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BACHELOR-OF-COMPUTER-APPLICATION in Artificial Intelligence at Canara College
Dakshina Kannada, Karnataka
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About the Specialization
What is Artificial Intelligence at Canara College Dakshina Kannada?
This Bachelor of Computer Application program at Canara College, affiliated with Mangalore University, integrates Artificial Intelligence topics within its general curriculum rather than as a distinct, dedicated specialization throughout all semesters. It focuses on providing a strong foundation in core computer science, while offering specialized electives in AI, Machine Learning, Deep Learning, and Data Science in the later stages. This approach ensures graduates are well-rounded in IT fundamentals, with significant exposure to cutting-edge AI concepts, aligning with the evolving demands of the Indian tech industry.
Who Should Apply?
This program is ideal for 10+2 graduates with a keen interest in logical reasoning, problem-solving, and technology. It caters to individuals aspiring for entry-level roles in software development, data analysis, or IT support in India. Working professionals seeking to transition into the booming AI and data science sectors can also leverage the elective subjects to upskill. Students passionate about building intelligent systems and understanding data-driven decision-making will find this curriculum engaging and relevant.
Why Choose This Course?
Graduates of this program can expect to pursue diverse career paths within the Indian technology landscape, including Junior Software Developer, Data Analyst, AI/ML Trainee, and Web Developer. Entry-level salaries typically range from INR 2.5 LPA to 4.5 LPA, with significant growth potential into specialized AI roles. The comprehensive foundation also aids in pursuing higher education like MCA or specialized M.Tech programs, aligning with professional certifications in AI and data science platforms for career advancement.
Student Success Practices
Foundation Stage
Master Core Programming Logic- (Semester 1-2)
Dedicate significant time to understanding C and C++ fundamentals, data structures, and algorithms. Solve daily coding challenges on platforms like HackerRank and GeeksforGeeks to build a strong logical base, crucial for all subsequent computer science and AI concepts.
Tools & Resources
HackerRank, GeeksforGeeks, CodeChef, NPTEL videos on Data Structures
Career Connection
A strong grasp of programming and data structures is the bedrock for any software development or AI engineering role, directly impacting problem-solving abilities in technical interviews and project development.
Build a Foundational Project Portfolio- (Semester 1-2)
Start working on small, personal projects using the skills learned in early semesters, such as C-based applications or basic web pages. Document your code and processes on platforms like GitHub to showcase your practical abilities and initiative.
Tools & Resources
GitHub, Visual Studio Code, W3Schools for Web Dev basics
Career Connection
Early project experience differentiates candidates, demonstrating initiative and practical application of knowledge, which is highly valued by Indian recruiters for internships and entry-level positions.
Engage in Peer Learning & Discussion- (Semester 1-2)
Form study groups to discuss complex topics like Discrete Mathematics and Object-Oriented Programming concepts. Explaining concepts to others solidifies your understanding and improves communication skills, essential for collaborative IT environments.
Tools & Resources
Discord/WhatsApp groups, College library resources, Online forums like Stack Overflow
Career Connection
Enhances teamwork and communication, critical soft skills for successful careers in IT companies, and helps in collaborative project work often seen in the industry.
Intermediate Stage
Deep Dive into Database and Web Technologies- (Semester 3-4)
Focus on gaining hands-on expertise in SQL, Java, Python, and web development frameworks. Build more complex applications that integrate databases and front-end interfaces to solve real-world problems, utilizing platforms like MySQL and modern web frameworks.
Tools & Resources
MySQL/PostgreSQL, Eclipse/IntelliJ IDEA for Java, Django/Flask for Python web, MERN stack tutorials
Career Connection
These skills are fundamental for roles like Full-Stack Developer, Backend Developer, and Database Administrator, which are consistently in high demand across Indian IT firms and startups.
Explore Operating Systems and Networking Concepts- (Semester 3-4)
Thoroughly understand the principles of operating systems and computer networks. Participate in workshops or online courses related to Linux administration or network configuration to gain practical insights into system management and security.
Tools & Resources
Linux (Ubuntu/CentOS), Wireshark, Cisco Packet Tracer, Coursera/edX courses on Networking
Career Connection
Crucial for System Administrator, Network Engineer, and Cybersecurity roles. This foundational knowledge is also important for understanding how distributed AI systems function in real-world scenarios.
Initiate AI/ML Learning through Electives- (Semester 5)
Actively choose AI/ML related electives in the 5th semester and complement with self-paced online tutorials. Start building small models using Python libraries for tasks like image recognition or simple prediction to build an early practical portfolio.
Tools & Resources
Python (NumPy, Pandas, Scikit-learn), Kaggle for datasets and competitions, Google Colab, YouTube tutorials for ML
Career Connection
Prepares students for specialized AI/ML roles by building practical skills and a portfolio, making them competitive for internships and entry-level positions in the growing Indian AI market.
Advanced Stage
Undertake Specialization-Focused Projects- (Semester 5-6)
For the final year projects (Project Work I & II), choose topics strictly within Artificial Intelligence, Machine Learning, Deep Learning, or Data Science. Work on real-world datasets and present robust solutions, collaborating closely with faculty mentors.
