Python for Data Science Essentials

Master fundamental Python programming concepts and essential libraries for effective data manipulation and analysis, laying the groundwork for machine learning applications.

beginner level · 7h · 8 modules

  1. Python Basics: Data Types and Variables
    • Introduction to Python Data Types
    • Working with Variables
    • Basic Data Type Operations
    • Practice Data Type and Variable Usage
  2. Control Flow and Logic
    • Conditional Statements: If, Elif, Else
    • Loops: For and While
    • Loop Control Statements
    • Build a Simple Decision Maker
  3. Functions in Python
    • Defining and Calling Functions
    • Function Arguments and Return Values
    • Scope and Lambda Functions
    • Create a Reusable Calculator Function
  4. Introduction to NumPy for Numerical Operations
    • NumPy Arrays: Creation and Indexing
    • NumPy Array Operations
    • Basic NumPy Array Methods
    • Perform Array Calculations with NumPy
  5. Introduction to Pandas for Data Manipulation
    • Pandas Series: Creation and Basics
    • Pandas DataFrames: Creation and Overview
    • Reading Data with Pandas
    • Load and Inspect a Dataset with Pandas
  6. Data Analysis with Pandas
    • Selecting Data: Loc and Iloc
    • Filtering DataFrames
    • Basic Data Aggregation
    • Analyze Sales Data
  7. Build a Data Analysis Pipeline
  8. Predictive Modeling Data Preparation