1. Objective

An embedded system is a combination of hardware and software provided that both should be synchronized with each other. The Arduino is an open-source computer hardware/software platform for building digital devices and interactive objects that can sense and control the physical world around them. In this course you will learn how the Arduino platform works in terms of the physical board and libraries and the IDE (Integrated Development Environment). The course will also cover programming the Arduino using C code and accessing the pins on the board via the software to control external devices. With this module student will get firm career growth in Electronics domain.

Program: Model based Development for Automotive Domain using MATLAB Software

• Dspacetargetlinks blocks.
• Code generation for the logic Development.
• MIL, SIL and PIL Testing.
• StateFlow and State transition diagrams.
• MAAB Guidelines, MXAM

*Note: Program 1 is conducted through online mode only.

Program 1: Model based Development for Automotive Domain using MATLAB Software

• Dspacetargetlinks blocks.
• Code generation for the logic Development.
• MIL, SIL and PIL Testing.
• StateFlow and State transition diagrams.
• MAAB Guidelines, MXAM

Program 2: Model based Development for Power Electronics Using DSP Controller

• Introduction to DSP Controller LAUNCHXL-F28379D using MATLAB.
• Code generation using Model based Development (MBD).
• MIL, SIL, PIL and HIL Testing using DSP Controller for:
  • Basic PWM Generation for DC-DC Converters.
  • Single phase Bipolar Sine PWM using Epwm & GPIO Blocks.
  • Single phase Unipolar Sine PWM using Epwm & GPIO Blocks.
  • Three phase 120 and 180 degrees mode for Induction motor.
  • Three phase Sine PWM for 3 phase Inverter.
  • Space Vector PWM for 3 phase Inverter.

Program Overview

1. Embedded C Programming
2. Arduino, 8051, and Raspberry Pi
3. Proteus and Keil uVision Software
4. Sensor Interfacing (ADC, I2C, SPI, UART)
5. IOT & Embedded Systems
6. Hands on Projects

*Note: Program will be conducted through online mode only.

Module 1: Software Installation and component familiarization

• Introduction to Proteus software
• Familiarization of PCB components
• Installation of Proteus software
• Testing of Components
• Safety precautions in PCB Design

Module 2: Design and Simulation circuits in proteus software

• Adding Library and packages to software
• Familiarizing with component and rating selection
• Designing and simulating of electronic circuits
• Integrated circuit based simulation and programming
• Troubleshooting
• Exporting the simulated circuit to pdf

Module 3: Design and preparation of PCB track layout

• Design and preparation of PCB track layout
• Auto routing and layout extraction
• Practice via manual routing on PCB track
• 3D visualization of the prepared track
• Track exportation to top/bottom copper domain

Module 4: Fabrication process of circuits in zero’PCB and copper clad

• Printing of design on copper clad sheet using heat transfer method
• Etching of processing using FeC13
• Drilling of circuit board
• Component affixing and soldering on the prepared board
• Testing and calibration
• Circuit design and fabrication in zero PCB

Program Overview

1. Manual Testing
2. Prompt Engineering
3. Java Programming Language
4. Selenium Web Driver
5. TestNG Framework
6. Page Object Model(POM)
7. API Testing (Postman & Rest Assured)
8. SQL
9. Cucumber framework
10. Jira-Bug Tracking & Agile Boards
11. GitHub-Version Control
12. Resume & Interview Guidance

*Note: Program will be conducted through online mode only.

PHASE 0: Foundation (2–3 weeks)

Mathematics: Focus only on what is used in DS & AI.

• Statistics: Mean, median, variance, std deviation, Probability, Bayes theorem, Hypothesis testing, p-value.
• Linear Algebra: Vectors, matrices, Dot product, transpose.
• Calculus: Derivatives (for optimization intuition).

PHASE 1: Programming & Data Handling (1 month)

Python (Core Skill): This is mandatory.

• Variables, loops, functions, List/dict comprehensions, File handling.
• Libraries: NumPy (numerical operations), Pandas (data cleaning & analysis), Matplotlib/Seaborn (visualization).

PHASE 2: Data Analysis & Visualization (3–4 weeks)

Exploratory Data Analysis (EDA): Learn to think like a data analyst.

• Data cleaning strategies, Handling missing & outliers, Feature distributions, Correlation analysis.

