Bachelor in Computer Application (BCA)
Specialization: Artificial Intelligence
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Course Highlights
Introduction
The BCA in Artificial Intelligence is a 3-year undergraduate program designed to blend foundational computer application knowledge with the emerging power of AI. This program empowers students with strong programming skills, a deep understanding of AI and machine learning techniques, and practical exposure to real-world problem-solving. It prepares graduates to build intelligent systems, develop predictive models, and contribute to the growing demand for AI-powered applications across industries.
Eligibility
Passed 10+2 examination preferably Mathematics/Statistics / Business Mathematics as one of the subject.
OR
A pass in diploma in Commercial Practice or equivalent. (for students having no Mathematics background has to undergo a compulsory bridge course on Mathematics & related Computer Subject framed by SSU).
Note: Physics and Mathematics are mandatory subjects at the 10+2 level.
Duration
4 Years Full-Time
Tuition Fees
Rs. 50,000 per Semester
*Fees such as Admission, Caution Money, Examination, Hostel, and Transport fees are extra.
Program Details
Programming Fundamentals
Master programming languages such as Python, C++ , and Java with a strong focus on logic building
Mathematics for AI
Study linear algebra, probability, and statistics to form the mathematical foundation for AI models
Data Structures and Algorithms
Learn efficient data handling, searching, and optimization techniques.
Artificial Intelligence
Understand search algorithms, knowledge representation, intelligent agents, and expert systems
Machine Learning
Supervised and unsupervised learning, decision trees, SVMs, clustering, and model evaluation.
Deep Learning
Neural networks, CNNs, RNNs, and frameworks like TensorFlow and PyTorch.
Natural Language Processing (NLP)
Text mining, sentiment analysis, and language modeling
Computer Vision
Image processing, object detection, face recognition, and video analysis using AI
Big Data Analytics
Handling and analyzing large datasets using tools like Hadoop, Spark, and Python libraries
Cloud Computing for AI
Deploying models on cloud platforms such as AWS, Azure, or Google Cloud
Ethics in AI
Study the social, ethical, and legal implications of AI technologies
Capstone Project
End-to-end AI system development involving real-world datasets and industry tools
Program Outcome
Apply Programming Skills
Use programming languages to develop AI-powered applications and services
Understand AI Techniques
Apply machine learning, deep learning, and data mining techniques to solve practical problems
Design Intelligent Systems
Create smart systems that can learn, adapt, and make autonomous decisions
Data-Driven Decision Making
Use AI and analytics tools to extract meaningful insights from complex datasets
Deploy Scalable Solutions
Implement and deploy AI models on cloud or edge environments with performance optimization
Ethical Computing
Address ethical concerns related to bias, transparency, and accountability in AI
Research and Innovation
Contribute to research, innovation, and development of cutting-edge AI technologies
Lifelong Learning
Stay updated with evolving tools, technologies, and frameworks in AI and software
Placement Opportunities
Software Development
Roles: Software Engineer, Backend Developer, Full Stack Developer, App Developer
Web and Mobile Application Development
Roles: Web Developer, Frontend
Engineer, Android/iOS Developer
Database and System Administration
Roles: Database Administrator (DBA),
System Administrator
Cloud Computing and DevOps
Roles: Cloud Engineer, DevOps
Engineer, Site Reliability Engineer
Cybersecurity
Roles: Security Analyst, Penetration
Tester, SOC Analyst
Data Science and Analytics
Roles: Data Analyst, Business Analyst
(for students who upskill in this
domain)
Artificial Intelligence and Machine Learning
Roles: AI Engineer, ML Engineer (with
specialization or upskilling)
Game Development and AR/VR
Roles: Game Developer, Graphics
Programmer, AR/VR Developer
Government & Public Sector
Roles: Technical Officer, Network
Engineer, Software Developer
Higher Studies and Research
Opportunities for M.Tech, MS, MBA, or Ph.D. in India or abroad
Entrepreneurship and Startups
Launching own tech products,
services, or freelancing through
platforms like Fiverr and Upwork
Teaching and Academics
Lecturer or Assistant Professor roles
in engineering colleges after
postgraduation
Lab List
1.Programming Lab
C, C++, Python, Java: Basic and advanced coding skills.
2.Data Structures Lab
Implementation of stacks, queues, trees, graphs, sorting, and searching algorithms.
3.Database Management Systems (DBMS) Lab
SQL, PL/SQL, database design, normalization, triggers, and transactions
4.Operating Systems Lab
Process management, scheduling algorithms, memory management, file systems
5.Computer Networks Lab
Socket programming, protocol simulation, packet tracing (e.g., Wireshark, Cisco Packet Tracer)
6.Software Engineering Lab
Software design, UML diagrams, testing strategies, version control tools like Git
7.Object-Oriented Programming Lab
Java/C++: Concepts like inheritance, polymorphism, interfaces, and GUI apps
8.Web Technologies Lab
HTML, CSS, JavaScript, PHP , Node.js, basic web app development
9.Compiler Design Lab
Lexical analyzer, parser, intermediate code generation using Lex & Yacc
10.Artificial Intelligence Lab
Search algorithms, logic programming, basic ML models in Python
11.Cybersecurity Lab
Kali Linux, penetration testing tools, basic cryptography, and web app security
12.Cloud Computing Lab
AWS/Azure basics, virtualization using VirtualBox/Docker, deployment of apps
13.Mobile App Development Lab
Android Studio or Flutter for building mobile apps
14.Machine Learning Lab (Optional/Advanced)
Scikit-learn, TensorFlow, or PyTorch for supervised/unsupervised learning
15.Project Lab / Capstone Lab
Final year project work with version control, documentation, and testing
Where Talent Meets Opportunity:
Our Graduates Are Building Futures with Leading Companies
