Course Code: 25CS01I | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science(CS)

The launchpad course that turns a beginner into a digitally confident technologist — covering hardware,
the internet, cybersecurity, coding logic and today’s AI tools.

What Students Will Learn & Gain

• Solid digital foundation — learn computer hardware, operating systems, networking basics and
  internet services — the vocabulary and know-how every IT/CS professional needs from day one.
• Cyber-safety as a habit — hands-on practice with threat identification, strong passwords,
  multi-factor authentication, safe browsing and data backup builds a security-first mindset.
• Problem-solving before syntax — block-based coding (Scratch/Blockly) and flowcharting develop
  algorithmic thinking, making later programming courses far easier to grasp.
• Early exposure to modern tech — guided, hands-on activities in Cloud Computing
  (AWS/Azure/GCP), IoT (Arduino/Tinkercad) and Artificial Intelligence build familiarity with technologies
  shaping the industry.
• AI fluency through prompt engineering — students learn to write clear, structured prompts and
  use tools like ChatGPT/Claude/Gemini effectively — a fast-emerging, highly valued workplace skill.
• Career direction from day one — exposure to IT certification pathways helps students plan their
  specialization (networking, security, cloud, development) early in the diploma.

Course Code: 25EE01I | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Electrical & Electronics /Electronics & Communication
The essential bridge between hardware and software — giving computer engineers the electrical
grounding needed to understand the machines they program.

What Students Will Learn & Gain

• Understands the physics behind computing — core concepts of electrical circuits, current,
  voltage and resistance explain how the hardware inside every computer actually works.
• Foundation for digital electronics — knowledge of basic electronic components and circuits
  directly supports the parallel course on Digital Logic and Computer Organization.
• Hardware and safety awareness — familiarity with electrical measuring instruments, safety
  practices and basic troubleshooting is valuable for anyone assembling or maintaining computer
  systems.
• Supports IoT and embedded systems work — electronics fundamentals underpin later hands-on
  work with sensors, microcontrollers, and IoT devices seen in the IT Skills and other integrated courses.
• Well-rounded engineering base — as a cross-department integrated course, it builds
  interdisciplinary awareness — a trait valued in engineers who design hardware-aware software.
• Practical, lab-driven learning — the 3:0:4 teaching scheme (heavy on practice) ensures concepts
  are reinforced through actual circuit-building and measurement, not just theory.

Course Code: 25CS33I | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science(CS)

The backbone of efficient programming — teaching students how to organize, store and manipulate data so their code runs faster and scales better.

What Students Will Learn & Gain

• Mastery of Python’s built-in structures — deep, hands-on practice with sets, tuples, lists,
  dictionaries and strings — the tools used in almost every real Python program.
• Core data structures, done properly — stacks, queues, singly/doubly linked lists and trees are built
  and operated on from scratch, not just used as black boxes.
• Efficiency-first thinking — students learn to compare data structures and choose the right one for a
  problem — a skill that directly improves code quality and performance.
• Recursion and error handling — structured practice in recursive problem-solving and exception
  handling builds resilience and clarity in code design.
• Abstract Data Types (ADT) via classes — implementing ADTs using user-defined types (UDTs)
  introduces object-oriented thinking early, preparing students for advanced programming.
• Strong base for interviews and further study — stacks, queues, linked lists and trees are staple
  topics in coding interviews and prerequisites for algorithms, databases and AI/ML courses.

Course Code: 25CS34I | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science(CS)

A hands-on, hardware-to-network course that prepares students to build, configure, secure and troubleshoot real IT infrastructure — not just theory.

What Students Will Learn & Gain

• End-to-end hardware competency — students identify, assemble and troubleshoot PC
  components — cabinets, SMPS, motherboards and chipsets — gaining real technician-level skill.
• OS installation and administration — practical installation and configuration of Windows/Linux,
  user account management, and PowerShell scripting build genuine sysadmin capability.
• Data protection know-how — disk partitioning, file systems, backup strategies and data/registry
  recovery techniques prepare students to safeguard critical information.
• Networking and security skills — IP addressing, DNS, firewalls, VPNs and network
  troubleshooting give students the ability to configure and secure real networks.
• Job-ready for IT support roles — the course closely mirrors real System/Network Administrator
  and IT Support Specialist job responsibilities, easing the transition to employment.
• Responsible tech practices — a dedicated module on e-waste management builds awareness of
  sustainable and regulation-compliant IT operations.

Course Code: 25CS43I | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science(CS)

Where programming meets data science — combining NumPy/Pandas-driven data analysis with the algorithm design skills needed to write efficient, scalable code.

