Data Science Roadmap

Chapter 1: Introduction to Data Science

• Data Scientist vs Data Analyst vs Data Engineer
• Using Google Colab
• Introduction to Command Line (Unix/Linux)
• Version Control: GitHub
• Visual Studio Code Setup
• Getting Started with LinkedIn
• Building Your Online Presence: GitHub and Kaggle Portfolio
• Visual Studio Code Editor

Chapter 2: Build a Strong Foundation

• Comprehensive Python Programming for Data Science
• Probability Basics
• Bayesian vs. Frequentist Statistics
• Mastering Machine Learning: A 2025 Guide for Aspiring Practitioners

Chapter 3: Data Manipulation and Visualization

• Exploratory Data Analysis for Machine Learning
• Handling Imbalanced Data
• Dimensionality Reduction
• Mastering Data Cleaning: A Five-Step Framework for Analysts

Chapter 4: Machine Learning Fundamentals

• Reinforcement Learning

Chapter 5: SQL and Databases

Chapter 6: Deep Learning

• Phase Transitions in Recurrent Neural Networks (RNN): A Statistical Physics Perspective

Chapter 7: Specialized Topics

Chapter 8: Real-World Projects

Chapter 9: Develop Industry-Specific Knowledge

Chapter 10: Build Your Portfolio and Online Presence

Chapter 11: Prepare for Job Applications

• Strategies for Success in Data Science
• How to Become a Data Scientist in 2025