Course Objective

Overview: Students will learn the basics of python and data preparation. Topics include: Python basics, lists, dictionaries, loops, functions, packages and libraries, Pandas, NumPy, querying databases, data cleaning, filtering, joining, aggregations, and outputs.

Course Outline

Part 1: Python Basics

  • Hello Python
    • Install software (anaconda)
    • The Jupyter notebook environment
    • Print(Hello World!)
    • Adding Comments
    • Variable types
    • Variable assignment
    • Calculations of with variables
    • Type conversions
  • Logic, Control Flow, and Filtering
    • Comparison operators
    • Boolean operators
    • If, elif, else
  • Python Lists – learn to store, access,
    and manipulate data in lists (helps
    working with big data)
    • Create a list
      • List of lists
      • Sub-setting list
  • Dictionaries
    • Create Dictionaries
    • Access Dictionaries
    • Dictionary Manipulation
    • Looping through Dictionary
  • Loops
    • While loop
    • For loop
  • Functions & Packages
    • What are Functions?
    • Methods
      • String methods
      • List methods
    • Packages
      • Import packages

Part 2: Python Intermediate

  • Dictionaries
    • Create Dictionaries
    • Access Dictionaries
    • Dictionary Manipulation
    • Looping through Dictionary
  • Numpy
    • Numpy Arrays vs Lists
    • 2D Numpy Arrays
    • Array Slicing
    • Numpy: Basic Statistics
  • Pandas & DataFrames
    • Pandas Basics
    • Importing/Formatting Data to DataFrame
    • Data Exploration and summary dataframes
    • Preparing data for Machine Learning
  • Matplotlib
    • Data Exploration with Charting:
      • Line plot
      • Scatter plot
      • Histogram
    • Brief overview of other charting libraries

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