Comprehensive Course Structure

The Computer Applications program at The Assam Kaziranga University Jorhat follows a structured academic calendar spanning eight semesters over four years. Each semester includes core courses, departmental electives, science electives, and laboratory components designed to build both theoretical knowledge and practical skills.

Semester	Course Code	Course Title	Credit Structure (L-T-P-C)	Pre-requisites
I	CS101	Programming in C	3-0-2-4	-
I	CS102	Mathematics for Computer Applications	3-0-0-3	-
I	CS103	Introduction to Computer Science	2-0-0-2	-
I	CS104	English for Technical Communication	2-0-0-2	-
I	CS105	Computer Laboratory	0-0-4-2	-
I	SC101	Physics for Engineers	3-0-0-3	-
I	SC102	Chemistry for Engineers	3-0-0-3	-
II	CS201	Data Structures and Algorithms	3-0-2-4	CS101
II	CS202	Digital Logic Design	3-0-0-3	-
II	CS203	Object-Oriented Programming	3-0-2-4	CS101
II	CS204	Mathematics for Computer Applications II	3-0-0-3	CS102
II	CS205	Database Management Systems	3-0-0-3	-
II	SC201	Biology for Engineers	3-0-0-3	-
III	CS301	Operating Systems	3-0-2-4	CS203
III	CS302	Computer Networks	3-0-2-4	CS201
III	CS303	Software Engineering	3-0-0-3	-
III	CS304	Web Technologies	3-0-2-4	CS203
III	CS305	Probability and Statistics	3-0-0-3	CS102
IV	CS401	Compiler Design	3-0-2-4	CS301
IV	CS402	Artificial Intelligence	3-0-2-4	CS201
IV	CS403	Cybersecurity Fundamentals	3-0-2-4	CS201
IV	CS404	Data Mining and Analytics	3-0-2-4	CS305
IV	CS405	Project Management	3-0-0-3	-
V	CS501	Machine Learning	3-0-2-4	CS402
V	CS502	Advanced Database Systems	3-0-2-4	CS205
V	CS503	Cloud Computing	3-0-2-4	CS302
V	CS504	Mobile Application Development	3-0-2-4	CS304
V	CS505	Human-Computer Interaction	3-0-0-3	-
VI	CS601	Internet of Things	3-0-2-4	CS302
VI	CS602	DevOps Practices	3-0-2-4	CS301
VI	CS603	Software Testing	3-0-2-4	CS303
VI	CS604	Digital Marketing	3-0-0-3	-
VI	CS605	Entrepreneurship in Tech	3-0-0-3	-
VII	CS701	Advanced Topics in AI	3-0-2-4	CS501
VII	CS702	Research Methodology	3-0-0-3	-
VII	CS703	Capstone Project I	0-0-6-4	-
VIII	CS801	Capstone Project II	0-0-6-4	-
VIII	CS802	Internship	0-0-0-10	-

Advanced Departmental Electives

These courses offer specialized knowledge in emerging areas of computer applications and are tailored to meet the evolving needs of industry professionals:

1. Machine Learning (CS501)

This course introduces students to fundamental concepts of machine learning, including supervised and unsupervised learning algorithms, neural networks, and deep learning frameworks. Students will implement real-world applications using tools like TensorFlow and PyTorch.

2. Advanced Database Systems (CS502)

This course delves into advanced topics in database design, optimization techniques, transaction management, and distributed databases. It explores NoSQL systems and cloud-based database solutions that are widely used in modern enterprises.

3. Cloud Computing (CS503)

Students learn about cloud architecture, service models (IaaS, PaaS, SaaS), virtualization technologies, containerization using Docker, and orchestration with Kubernetes. The course includes hands-on labs on AWS, Azure, and Google Cloud.

4. Mobile Application Development (CS504)

This elective focuses on building cross-platform mobile apps for iOS and Android using modern frameworks such as React Native and Flutter. Students develop real-world applications with features like authentication, API integration, and push notifications.

5. Human-Computer Interaction (CS505)

The course emphasizes the design of user-friendly interfaces and the psychology behind human interaction with technology. It covers usability testing, prototyping, accessibility standards, and inclusive design principles.

6. Internet of Things (CS601)

This course explores the integration of physical devices with digital networks for smart automation. Students work on projects involving sensors, microcontrollers, wireless communication protocols, and cloud platforms to create IoT applications.

7. DevOps Practices (CS602)

The course introduces continuous integration/continuous deployment (CI/CD) pipelines, version control systems, automation tools, and infrastructure as code. Students gain practical experience in deploying scalable applications using Jenkins, GitLab CI, and Ansible.

8. Software Testing (CS603)

This course teaches various software testing methodologies including unit testing, integration testing, system testing, and performance testing. It includes hands-on experience with tools like Selenium, JUnit, and Postman for automated testing.

9. Digital Marketing (CS604)

The course combines technical skills with marketing strategies to drive online business growth. Topics include SEO/SEM, social media analytics, email marketing automation, and data-driven advertising using platforms like Google Ads and Facebook Business Suite.

10. Entrepreneurship in Tech (CS605)

This elective empowers students with the skills needed to launch and manage technology startups. It covers business model innovation, pitch deck preparation, investor relations, legal aspects of tech entrepreneurship, and funding mechanisms.

Project-Based Learning Philosophy

The department strongly advocates for project-based learning as a core pedagogical approach. Projects are designed to integrate knowledge from multiple disciplines and foster innovation and problem-solving skills.

Mini-Projects

Mini-projects are assigned in the third and fourth semesters, allowing students to apply theoretical concepts in practical scenarios. These projects span 6-8 weeks and involve working in teams of 3-5 members under faculty supervision.

Final-Year Thesis/Capstone Project

The final-year capstone project is a comprehensive endeavor that requires students to solve a real-world problem using advanced technologies. Projects are selected based on student interests, faculty expertise, and industry relevance. The process involves literature review, research methodology, implementation, testing, documentation, and presentation.

Project Selection Process

Students can propose projects aligned with their interests or choose from a list of faculty-identified problems. The selection is done through a proposal submission process followed by a review panel that evaluates feasibility, innovation, and resource requirements.

Evaluation Criteria

Projects are evaluated based on technical execution, creativity, presentation quality, documentation, peer collaboration, and impact assessment. A final evaluation committee comprising faculty members and industry experts provides feedback and grades.