MORE THAN JUST A COURSE
Python for Data Prep
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
- Create a 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
- Data Exploration with Charting:
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