Tools & Resources
TensorFlow/PyTorch, Jupyter Notebooks, AWS/GCP Free Tier for cloud deployment, Research papers on AI applications
Career Connection
High-quality, specialized projects are paramount for securing roles as AI Engineer, Data Scientist, or ML Engineer. They demonstrate advanced technical proficiency and problem-solving capabilities to potential employers.
Prepare for Placements and Higher Studies- (Semester 5-6)
Actively participate in campus placements, aptitude tests, and mock interviews. Simultaneously, explore options for MCA or specialized Master''''s programs, preparing for entrance exams like NIMCET if higher education is the goal, ensuring a clear post-graduation path.
Tools & Resources
Placement cell resources, Online aptitude platforms, LinkedIn for networking, GRE/GATE/NIMCET prep materials
Career Connection
Directly impacts securing immediate employment in reputable Indian tech companies or gaining admission to prestigious postgraduate programs, setting the foundation for long-term career growth.
Network and Attend Tech Events- (Semester 5-6)
Engage with industry professionals, alumni, and peers through tech conferences, webinars, and online communities. This builds a professional network and keeps you updated with the latest trends and innovations in AI and computer science.
Tools & Resources
LinkedIn, Meetup groups (local tech communities), Tech conferences (e.g., Google DevFest, Data Science Summits)
Career Connection
Networking opens doors to internship opportunities, mentorship, and potential job referrals, which are invaluable for career advancement in the competitive Indian IT sector.
Program Structure and Curriculum
Eligibility:
- Pass in PUC/10+2 or equivalent examination with Mathematics/Computer Science/Statistics/Business Mathematics/Accountancy as one of the subjects, as per Mangalore University norms.
Duration: 6 Semesters (3 years)
Credits: 120 credits (for the 3-year degree as per 20 credits/semester) Credits
Assessment: Internal: 40% for Theory, 50% for Practicals, External: 60% for Theory, 50% for Practicals
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BCA101 | Fundamentals of Computers | Core | 4 | Computer Basics and Generations, Input/Output Devices, Memory Systems, Software Concepts, Operating Systems Introduction |
| 21BCA102 | Programming in C | Core | 4 | C Language Fundamentals, Operators and Expressions, Control Structures, Functions and Arrays, Pointers and Structures |
| 21BCA103 | Discrete Mathematical Structures | Core | 4 | Set Theory and Logic, Relations and Functions, Graph Theory, Trees and Algorithms, Recurrence Relations |
| 21OECA01 | Office Automation | Open Elective | 3 | MS Word for Document Creation, MS Excel for Data Analysis, MS PowerPoint for Presentations, Database Management with MS Access, Internet Fundamentals |
| 21SECA01 | Web Designing | Skill Enhancement | 3 | HTML Structure and Elements, CSS for Styling, Responsive Design Principles, JavaScript Basics, Web Publishing |
| 21AECC11 | Language I (Kannada/Sanskrit/Hindi etc.) | Ability Enhancement | 2 | Grammar, Composition, Literary Texts, Communication Skills, Cultural Context |
| 21AECC12 | English I | Ability Enhancement | 2 | Reading Comprehension, Writing Skills, Grammar and Vocabulary, Effective Communication, Report Writing |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BCA201 | Data Structures | Core | 4 | Arrays and Linked Lists, Stacks and Queues, Trees and Binary Search Trees, Graphs and Traversals, Sorting and Searching |
| 21BCA202 | Object Oriented Programming using C++ | Core | 4 | OOP Concepts, Classes and Objects, Inheritance and Polymorphism, Constructors and Destructors, File Handling |
| 21BCA203 | Database Management System | Core | 4 | Database Concepts, ER Model, Relational Model, SQL Queries, Normalization |
| 21OECA02 | Data Analytics with Excel | Open Elective | 3 | Excel Functions for Data, Data Visualization in Excel, Pivot Tables and Charts, Data Analysis Tools, Basic Statistical Analysis |
| 21SECA02 | DTP Lab (Desktop Publishing) | Skill Enhancement | 3 | Introduction to DTP, Page Layout Design, Image Editing Basics, Typography Principles, Document Production |
| 21AECC21 | Language II (Kannada/Sanskrit/Hindi etc.) | Ability Enhancement | 2 | Advanced Grammar, Creative Writing, Poetry and Prose Analysis, Public Speaking, Translation |
| 21AECC22 | English II | Ability Enhancement | 2 | Literary Appreciation, Business Communication, Technical Writing, Presentation Skills, Interviews and Group Discussions |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BCA301 | Operating System | Core | 4 | OS Introduction and Functions, Process Management, Memory Management, File Systems, I/O Management |
| 21BCA302 | Java Programming | Core | 4 | Java Fundamentals, Classes, Objects, Methods, Inheritance and Interfaces, Exception Handling, Multithreading and Applets |
