Master Deep Learning Using MATLAB

Introduction to AI, ML & Deep Learning Concepts

Understanding Neural Networks - Layers, Neurons, Activation Functions

MATLAB Environment Setup & Deep Learning Toolbox Overview

Data Handling for Deep Learning - Images & Structured Data

Data Preprocessing & Visualization using MATLAB

Introduction to Neural Network Design in MATLAB

Building Basic Neural Network for Classification

Training Neural Networks & Understanding the Learning Process

Introduction to Convolutional Neural Networks (CNN) - MNIST Dataset

Build Image Classification Model (Object Recognition Use Case)

Model Evaluation & Accuracy Analysis

Hands-on Lab - Build Handwritten Digit Recognition

Performance Metrics for Deep Learning Models

Confusion Matrix & Error Analysis

Hyperparameter Tuning - Learning Rate, Epochs

Improving Model Accuracy & Reducing Overfitting

Working with Larger & Noisy Datasets

Mini Project - Surface Defect Detection Model for Manufacturing Images

Transfer Learning Concepts using Pretrained Models

Applying Deep Learning to Real-World Image Datasets

Signal/Data-Based Deep Learning Applications

Debugging & Improving Deep Learning Models

Model Deployment Concepts - MATLAB Integration

Final Project Planning - Problem Statement & Dataset Selection

Final Project Kickoff - Medical Image Classification System Design (e.g., Disease Detection)

Data Preparation & Image Preprocessing

Model Development using CNN / Transfer Learning

Model Testing, Optimization & Validation

Result Visualization & Output Interpretation

Version Control using Git & GitHub + Project Presentation & Career Guidance