What Students Will Learn & Gain

• Practical data analytics skills — hands-on work with NumPy arrays and Pandas
  Series/DataFrames covers real tasks — cleaning, filtering, grouping and aggregating data.
• Data storytelling through visualization — using Matplotlib and Seaborn, students learn to turn raw
  numbers into clear, insightful charts — a core data-analyst skill.
•  Algorithm design strategies — brute force, divide-and-conquer, greedy and dynamic programming
  approaches are taught through classic problems like sorting, searching and Fibonacci.
• Efficiency analysis (Big-O thinking) — asymptotic time and space complexity analysis, plotted and
  compared, builds the habit of writing code that scales — vital for technical interviews.
• Graphs and hashing fundamentals — BFS/DFS traversal and hash-table based applications (e.g.,
  secure password verification) extend problem-solving into advanced CS territory.
• Dual career readiness — the blend of data analysis and algorithmic rigor prepares students for both
  data-analyst and software-developer career paths.

Course Code: 25CS44I | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science(CS)

A complete front-end journey — from UI/UX design thinking to HTML/CSS/JavaScript and modern React.js — ending in a fully functional Single Page Application

What Students Will Learn & Gain

• Design-first approach — UI/UX principles and the 5-stage Design Thinking process (using tools like
  Figma) teach students to design for users before writing a line of code.
• Strong HTML & CSS fundamentals — structured practice building forms, tables, layouts and styling
  gives students the ability to turn any design into a working webpage.
• Dynamic, interactive pages with JavaScript — DOM manipulation, event handling and JSON
  handling let students build responsive, interactive user experiences.
• Industry-relevant React.js skills — components, props, hooks (useState/useEffect) and React
  Router are exactly what employers expect from junior front-end developers today.
• Portfolio-ready project experience — the course builds up to a complete Single Page Application
  (SPA) with routing and protected pages — a strong addition to any student portfolio.
• Direct path to front-end/full-stack roles — combining design, markup, scripting and framework
  skills makes graduates immediately relevant for web-developer internships and jobs.

Course Code: 25ME02I | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Mechanical Engineering (ME)

Builds the visual and spatial communication skills every engineer needs — translating ideas into precise technical drawings using modern CAD tools.

What Students Will Learn & Gain

• Universal engineering language — learning standard drawing conventions, projections and
  dimensioning enables clear communication of technical ideas across any engineering discipline.
• Spatial visualization — practicing orthographic and isometric views strengthens the ability to
  mentally construct and interpret 2D/3D objects — useful in UI/product design and hardware work too.
• CAD software proficiency — hands-on use of computer-aided design tools builds practical,
  transferable software skills valued in product design, prototyping and documentation roles.
  n Precision and attention to detail — engineering graphics demands accuracy in scale, proportion
  and annotation — a discipline that carries over into all technical work.
  n Cross-disciplinary foundation — as a course taught outside the CS department, it broadens a
  computer science student’s ability to collaborate with mechanical/product teams.
  n Documentation skills — the ability to read and produce technical drawings supports later work in
  hardware documentation, IoT device design and system diagrams.

Course Code: 25CS42I | Contact Hours: 8 Hrs/week | Credits: 6 | Teaching Dept: Computer Science(CS)

A hands-on journey into Object-Oriented Programming using Java — building both strong OOP fundamentals and the SOLID design habits that separate hobby coders from professional developers.

What Students Will Learn & Gain

• True mastery of OOP concepts — classes, objects, encapsulation, inheritance, polymorphism and abstraction are each built and practiced hands-on in Java, one of the world’s most widely used
  enterprise languages.
• SOLID principles woven throughout — every OOP concept is paired with its related SOLID
  principle (SRP, OCP, LSP, ISP, DIP) using violation/correction examples — building genuinely
  maintainable coding habits.
• Robust, production-style code — structured practice in exception handling, the Collections
  Framework (List, Set, Map, Queue) and multithreading prepares students to write reliable, efficient
  applications.
• Real-world data skills — file handling, Java annotations, and JDBC-based database connectivity
  (CRUD operations) mirror tasks found in actual enterprise software jobs.
• Refactoring as a core skill — students repeatedly take flawed code and refactor it to fix principle
  violations — exactly the skill senior developers expect from code reviews.
• Strong base for enterprise & Android careers — Java’s dominance in enterprise backend
  systems, large-scale applications and Android development makes this course directly relevant to
  major career paths.

Course Code: 25CS52ID | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science (CS)

A hands-on cybersecurity foundation — covering threats, cryptography, network/web/OS security and the beginnings of penetration testing, in a dedicated lab environment.

What Students Will Learn & Gain

• Real security-lab experience — students set up Kali Linux, VirtualBox and VMware environments
  from week one, learning by doing rather than by theory alone.
• Covers the full threat landscape — malware, phishing/social engineering, password attacks and
  web vulnerabilities (SQLi, HTTP/OS command injection) are studied and safely simulated.
• Applied cryptography — encryption, hashing, digital signatures, and algorithms like AES and RSA
  are implemented and tested by hand, grounding security decisions in real mathematics.
• Cross-platform hardening skills — Windows security (Active Directory, Group Policy, BitLocker)
  and Linux security (SELinux, AppArmor, SSH hardening) are both practiced in depth.
• Early introduction to VAPT — reconnaissance, privilege escalation and the MITRE ATT&CK;
  framework give a first taste of professional penetration-testing methodology.
• Certification-aligned content — topics map closely to CompTIA Security+, CEH and Cisco
  CyberOps, giving students a head start on industry-recognized certifications.

