Comprehensive Course Structure
The Bachelor of Computer Science program at Iasscom Fortune Institute of Technology is meticulously designed to provide a comprehensive foundation in both theoretical and applied aspects of computer science. The curriculum spans eight semesters, with each semester carefully structured to build upon the previous one, ensuring progressive learning and specialization.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | CS101 | Programming Fundamentals | 3-0-0-3 | - |
| 1 | CS102 | Mathematics I | 3-0-0-3 | - |
| 1 | CS103 | Computer Organization | 3-0-0-3 | - |
| 1 | CS104 | Introduction to Data Structures | 3-0-0-3 | - |
| 1 | CS105 | Lab - Programming Fundamentals | 0-0-3-0 | - |
| 2 | CS201 | Discrete Mathematics | 3-0-0-3 | CS102 |
| 2 | CS202 | Algorithms | 3-0-0-3 | CS104 |
| 2 | CS203 | Database Management Systems | 3-0-0-3 | CS104 |
| 2 | CS204 | Operating Systems | 3-0-0-3 | CS103 |
| 2 | CS205 | Lab - Algorithms & Data Structures | 0-0-3-0 | - |
| 3 | CS301 | Software Engineering | 3-0-0-3 | CS201 |
| 3 | CS302 | Computer Networks | 3-0-0-3 | CS204 |
| 3 | CS303 | Artificial Intelligence & Machine Learning | 3-0-0-3 | CS202 |
| 3 | CS304 | Cybersecurity Fundamentals | 3-0-0-3 | CS203 |
| 3 | CS305 | Lab - Software Engineering | 0-0-3-0 | - |
| 4 | CS401 | Data Science and Analytics | 3-0-0-3 | CS202 |
| 4 | CS402 | Cloud Computing | 3-0-0-3 | CS204 |
| 4 | CS403 | Mobile Application Development | 3-0-0-3 | CS101 |
| 4 | CS404 | Human-Computer Interaction | 3-0-0-3 | CS201 |
| 4 | CS405 | Lab - Cloud & Mobile Apps | 0-0-3-0 | - |
| 5 | CS501 | Advanced Algorithms | 3-0-0-3 | CS202 |
| 5 | CS502 | Deep Learning | 3-0-0-3 | CS303 |
| 5 | CS503 | Network Security | 3-0-0-3 | CS203 |
| 5 | CS504 | Big Data Technologies | 3-0-0-3 | CS401 |
| 5 | CS505 | Lab - Advanced Topics | 0-0-3-0 | - |
| 6 | CS601 | Quantum Computing | 3-0-0-3 | CS202 |
| 6 | CS602 | Reinforcement Learning | 3-0-0-3 | CS502 |
| 6 | CS603 | Embedded Systems | 3-0-0-3 | CS103 |
| 6 | CS604 | Game Development | 3-0-0-3 | CS303 |
| 6 | CS605 | Lab - Specialized Electives | 0-0-3-0 | - |
| 7 | CS701 | Capstone Project I | 3-0-0-3 | CS501 |
| 7 | CS702 | Research Methodology | 3-0-0-3 | - |
| 7 | CS703 | Project Management | 3-0-0-3 | - |
| 7 | CS704 | Internship Preparation | 3-0-0-3 | - |
| 7 | CS705 | Lab - Capstone & Research | 0-0-3-0 | - |
| 8 | CS801 | Capstone Project II | 3-0-0-3 | CS701 |
| 8 | CS802 | Advanced Elective I | 3-0-0-3 | - |
| 8 | CS803 | Advanced Elective II | 3-0-0-3 | - |
| 8 | CS804 | Industry Exposure Workshop | 3-0-0-3 | - |
| 8 | CS805 | Lab - Final Project | 0-0-3-0 | - |
Advanced Departmental Electives
The department offers a range of advanced elective courses that allow students to delve deeper into specialized areas within computer science. These courses are designed to provide cutting-edge knowledge and practical skills relevant to current industry demands.
Deep Learning with TensorFlow is an intensive course that covers advanced neural network architectures, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. Students learn how to implement complex models using the popular TensorFlow framework and apply them to image recognition, natural language processing, and time-series forecasting.
Natural Language Processing (NLP) explores techniques for processing and understanding human language through computational methods. Topics include tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, and machine translation. Students work with real-world datasets and build end-to-end NLP pipelines using libraries like spaCy and Hugging Face Transformers.
Computer Vision delves into the principles and applications of image processing and pattern recognition. The course covers image filtering, feature extraction, object detection, segmentation, and facial recognition. Students implement algorithms using OpenCV and Python to create visual analytics tools and robotic vision systems.
Reinforcement Learning introduces students to decision-making processes in uncertain environments. The course explores Markov Decision Processes (MDPs), Q-learning, policy gradients, and deep reinforcement learning. Practical applications include autonomous vehicles, game-playing AI, and robotics control systems.
Quantum Computing provides an overview of quantum mechanics and its application in computation. Students study qubits, superposition, entanglement, quantum gates, and algorithms like Shor’s algorithm and Grover’s search. The course includes hands-on experience with quantum simulators and real quantum hardware from IBM Quantum.
Blockchain Security examines the cryptographic foundations of blockchain technology and its security mechanisms. Students explore consensus protocols, smart contracts, distributed ledger systems, and vulnerabilities in blockchain implementations. Real-world case studies cover cryptocurrency attacks, regulatory compliance, and secure decentralized applications (dApps).
Embedded Systems covers hardware-software integration for resource-constrained environments. The course includes microcontroller programming, real-time operating systems (RTOS), sensor interfacing, and power management. Students design embedded solutions for IoT devices, automotive systems, and industrial automation.
Game Development focuses on creating interactive experiences using modern game engines like Unity and Unreal Engine. Students learn game architecture, physics simulation, AI behavior scripting, and user interface design. The course culminates in a full-fledged game prototype developed by teams.
Human-Computer Interaction (HCI) emphasizes the design and evaluation of user interfaces. Topics include usability testing, cognitive psychology, accessibility standards, and prototyping tools. Students develop inclusive digital products that meet diverse user needs and improve overall user experience.
Mobile Application Development introduces students to cross-platform development using frameworks like React Native and Flutter. The course covers mobile UI/UX design, API integration, authentication systems, and app deployment strategies. Students build apps for iOS and Android platforms from scratch.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that hands-on experience is essential for mastering complex computer science concepts. Projects are designed to simulate real-world scenarios, encouraging students to apply theoretical knowledge in practical contexts.
Mini-projects are assigned throughout the program, typically at the end of each semester. These projects aim to reinforce core concepts while building teamwork and communication skills. Each project is guided by a faculty mentor who provides feedback, evaluates progress, and ensures alignment with learning objectives.
The final-year thesis or capstone project represents the culmination of a student's academic journey. Students select a research topic in consultation with their faculty advisor, conduct literature reviews, design experiments, and present findings to a panel of experts. The project often leads to publications, patents, or startup ventures.
Students are encouraged to propose innovative ideas for their projects, ensuring that they contribute meaningfully to the field. Collaboration with industry partners, government agencies, or research institutions is facilitated to provide real-world relevance and impact.