming Fundamentals — 4 credits
- Logical Skills Building & Soft Skills — 2 credits
- AI Ethics & Responsible Technology — 2 credits
Semester 3 · Specialisation & Track — 20 credits
- Application Programming in Python — 4 credits
- Design & Analysis of Algorithms — 4 credits
- Frontend Technologies & React — 4 credits
- Backend Engineering & Node.js — 4 credits
- AI in Web Applications — 4 credits (AI track)
- Web Data Analytics — 4 credits (Data Science track)
- Modern Full-Stack Frameworks — 4 credits (Technology track)
Semester 4 · Capstone & Advanced Track — 23 credits
- Technology Product Management & Agile Delivery (Scrum) — 3 credits
- Research Project / Industry / Open-Dataset Problem — 8 credits
- Full-Stack Data Science Applications — 4 credits
- DevOps for Full-Stack — 4 credits
- Analytics Dashboard Development — 4 credits (AI track)
- Cloud Deployment Strategies — 4 credits (Data Science track)
- Microservices Architecture — 4 credits (Technology track)
Fees & Scholarships
Transparent Fee Structure
Everything you'll pay for the 2-year MCA program: tuition plus one-time registration and annual examination charges. No hidden costs.
Domestic Students
Indian Nationals
Total Program Fee
₹1,30,000
Per Semester
₹32,500
Per Year
₹65,000
No Cost EMI available on education loans availed by domestic students
International Students
Foreign Nationals
Total Program Fee
$2,000
Per Semester
$500
Per Year
$1,000
Registration & Exam Fees
One-time & annual charges
Domestic
· Indian Nationals
SAARC
· SAARC Countries
International
· Other Countries
Also Offered
Campus Immersion Fees
Same the 2-year MCA program, taught online through the week with scheduled visits to the Greater Noida campus. Domestic students only.
Curriculum and fees last reviewed:
Questions about the MCA curriculum
Learn with your A.I. Companions
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Web, mobile, lab and tutor - wired into a single learner profile. Pick any panel below to see what each part of the ecosystem does for you.
- 1.A function in C declares a return type, name, parameters and body.
- 2.Recursion = a function calling itself with a smaller problem until a base case.
- 3.The factorial example shows a base case (n==0) and a recursive case (n × f(n−1)).
- 4.Each recursive call adds a stack frame - beware of deep recursion.
- • A function declares return type + body
- • Recursion calls itself with smaller input
- • Always needs a base case
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Resume Builder
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What You'll Master
Technologies & Skills You'll Build
Programming
Full-Stack & APIs
Data & AI
Cloud & DevOps
Why Sharda MCA
Four Things That Set Us Apart
Specialisations
9 Specialisations
3 Sub-Tracks Each
Choose your specialization - Software Engineering, AI, Data Science, Cloud Computing, MLOps, Generative AI or Full-Stack Development. An MCA designed for tech leadership.
Curriculum
Capstone-First
Curriculum
By Year 2, your capstone is your portfolio - 8-credit industry project shipped on real datasets.
Labs
GPU Labs
from Day 1
Outcomes
90%+
Placement
Life at Sharda
Campus Immersion
Experience the perfect blend of traditional and digital learning environments.
Student Life
Events & Fests
Annual fests, tech conclaves, cultural events & departmental competitions.
Infrastructure
Tech Labs
State-of-the-art computing labs with industry-grade hardware & software.
Digital Campus
Smart Campus
Wi-Fi enabled campus with cloud infrastructure & digital learning tools.
Partnerships
Industry Connect
Regular industry interactions, company visits & collaborative projects.
Innovation
Hackathons
Annual coding contests, build sprints & innovation challenges.
Knowledge
Library
Digital & physical resources for research and learning.
Placement Highlights 2024
Our MCA graduates are placed at leading tech companies across India and globally with advanced technical training, system design preparation, and research projects.
600+ recruiters · ₹1.62 Cr highest package · 7,818 scholarships (₹44.79 Cr)
Career Outcomes
Tech Careers That Await You
Salary ranges based on 2024 placement data. Bar shows relative to highest MCA package (₹28 LPA).
What Our Graduates Say
Real accounts from MCA graduates now leading engineering teams at India's top tech companies.
The dual AI and Data Science sub-tracks gave me skills that most CS graduates from 4-year programs simply didn't have. TCS hired me directly into their AI Practice - that was the MCA opening doors a BTech usually does.
