These are the main topics that we will explore in this course. These topics will be broken into Lectures, which is how we will organize each class.

• Essential Terminology
  • Program
  • Declaration
  • Expression
  • Control Flow
• Basic Data Types
  • Variables
  • Integers & Floats
  • Strings
  • Booleans
• Conditionals
  • Booleans
  • Comparison Operators
  • Logical Operators
  • Conditional Statements
• Lists
  • Creating & Accessing Lists
  • List Updates & Operators
  • Tuples & Sets
• Dicts
  • Creating Dicts
  • Accessing Dict Data
  • Manipulating Dict Data
• Loops
  • while Loops
  • for Loops
  • Iterating over Dicts
  • Control Flow & Infinite Loops
  • Nested Loops
• Functions
  • Elements of a Function
  • Function Arguments & the return Statement
  • Anonymous Functions
  • Variable Scope
• Modules
  • Importing & Using Modules
  • Module Scope
  • Common & Featured Modules
• Classes & Inheritance
  • High-Level Overview
  • Class vs. Instance Variables
  • Class Definition Example 1: Basic Elements
  • Class Definition Example 2: Child Classes & Inheritance
  • Review of Classes & Inheritance
• Data Science
  • What, Why, & Who?
  • Real Applications
  • The Data Science Lifecycle
  • Python Tools for Data Science
• Pandas Basics
  • Capabilities of Pandas
  • NumPy ndarrays
  • Index
  • Series
  • DataFrames
  • Setting Up Our First Data Science Project
• Data Pre-Processing with Pandas
  • Wine Review Data Dictionary
  • Wrangling Data
  • Selecting Data
  • Cleaning & Organizing Data
• Exploratory Data Analysis with Pandas
  • Categorical Data
  • Joining & Concatenating
  • Grouping
  • Filtering
  • Descriptive Statistics
• Data Visualization
  • coming soon...
• Course Review
  • Data Structures
  • Control Flow
  • OOP (Object-Oriented Programming)
  • Data Science Strategy
  • Pandas
• Python Project Ideas