Python Mastery for Data Science & MLOps: From Zero to Pro!

Here’s your ultimate roadmap to becoming a Python pro for Data Science and MLOps, packed with all the essentials:

Part 1: Getting Started with Python Basics

1. Python Fundamentals

• Install Python (Anaconda is recommended for data science beginners).
• Cover basics: variables, data types, loops, conditionals, and functions.
• Tools: Jupyter Notebook, Colab.

1. Essential Libraries

• Start with numpy for arrays, pandas for data manipulation, matplotlib & seaborn for plotting.

Part 2: Data Science Foundations

1. Data Wrangling with Pandas

• Learn data cleaning, filtering, and transforming.
• Practice merging datasets, group operations, and handling missing values.

1. Data Visualization

• Dive deep into matplotlib and seaborn for plotting.
• Learn to create insightful charts, histograms, scatter plots, and more.

1. Statistics and Probability with Python

• Basics of probability, distributions, and statistical testing.
• Use scipy for statistical calculations.

Part 3: Machine Learning Essentials with Scikit-Learn