Data Science 2.0 Roadmap

Becoming a modern Data Scientist is no longer about coding a few ML models in isolation. It combines programming, statistics, machine learning, and AI integration into real-world, deployable solutions. This is Data Science 2.0 — you don’t just analyze data, you turn it into intelligent systems.

Stage 1: Python & Core Programming

Goal: Build coding fluency and understand programming fundamentals.

• Python basics: variables, loops, functions, objects
• Data structures: lists, dictionaries, tuples
• Object Oriented Programming
• GitHub for version control and collaboration

Example Projects:

• Calculator and To-Do List app
• Automated web scraper
• Portfolio hosted on GitHub

Stage 2: Data Manipulation & Analysis

Goal: Learn to work with structured datasets.

• Pandas for data manipulation
• NumPy for numerical computing
• Jupyter workflows
• SQL for querying databases