Comprehensive Course Structure
The Skill Development program at Matrix Skilltech University Geyzing is structured over eight semesters, ensuring a progressive and comprehensive academic journey. Each semester integrates foundational sciences, core engineering principles, departmental electives, science electives, and hands-on laboratory experiences to create a well-rounded educational experience.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| I | ENG101 | English for Technical Communication | 3-0-0-3 | - |
| I | MAT101 | Calculus and Differential Equations | 4-0-0-4 | - |
| I | PHY101 | Physics of Materials | 3-0-0-3 | - |
| I | CSE101 | Introduction to Computer Science | 3-0-0-3 | - |
| I | ENG102 | Engineering Drawing and Design | 2-0-0-2 | - |
| I | LIT101 | Introduction to Liberal Arts | 3-0-0-3 | - |
| I | LAB101 | Computer Lab I | 0-0-2-1 | - |
| II | MAT102 | Linear Algebra and Statistics | 4-0-0-4 | MAT101 |
| II | CSE102 | Data Structures and Algorithms | 3-0-0-3 | CSE101 |
| II | PHY102 | Electronics and Circuits | 3-0-0-3 | PHY101 |
| II | ENG103 | Technical Writing and Presentation | 2-0-0-2 | - |
| II | LAB102 | Data Structures Lab | 0-0-2-1 | CSE101 |
| III | MAT201 | Differential Equations and Complex Analysis | 3-0-0-3 | MAT102 |
| III | CSE201 | Database Management Systems | 3-0-0-3 | CSE102 |
| III | EE201 | Digital Electronics and Logic Design | 3-0-0-3 | PHY102 |
| III | LAB201 | Database Systems Lab | 0-0-2-1 | CSE102 |
| IV | MAT202 | Probability and Queuing Theory | 3-0-0-3 | MAT201 |
| IV | CSE202 | Operating Systems | 3-0-0-3 | CSE201 |
| IV | ME201 | Engineering Mechanics | 3-0-0-3 | - |
| IV | LAB202 | Operating Systems Lab | 0-0-2-1 | CSE201 |
| V | CSE301 | Computer Networks | 3-0-0-3 | CSE202 |
| V | ME301 | Mechanical Engineering Fundamentals | 3-0-0-3 | ME201 |
| V | LAB301 | Networks Lab | 0-0-2-1 | CSE202 |
| VI | CSE302 | Software Engineering | 3-0-0-3 | CSE301 |
| VI | EE301 | Signals and Systems | 3-0-0-3 | PHY102 |
| VI | LAB302 | Software Engineering Lab | 0-0-2-1 | CSE301 |
| VII | CSE401 | Machine Learning and AI | 3-0-0-3 | CSE302 |
| VII | EE401 | Control Systems | 3-0-0-3 | EE301 |
| VII | LAB401 | ML/AI Lab | 0-0-2-1 | CSE302 |
| VIII | CSE402 | Capstone Project | 3-0-0-3 | CSE401 |
| VIII | LAB402 | Final Year Project Lab | 0-0-2-1 | CSE401 |
Following the core curriculum, students are introduced to a wide array of departmental electives that allow them to specialize in areas of interest. These courses provide depth and focus beyond the general framework.
Advanced Departmental Electives
Deep Learning and Neural Networks: This course delves into advanced architectures such as CNNs, RNNs, Transformers, and GANs. Students will implement models using TensorFlow and PyTorch, gaining hands-on experience in training large-scale neural networks for image recognition, natural language processing, and generative tasks.
Reinforcement Learning: Designed to explore decision-making strategies in dynamic environments, this course covers Markov Decision Processes, Q-Learning, Policy Gradients, and Deep Deterministic Policy Gradient (DDPG). Students will apply these concepts to robotics, game AI, and autonomous systems.
Cybersecurity & Ethical Hacking: This course focuses on network security principles, cryptographic techniques, penetration testing, vulnerability assessment, and incident response. Students will gain practical skills in defensive and offensive cybersecurity practices through lab simulations.
Blockchain Technologies: A comprehensive study of distributed ledger systems, smart contracts, consensus mechanisms, and decentralized applications. Students will build their own blockchain platforms using Solidity and explore real-world use cases in finance, supply chain, and digital identity.
Data Visualization & Storytelling with Python: This course teaches students to transform raw data into compelling visual narratives using libraries like Matplotlib, Seaborn, Plotly, and D3.js. Emphasis is placed on storytelling techniques and interactive dashboards for business intelligence.
UX/UI Design Principles: Students will learn user research methods, wireframing, prototyping, usability testing, and accessibility standards. The course includes projects that require students to design interfaces for mobile apps, web platforms, and enterprise software.
Product Management Fundamentals: An introduction to product lifecycle management, agile methodologies, market analysis, and cross-functional team collaboration. Students will simulate managing a product from conception to launch through real-world case studies.
DevOps & Cloud Computing: This course covers CI/CD pipelines, containerization with Docker and Kubernetes, infrastructure-as-code (Terraform), and deployment automation on AWS, Azure, and GCP. Practical labs involve building scalable cloud-native applications.
Sustainable Technologies & Green Innovation: Exploring renewable energy systems, waste management technologies, carbon footprint reduction, and green building design. Students will engage in projects that propose eco-friendly solutions for urban development and industrial processes.
Financial Technology (FinTech) & Risk Analytics: Students will study cryptocurrency trading, algorithmic trading strategies, regulatory compliance, and risk modeling using Python and SQL. The course includes simulations of financial markets and portfolio optimization techniques.
Digital Marketing & E-commerce Strategy: This elective explores SEO/SEM, social media analytics, customer journey mapping, conversion optimization, and digital product launches. Students will create marketing campaigns for real clients and analyze their performance using tools like Google Analytics and Facebook Ads Manager.
Human-Computer Interaction: Focused on understanding user behavior, cognitive psychology, and interaction design principles, this course emphasizes the role of usability in software development. Students will conduct user studies and evaluate interface designs based on human factors research.
Robotic Process Automation (RPA): A practical exploration of automation technologies using tools like UiPath, Automation Anywhere, and Blue Prism. Students will design workflows for repetitive tasks and integrate RPA solutions with enterprise systems.
Project-Based Learning Philosophy
The department's philosophy on project-based learning emphasizes the importance of experiential education in developing critical thinking, problem-solving, and collaborative skills. Mini-projects are introduced early in the curriculum to help students apply theoretical concepts in practical scenarios.
Each semester, students work on a series of mini-projects that build upon each other, culminating in a final-year thesis or capstone project. These projects are selected based on student interests, faculty expertise, and industry relevance. Students can propose their own ideas, collaborate with peers, or join existing research initiatives.
The evaluation criteria for mini-projects include technical execution, innovation, teamwork, presentation quality, and documentation standards. Final-year projects are supervised by faculty mentors who guide students through the research process, from hypothesis formulation to solution implementation.