Conquer Programming by Learning Python
Programming is a hugely useful skill...and it's frustratingly hard to learn, especially on your own.
Class details
Audience: People new to programming. No experience with either programming or Python is required.
Length: 2-5 days, depending on options chosen. Where possible, doing them in half-day segments tends to work best for new programmers, keeping them from being overwhelmed and giving them time to absorb things. The two-day option will introduce people to programming and is useful in time-constrained circumstances, but in my experience if you actually want to turn a student into a real programmer, they need more time and practice. So I recommend a minimum of three days.
Approach: Each topic starts with a very interactive, discussion-based lecture where I do live coding to explain concepts, punctuated by short student exercises to help students absorb the mechanics. These are followed by more challenging team-based exercise projects that combine two or three concepts to accomplish a realistic programming task. We regularly review the concepts learned so far and students have plenty of opportunity to ask about anything that needs more discussion. Students receive book-length HTML and Jupyter Notebook files of the entire class content.
Curriculum
Fundamentals (2 days)
Part 1: Programming
- Variables: What they are, and Python's unique approach
- Strings: Text for humans
- Functions: The building block of scripts
- If This Then That: Python code blocks and if/else statements
- Objects: Everything in Python is an object -- what does that mean, and how do you work with objects?
- Lists: Python is a language about lists
Part 2: Scripting
- Review of Part 1, with a team exercise
- Scripts: What they are, and how to use comments
- Importing code: Making use of libraries
- Formatting text: How to make your human-oriented output look good
- Files: Basic reading and writing
Part 3: Parsing
- Review of Parts 1-2, with team exercise
- Parsing strings: Basic yet powerful techniques for parsing string input without using regular expressions
- CSV: Using the built-in CSV module to parse spreadsheet data
- Sorting lists
- Sets: Usually overlooked in tutorials, sets help solve many common problems
Part 4: Reporting
- Review of Parts 1-3, with a team exercise
- Lists redux: Let's really nail this list stuff
- Dictionaries: A fancy kind of list that is like a little database
- Counter: Using libraries to solve problems
- Final exercise: Parse a spreadsheet, crunch the data, and write out a report
Optional topics
You can pick and choose among these based on your needs.
Regular Expressions
- An overview of regular expressions and how they work in Python
- Class exercises where we walk through solving a couple of typical parsing scenarios with regular expressions
- Optionally, a deeper dive into regular expressions, for students who will be doing a lot of text parsing
Unicode
- A fun (really!) review of the history of Unicode and why it came about
- A compelling demonstration of why Absolutely Every Programmer Should Understand Unicode
- A clear set of simple guidelines for how to handle Unicode and solve problems
Students are always surprised at how interesting this topic is (hey, I even discuss Klingon!), and they find that handling Unicode is actually quite easy if you understand what it's about.
Data Science
- Overview of data science support in Python
- Introduction to using Pandas to parse tabular data
- Examples of using the Pandas Series class to solve typical programming problems
- JSON parsing
- Databases: How to use the sqlite3 library to interact with a database
Automation and Workflow
- Command-line operations in Python: executing other scripts, etc.
- File handling: Copying and moving files around
- Websites: Accessing websites, using JSON
- Packaging code: How to create libraries for you and your team
Object-Oriented Programming
- Creating basic objects: What is this 'self' thing?
- Accessing built-in Python functionality: The 'dunder' methods
- Using inheritance to streamline code
This is a relatively basic overview of Object-Oriented Programming, which is all that 99% of students usually need. We don't cover more advanced topics like Properties, Decorators, and static methods, unless the students have a particular need for more extended coverage.