• Gain an introduction to programming and begin writing pseudocode.
• Get acquainted with Python fundamentals, writing “Hello, World” and creating comments.

• Explore the concept of variables and differentiate between variable types.
• Create and re-assign numerical variables using common naming guidelines and numerical operators.
• Re-assign variables using variables and shorthand assignment operators.
• Create string variables, concatenate strings, and print complex structures.

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

• Define control flow and describe scenarios in which control flow would be helpful.
• Explore logical comparison. Explain different comparison and equality operators and use them to evaluate and compare statements.
• Get acquainted with Booleans, use if/elif/else conditionals to control program flow based on Boolean conditions, and use comparison operators in conditionals.
• Create and manipulate lists, adding and removing elements and printing out elements/list lengths.
• Understand the use of loops in programming. Implement for loops to iterate lists and range() to dynamically generate loops.
• Explain a while loop and its best use cases. Leverage while loops to control program flow.
• Dive into functions, identifying use cases, creating and calling functions, and returning values.
• Utilize parameters and arguments in functions. Implement keyword arguments.

Lab: Code a working Python program using control flow and functions.

• Describe object-oriented programming and provide examples of what could be described as an object.
• Differentiate between keys and values. Compare and contrast dictionaries and lists. Use dictionaries to solve common problems in Python.
• Distinguish between lists and sets. Create variables that hold sets. Use sets to determine the frequency of elements.
• Compare and contrast classes and objects. Define classes. Instantiate objects from classes.
• Explain the use of the __init__ method. Understand class variables versus instance variables. Create classes with default instance variables.
• Implement inheritance. Describe what has been inherited from one class to another and when to use inheritance.

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

• Define variable scope and explain the order of scope precedence that Python follows when resolving variable names. Use the global keyword to access global variables.
• Understand common types of errors and use print statements to troubleshoot. Implement the try-except code to handle errors.
• Define when floats are created, use escape characters, and perform basic data type conversion.

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

• Review Python basics covered so far.
• Get acquainted with key components of intermediate Python coding, such as scripting, abstraction, modules, and libraries and APIs.
• Define the uses of scripting and write scripts that perform file I/O and take user input.
• Explore code abstraction. Use itertools to implement efficient looping and list comprehensions to concisely create lists.
• Add libraries and modules to Python programs. Create programs utilizing PyTime. Navigate library documentation.
• Describe what an application programming interface (API) is and why we might use one. Identify common APIs on the web. Call APIs.

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

• Review Python basics and intermediate skills covered so far.
• Explore how Python is used by data scientists through a case study.
• Use Pandas to read in data sets. Understand the integrity and characteristics of data sets. Filter, sort, and manipulate DataFrame Series.
• 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.
• Implement different types of graphs on a given data set using Pandas.
• Identify and handle missing values with Pandas. Implement groupby() statements for specific segmented analysis. Use apply() functions to clean data with Pandas.

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

• Review Python basics and intermediate skills covered so far.
• Explore how Python is used by web developers with a case study.
• Differentiate between web applications, websites, front-end, and back-end. Apply basic HTML and CSS.
• Define Flask, understand how values are passed between websites and the Flask back-end and create simple Flask websites.
• Create routes using Flask. Pass variables into routes.
• Implement simple templates in Flask apps. Pass variables into templates.
• Add data from APIs to Flask applications.

Lab: Create a working web application using Flask.

• Review what’s been covered throughout the course.
• Choose a project based on your interests and use Python skills to build an application.
• Identify ways to keep learning.

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