Introduction to Programming

• Define programming.
• Begin writing pseudocode.

Introduction to Python

• Get acquainted with the Python programming language.
• Write “Hello, World” and create comments.

Introduction to Programming With Variables

• Explore the concept of variables.
• Differentiate between variable types.

Numerical Variables

• Create and re-assign numerical variables using common naming guidelines and numerical operators.

Reassigning Variables

• Re-assign variables using variables and shorthand assignment operators.

String Variables

• Create string variables, concatenate strings, and print complex structures.

Lab 1

• Apply what you’ve learned to create a working Python program.

Introduction to Control Flow

• Define control flow.
• Describe scenarios in which control flow would be helpful.

Logical Comparison

• Explore logical comparison.
• Explain different comparison and equality operators and use them to evaluate and compare statements.

Boolean Conditionals

• Get acquainted with Booleans.
• Use if/elif/else conditionals to control program flow based on Boolean conditions.
• Use comparison operators in conditionals.

Lists

• Create variables that hold lists.
• Print out specific elements in a list.

List Operations

• Print the length of a list.
• Add elements to and remove elements from lists.

For Loops

• Understand the use of loops in programming.
• Use for loops to iterate lists.
• Use range() to dynamically generate loops.

While Loops

• Explain a while loop and its best use cases.
• Use a while loop to control program flow.

Functions

• Identify when to use a function.
• Create and call functions.
• Return values from functions.

Function Arguments

• Utilize parameters and arguments in functions.
• Implement keyword arguments.

Lab 2

• Code a working Python program using control flow and functions.

Introduction to Object-Oriented Programming

• Describe object-oriented programming.
• Provide examples of what could be described as an object.

Dictionaries

• Differentiate between keys and values.
• Compare and contrast dictionaries and lists.
• Use dictionaries to solve common problems in Python.

Sets

• Distinguish between lists and sets.
• Create variables that hold sets.
• Use sets to determine the frequency of elements.

Classes

• Compare and contrast classes and objects.
• Define classes.
• Instantiate objects from classes.

Class Instance Variables

• Explain the use of the __init__ method.
• Understand class variables versus instance variables.
• Create classes with default instance variables.

Inheritance

• Implement inheritance.
• Describe what has been inherited from one class to another.
• Explain when to use inheritance.

Lab 3

• Continue building on the previous project, applying Python classes and dictionaries.

Variable Scope

• Define variable scope.
• Explain the order of scope precedence that Python follows when resolving variable names.
• Use the global keyword to access global variables.

Debugging Principles and Techniques

• Understand common types of errors.
• Use print statements to troubleshoot.
• Implement the try-except code to handle errors.

Intermediate Variables

• Define when floats are created.
• Use escape characters.
• Perform basic data type conversion.

Lab 4

• Continue building the Python program you started in previous labs by incorporating error troubleshooting.

Introduction to Intermediate Python

• Review Python basics covered so far.
• Get acquainted with key components of intermediate Python coding, such as scripting, abstraction, modules, and libraries and APIs.

File I/O

• Define the uses of scripting.
• Write scripts that perform file I/O.

User Input

• Write scripts that take user input.

Code Abstraction: Itertools

• Use itertools to implement efficient looping.

Code Abstraction: List Comprehensions

• Use list comprehensions to concisely create lists.

Modules and Libraries

• Add libraries and modules to Python programs.
• Create programs utilizing PyTime.
• Navigate library documentation.

APIs

• Describe what an application programming interface (API) is and why we might use one.
• Identify common APIs on the web.
• Call APIs.

Lab 5

• Expand upon the previous lab, applying I/O, code abstraction, and libraries to a Python program.

Introduction to Python for Data Science

• Review Python basics and intermediate skills covered so far.
• Explore how Python is used by data scientists through a case study.

Pandas

• Use Pandas to read in data sets.
• Understand the integrity and characteristics of data sets.
• Filter, sort, and manipulate DataFrame Series.

Data Visualization

• Describe why data visualization is important.
• Identify the characteristics of a great data visualization. Identify when you would use bar charts, pie charts, scatterplots, and histograms.

Plotting With Pandas

• Implement different types of graphs on a given data set using Pandas.

Pandas Best Practices

• Identify and handle missing values with Pandas.
• Implement groupby() statements for specific segmented analysis.
• Use apply() functions to clean data with Pandas.

Data Science and Python Lab

• Building off the previous lab, apply Pandas to solve a problem in a program.

Introduction to Python for Web Development

• Review Python basics and intermediate skills covered so far.
• Explore how Python is used by web developers with a case study.

Introduction to Web Applications

• Differentiate between web applications, websites, front-end, and back-end.
• Apply basic HTML and CSS.

Flask

• Define Flask and understand how values are passed between websites and the Flask back-end.
• Create simple Flask websites.

Flask Routing

• Create routes using Flask.
• Pass variables into routes.

Flask Templates

• Implement simple templates in Flask apps.
• Pass variables into templates.

Flask Requests

• Add data from APIs to Flask applications.

Web Application Lab

• Create a working web application using Flask.

Review and Q/A

• Review what’s been covered throughout the course.

Final Project

• Build a program that reinforces the skills you’ve learned in the course.

Course Summary

• Recap what you’ve learned and identify ways to keep learning.