Akshat Gupta
MCA Full-Stack Development
AI Engineer · Class of 2024
We had actual penetration testing labs from the second year. That hands-on time is why I cleared three certifications before graduation and walked straight into an Information Security role at Wipro.
Meera Iyer
MCA Cyber Security
Security Analyst · Class of 2024
The build sprint culture here is real. My team shipped a working web app in Semester 2. It's now live on the Play Store. No other MCA program would have made that happen.
Rohan Singh
MCA Full-Stack Development
CEO · Class of 2023
The cloud computing specialization prepared me for AWS certification. I cleared all three levels before graduating and got placed in Infosys as a Cloud Solutions Architect with a 12 LPA package.
Priya Sharma
MCA Cloud Computing
Cloud Architect · Class of 2024
The MLOps & AI Engineering track at Sharda MCA was ahead of its time. We deployed real models on Kubernetes from day one. Now I'm running production ML pipelines at Flipkart that serve millions of users daily.
Arjun Malhotra
MCA MLOps & AI Engineering
ML Engineer · Class of 2023
The Generative AI specialization was a game-changer. I'm now working on LLM fine-tuning at a Silicon Valley startup, all thanks to the foundation I got in the MCA program.
Sneha Reddy
MCA Generative AI & LLMs
AI Researcher · Class of 2024
The Data Science track taught me to think beyond just coding - statistical modelling, business analytics, time-series forecasting. Understanding business metrics helped me land a Product Analyst role at Razorpay straight out of college.
Vikram Joshi
MCA Data Science
Product Analyst · Class of 2023
The Software Engineering track gave me real architecture chops - design patterns, microservices, IoT systems, CI/CD pipelines. By Year 2 I was leading a capstone team that shipped a production-grade fleet management platform. That portfolio is what landed me an SDE-2 role.
Ananya Patel
MCA Software Engineering
Software Engineer · Class of 2024
The dual AI and Data Science sub-tracks gave me skills that most CS graduates from 4-year programs simply didn't have. TCS hired me directly into their AI Practice - that was the MCA opening doors a BTech usually does.
Akshat Gupta
MCA Full-Stack Development
AI Engineer · Class of 2024
We had actual penetration testing labs from the second year. That hands-on time is why I cleared three certifications before graduation and walked straight into an Information Security role at Wipro.
Meera Iyer
MCA Cyber Security
Security Analyst · Class of 2024
The build sprint culture here is real. My team shipped a working web app in Semester 2. It's now live on the Play Store. No other MCA program would have made that happen.
Rohan Singh
MCA Full-Stack Development
CEO · Class of 2023
The cloud computing specialization prepared me for AWS certification. I cleared all three levels before graduating and got placed in Infosys as a Cloud Solutions Architect with a 12 LPA package.
Priya Sharma
MCA Cloud Computing
Cloud Architect · Class of 2024
The MLOps & AI Engineering track at Sharda MCA was ahead of its time. We deployed real models on Kubernetes from day one. Now I'm running production ML pipelines at Flipkart that serve millions of users daily.
Arjun Malhotra
MCA MLOps & AI Engineering
ML Engineer · Class of 2023
The Generative AI specialization was a game-changer. I'm now working on LLM fine-tuning at a Silicon Valley startup, all thanks to the foundation I got in the MCA program.
Sneha Reddy
MCA Generative AI & LLMs
AI Researcher · Class of 2024
The Data Science track taught me to think beyond just coding - statistical modelling, business analytics, time-series forecasting. Understanding business metrics helped me land a Product Analyst role at Razorpay straight out of college.
Vikram Joshi
MCA Data Science
Product Analyst · Class of 2023
The Software Engineering track gave me real architecture chops - design patterns, microservices, IoT systems, CI/CD pipelines. By Year 2 I was leading a capstone team that shipped a production-grade fleet management platform. That portfolio is what landed me an SDE-2 role.
Ananya Patel
MCA Software Engineering
Software Engineer · Class of 2024
Admissions
Simple 3-Step Admission
Follow our straightforward admission process designed to get you started as quickly as possible.
Step 01
Fill your application form
Complete your applicant profile and pick your programme, takes under 1 minutes.
Step 02
Pay your program fee
A simple, secure online payment, your seat is reserved instantly.
Step 03
Upload your documents
Paying logs you straight into your student portal, upload documents there to confirm admission.
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Tech Journey?
Join Sharda's MCA program and build the skills that top tech companies are looking for.