Session 1: Introduction to Data Science

Session 2: Python Basics for Data Science

Session 3: Data Handling with Pandas

Session 4: NumPy for Numerical Computing

Session 5: Data Visualization with Matplotlib

Session 6: Advanced Data Visualization with Seaborn

Session 7: Machine Learning Overview

Session 8: Data Preprocessing and Feature Engineering

Session 9: Supervised Learning – Regression

Session 10: Supervised Learning – Classification

Session 11: Model Evaluation and Cross-validation

Session 12: Unsupervised Learning – Clustering

Session 13: Ensemble Learning

Session 14: Introduction to Neural Networks

Session 15: Deep Learning with TensorFlow

Session 16: Convolutional Neural Networks (CNNs)

Session 17: Recurrent Neural Networks (RNNs)

Session 18: Generative AI & GANs

Session 19: Working with PySpark

Session 20: Natural Language Processing (NLP) with NLTK

Session 21: Hadoop Basics

Session 22: Text Classification with NLP

Session 23: Data Visualization with Tableau

Session 24: Introduction to Large Language Models (LLMs)