Course Content

Module 1: Foundations of Data Science

• Introduction to Data Science & Career Paths

• Excel for Data Analysis

• SQL for Data Extraction & Queries

Module 2: Python for Data Science

• Python Basics & Data Structures

• Libraries: NumPy, Pandas, Matplotlib, Seaborn

• Data Cleaning & Preprocessing

Module 3: Machine Learning

• Supervised vs Unsupervised Learning

• Regression, Classification, Clustering

• Model Evaluation & Tuning

Module 4: Deep Learning & AI

• Neural Networks & Backpropagation

• TensorFlow & PyTorch Basics

• Computer Vision & Natural Language Processing (NLP)

Module 5: Big Data & Cloud Computing

• Introduction to Big Data & Hadoop

• Spark for Data Processing

• Cloud Platforms (AWS) for Model Deployment

Module 6: Data Visualization & Storytelling

• Visualization with Matplotlib, Seaborn, Power BI/Tableau

• Dashboard Creation & Insights

• Communicating Results Effectively

Module 7: Real-World Projects & Deployment

• End-to-End Data Analysis Projects

• ML Model Deployment with Flask/Django

• Working with APIs & Automation

Module 8: Agile & Professional Skills

• Agile Methodology & Scrum

• Collaboration Tools (Git, GitHub, JIRA)

• Preparing for Data Science Interviews