Generative AI & ML Job Oriented Program 

offered by Prepzee

Module 1 : Python Fundamentals and Data Structures

Python Basics: Syntax, Variables, Data Types

Input and Output (print(), input())

Basic Operators and Expressions

Conditional Statements (if, elif, else)

Loops (for, while)

Module 2 : File Handling and Data Wrangling with Numpy

File Handling: Reading and Writing Files (Text and CSV)

Parsing CSV Files with the csv Module

Error Handling with Try/Except Blocks

Introduction to Numpy Arrays and Array Operations

Reshaping, Indexing, and Slicing Numpy Arrays

Module 3 : Unsupervised Learning in ML

K-Means Clustering

Dimensionality Reduction

Linear Discriminant Analysis (LDA)

Principal Component Analysis (PCA)

Module 4 : Introduction to Deep Learning and Framework Basics

Overview of Deep Learning and Neural Networks

Difference between DS VS ML VS AI

Setting up TensorFlow, Keras, and PyTorch environments

Introduction to Tensors, Computation Graphs, and Autograd

Basics of building and training models in TensorFlow and PyTorch

Module 5 : Deep Neural Networks and Core Architectures

Artificial Neural Networks (ANN)

Convolutional Neural Networks (CNN)

Recurrent Neural Networks (RNN)

Introduction to Transfer Learning

Module 6 : Advanced Neural Networks (GNN, LSTM)

Long Short-Term Memory Networks (LSTM)

Graph Neural Networks (GNN)

Advanced Recurrent Architectures: Bidirectional RNN, GRU

Hyperparameter Tuning and Model Optimization