PHASE 3: Machine Learning (1.5–2 months)

Classical Machine Learning: Use Scikit-learn.

• Supervised: Linear/Logistic Regression, Decision Trees, Random Forest, SVM.
• Unsupervised: K-Means, PCA.
• Evaluation: Accuracy, Precision, Recall, F1, ROC-AUC.

PHASE 4: AI / Deep Learning (1–1.5 months)

Deep Learning Foundations: Neural Networks, Activation functions, Backpropagation, Loss functions, Optimizers (SGD, Adam).

Frameworks: TensorFlow + Keras OR PyTorch.

PHASE 5: Specializations (1–2 months)

• NLP: Text preprocessing, TF-IDF, Word embeddings, Transformers, LLM APIs.
• Computer Vision: Image preprocessing, CNNs, Transfer learning.
• Time Series: ARIMA, LSTM.

PHASE 6: Data Engineering Basics (3–4 weeks)

• SQL (PostgreSQL / MySQL), Data pipelines, ETL concepts, Apache Airflow basics.

PHASE 7: Deployment & MLOps (3–4 weeks)

• Flask / FastAPI, REST APIs, Docker, CI/CD basics.

PHASE 8: Projects (Critical for Jobs)

Must-have: End-to-end ML project, AI app with frontend, Real dataset + deployment.

PHASE 1: Web Foundations (3–4 weeks)

• HTML5: Semantics, Forms, Accessibility (ARIA), SEO basics, Media tags.
• CSS3: Box Model, Flexbox, Grid, Responsive Design, Animations, Tailwind CSS.

PHASE 2: JavaScript Core (5–6 weeks)

• ES6+: Closures, DOM, Async/Await, Fetch API, Events, Scopes.

PHASE 3: Tooling & Ecosystem (1–2 weeks)

• Git & GitHub, NPM/Yarn, Vite, Browser DevTools.

PHASE 4: React.js (5–6 weeks)

• JSX, Hooks (useState, useEffect, useContext), React Router, Context API, Performance optimization.

PHASE 5: Angular (4–5 weeks)

• TypeScript, Angular CLI, Services & DI, RxJS (Observables), Routing.

PHASE 6: UI/UX & Design (1–2 weeks)

• WCAG Accessibility, Figma, Performance (Lighthouse), Mobile-first design.

PHASE 7 & 8: Testing & Deployment

• Testing: Jest, Cypress.
• Deployment: Netlify, Vercel, CI/CD, SEO.

PHASE 9: Portfolio & Job Readiness

Must-Have: React SPA with API, Angular Enterprise App, Responsive UI Clones.

PHASE 0: Core Computer Science Basics (2 weeks)

• How the web works (HTTP/HTTPS), Client–Server architecture, Request–Response cycle.
• Status codes (200, 400, 401, 404, 500), JSON & REST concepts.

PHASE 1: Programming Foundations (3–4 weeks)

• Option A: Node.js: Async/await, Event loop, Promises, Error handling.
• Option B: Python: Virtual environments, Exception handling, Async basics.

PHASE 2: Backend Frameworks (4–6 weeks)

• Node.js: Express.js / Fastify, Middleware, Routing, Validation.
• Python: FastAPI (recommended), Flask, Django basics.

PHASE 3: Databases (3–4 weeks)

• SQL: PostgreSQL / MySQL, Joins, Indexing, Transactions.
• NoSQL: MongoDB, Document modeling, Aggregations.
• ORMs: Prisma/Sequelize (Node), SQLAlchemy (Python).

PHASE 4: API Design & Security (2–3 weeks)

• RESTful principles, Pagination, Versioning, Idempotency.
• Security: JWT, OAuth, Password hashing (bcrypt).

PHASE 5: Advanced Backend (4 weeks)

• Caching (Redis), Rate limiting, Load balancing, Background jobs (queues).
• Security: SQL Injection, XSS/CSRF, CORS, Environment variables.

PHASE 6 & 7: Quality & Deployment (5 weeks)

• Testing: Unit & Integration tests (Jest/PyTest), Postman mocking.
• DevOps: Docker, Nginx (reverse proxy), AWS/GCP basics, CI/CD.

PHASE 8: Real-World Projects (Critical)

Must-build: Auth System, E-commerce API, Payment Integration, Microservice-based API.