Course Code: 25CS53IA | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science (CS)

practical, project-driven introduction to Deep Learning — from building neural networks with
TensorFlow/Keras to tuning, explaining, and deploying real models.

What Students Will Learn & Gain

• Hands-on with industry-standard tools — TensorFlow, Keras and TensorBoard are used from the
  very first week to build and visualize real neural networks, not just discuss them in theory.
• Covers the full deep learning toolkit — Artificial, Convolutional and Recurrent Neural Networks
  (including LSTMs), plus generative models like Autoencoders and GANs, give a broad, practical AI
  foundation.
• Data discipline before modeling — normalization, augmentation, encoding, and train/validation/test
  splitting instill the good data-handling habits every ML engineer needs.
• Model tuning that actually works — hyperparameter tuning, regularization (dropout, L1/L2), and
  evaluation via precision/recall/F1 teach students to build models that generalize, not just memorize.
• Explainable and deployable AI — tools like Grad-CAM and SHAP for explainability, plus
  deployment via Flask/TensorFlow Serving, take students beyond training into real-world AI delivery.
• Portfolio-ready capstone project — a full mini-project — from problem definition to trained,
  deployed model — gives students a concrete AI project to showcase to employers.

Course Code: 25CS53IB | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science (CS)

A practical, multi-cloud security course — teaching students to secure, monitor and stay compliant across AWS, Azure and GCP

What Students Will Learn & Gain

• Real multi-cloud, hands-on labs — practical work across AWS, Azure and GCP — configuring
  IAM, VPCs, encryption (KMS) and threat-detection tools like GuardDuty — builds directly employable
  cloud-security skills.
• Compliance literacy, not just technical skill — frameworks like GDPR, HIPAA and ISO 27001,
  plus data-sovereignty and legal considerations, prepare students to operate within real regulatory
  constraints.
• Covers the full cloud-security lifecycle — identity management, data protection, network security,
  monitoring and incident response are each practiced hands-on in realistic scenarios.
• DevSecOps mindset — securing serverless functions and containers (Lambda, ECS/EKS/AKS) and
  embedding security into CI/CD pipelines reflects how modern engineering teams actually work.
• Incident-response readiness — simulated security incidents and cloud security audits build the
  judgment needed for SOC analyst and cloud-security-analyst roles.
• Capstone multi-cloud project — designing and securing a hybrid/multi-cloud infrastructure
  end-to-end ties every concept together into a strong portfolio piece.

Course Code: 25CS53IC | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science (CS)

An end-to-end DevOps course — taking students through the entire software delivery pipeline, from Git to CI/CD to containers, orchestration and monitoring.

What Students Will Learn & Gain

• The complete DevOps lifecycle — students experience version control, continuous integration,
  continuous deployment, and monitoring as one connected pipeline, not isolated topics.
• Genuine Git/GitHub collaboration skills — branching, merging, resolving conflicts, and
  contributing to open-source projects (forking, pull requests) build real team-based coding experience.
• Industry-standard CI/CD practice — hands-on pipelines built with Jenkins and GitHub Actions
  mirror exactly what’s used in professional engineering teams today.
• Containers and orchestration — building custom Docker images and deploying/scaling
  applications on Kubernetes are core, high-demand DevOps engineering skills.
• Infrastructure as Code and observability — configuration management with Ansible, combined
  with monitoring/logging via Prometheus, Grafana and the ELK stack, rounds out a full SRE-style skill
  set.
• Forward-looking exposure — serverless computing and AI-powered predictive monitoring keep the
  course aligned with where the DevOps field is heading next.

Course Code: 25CS53ID | Contact Hours: 7 Hrs/week | Credits: 5 | Teaching Dept: Computer Science (CS)

A structured, hands-on introduction to penetration testing — teaching students to think, probe and report like a professional ethical hacker, within a clear legal framework.

What Students Will Learn & Gain

• A professional pentesting methodology — scoping, reconnaissance, exploitation and reporting
  are taught as a repeatable, disciplined process — not random ‘hacking’.
• Strong legal and ethical grounding — coverage of India’s IT Act 2000, CERT-In, and sector
  regulations (RBI, IRDAI, TRAI) ensures students understand exactly where the legal boundaries lie.
• Broad, hands-on attack-surface practice — network, wireless, web application (OWASP Top 10),
  cloud, mobile and IoT vulnerabilities are all explored through guided, safe exercises.
• Real industry tools — Nmap, Wireshark, Burp Suite and the Social Engineer Toolkit are used
  directly, building genuinely employable technical skills.
• Post-exploitation and reporting discipline — practicing persistence, lateral movement, and writing
  clear remediation reports mirrors what real penetration-testing consultants deliver to clients.
• A direct route to certification and jobs — content aligns closely with CEH-style skills, opening a
  clear path toward penetration-tester and security-analyst careers.