| 21BCA303 | Computer Networks | Core | 4 | Network Topologies, OSI and TCP/IP Models, Network Devices, IP Addressing, Network Security Basics |
| 21OECA03 | E-Commerce | Open Elective | 3 | E-Commerce Models, Payment Systems, Online Marketing, E-Security, Legal Aspects of E-Commerce |
| 21SECA03 | Android App Development | Skill Enhancement | 3 | Android Studio Environment, Activities and Layouts, User Interface Design, Event Handling, Data Storage |
| 21VSC301 | Environmental Studies | Value Added Course | 2 | Ecosystems, Biodiversity, Environmental Pollution, Sustainable Development, Environmental Protection |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BCA401 | Software Engineering | Core | 4 | Software Development Life Cycle, Software Requirements, Design Concepts, Testing Strategies, Project Management |
| 21BCA402 | Python Programming | Core | 4 | Python Syntax and Data Types, Control Flow, Functions and Modules, Object-Oriented Python, File I/O |
| 21BCA403 | Web Programming | Core | 4 | HTML5 and CSS3, JavaScript and DOM, Server-Side Scripting (PHP/ASP.NET basics), Databases with Web, Web Security Basics |
| 21OECA04 | Cyber Security | Open Elective | 3 | Cybercrime Overview, Network Security Threats, Cryptography Basics, Digital Forensics, Security Policies |
| 21SECA04 | R Programming | Skill Enhancement | 3 | R Environment and Basics, Data Structures in R, Data Manipulation, Statistical Graphics, Programming with R |
| 21VSC401 | Indian Constitution | Value Added Course | 2 | Constitutional Framework, Fundamental Rights, Directive Principles, Union and State Government, Local Self-Government |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BCA501 | Cryptography and Network Security | Core | 4 | Security Services and Mechanisms, Symmetric Key Cryptography, Asymmetric Key Cryptography, Hash Functions, Network Security Applications |
| 21BCA502 | Numerical and Statistical Methods | Core | 4 | Numerical Errors, Solutions of Equations, Interpolation, Statistical Measures, Correlation and Regression |
| 21DSE5.1A | Data Mining & Data Warehousing | Discipline Specific Elective | 4 | Data Warehousing Concepts, OLAP Operations, Data Mining Techniques, Association Rules, Clustering and Classification |
| 21DSE5.1B | Internet of Things | Discipline Specific Elective | 4 | IoT Architecture, Sensors and Actuators, Communication Protocols, Cloud Integration, IoT Security |
| 21DSE5.1C | Cloud Computing | Discipline Specific Elective | 4 | Cloud Service Models (IaaS, PaaS, SaaS), Cloud Deployment Models, Virtualization, Cloud Security, Cloud Providers |
| 21DSE5.2A | Artificial Intelligence | Discipline Specific Elective (AI-related) | 4 | AI Problem Solving, Search Algorithms, Knowledge Representation, Machine Learning Basics, Natural Language Processing Introduction |
| 21DSE5.2B | Machine Learning | Discipline Specific Elective (AI-related) | 4 | Supervised Learning, Unsupervised Learning, Regression Algorithms, Classification Algorithms, Model Evaluation |
| 21DSE5.2C | Big Data Analytics | Discipline Specific Elective | 4 | Big Data Characteristics, Hadoop Ecosystem, MapReduce, NoSQL Databases, Data Stream Analytics |
| 21BCA503 | Project Work I | Project | 4 | Problem Identification, Requirement Analysis, System Design, Implementation Planning, Report Writing |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21BCA601 | Computer Graphics | Core | 4 | Graphics Primitives, 2D and 3D Transformations, Viewing and Clipping, Color Models, Image Processing Basics |
| 21BCA602 | Theory of Computation | Core | 4 | Finite Automata, Regular Expressions, Context-Free Grammars, Turing Machines, Undecidability |
| 21DSE6.1A | Digital Image Processing | Discipline Specific Elective | 4 | Image Fundamentals, Image Enhancement, Image Restoration, Image Compression, Image Segmentation |
| 21DSE6.1B | Game Programming | Discipline Specific Elective | 4 | Game Development Process, Game Engines (Unity/Unreal basics), 2D/3D Graphics in Games, Physics and AI in Games, Input and Interaction |
| 21DSE6.1C | Mobile Application Development | Discipline Specific Elective | 4 | Mobile OS Overview (Android/iOS), Hybrid App Frameworks (React Native/Flutter basics), UI/UX for Mobile, APIs and Data Storage, App Deployment |
| 21DSE6.2A | Data Science | Discipline Specific Elective (AI-related) | 4 | Data Science Lifecycle, Data Collection and Cleaning, Exploratory Data Analysis, Statistical Inference, Predictive Modeling |
| 21DSE6.2B | Deep Learning | Discipline Specific Elective (AI-related) | 4 | Neural Network Fundamentals, Activation Functions, Backpropagation, Convolutional Neural Networks, Recurrent Neural Networks |
| 21DSE6.2C | Natural Language Processing | Discipline Specific Elective (AI-related) | 4 | Text Preprocessing, Tokenization and Stemming, Language Models, Named Entity Recognition, Sentiment Analysis |
| 21BCA603 | Project Work II | Project | 4 | Project Implementation, Testing and Debugging, Documentation, Presentation and Demonstration, Maintenance Planning |
