Full Stack Data Science with GenAI

Welcome to “Full Stack Data Science with GenAI – Learn by Building Projects” – the only beginner-friendly course that takes you from zero to job-ready in Data Science and Generative AI through real-world, hands-on projects.

Whether you’re a complete beginner or someone looking to switch careers, this course is designed to make complex topics simple and practical. We focus on "learning by doing" – no endless theory, no fluff. Just real skills, built step-by-step.

What Makes This Course Unique?

1. Project-Based Learning – Build real data science and AI applications as you learn
2. Covers Both Traditional ML and Modern GenAI – Get ahead in today’s job market
3. Beginner Friendly – No prior experience in programming, math, or data science needed
4. Career-Focused – Includes resume tips and guidance to land your first data job

What You’ll Learn

1. Data science fundamentals and workflows
2. Python programming for data analysis and ML
3. Key math and statistics concepts for data science
4. Data cleaning, EDA, and feature engineering
5. Supervised and unsupervised machine learning
6. Real-world projects for your portfolio
7. Generative AI (GenAI) and Agentic AI concepts
8. Building GenAI applications like text and image generators
9. Resume building and interview tips to get job-ready

Course Modules

1. Intro to Data Science & GenAI
2. Python for Data Science
3. Math for Data Science
4. Data Collection & Cleaning
5. EDA & Feature Engineering
6. Supervised Learning (with Projects)
7. Unsupervised Learning (with Projects)
8. Real-World Projects
9. GenAI & Agentic AI
10. GenAI Projects
11. Resume Building
12. Tips to Get Interview Calls

Who Is This Course For?

1. Absolute beginners
2. Students or professionals wanting to learn data science
3. Tech enthusiasts exploring GenAI
4. Career switchers aiming for data/AI roles
5. Anyone who prefers hands-on learning with real projects

Tools & Technologies Used

1. Python, Pandas, NumPy, Matplotlib, Scikit-learn
2. GenAI tools (like OpenAI APIs, Hugging Face, or similar)
3. Jupyter Notebooks, Google Colab
4. Basic deployment tools (optional)

By the end of this course, you’ll not only understand the full data science pipeline — you’ll have built and deployed projects that prove it.

Let’s get started – enroll now and begin your data science journey!