Programming with Python

This course aims to build foundations for programming with python and covers 5 main areas. Each area contains modules, concepts and problem sets.

💡 Prerequisites for the Course

To ensure a smooth learning experience, make sure you meet the following prerequisites:

Hardware:

A functional laptop or desktop computer
A reliable internet connection

Software:

A modern web browser (preferably Google Chrome)
Zoom for online sessions

Knowledge:

Basic understanding of calculus

1. Getting Started with Programming

Creativity, Motivation, and Basics: Understand why programming is important, how it fosters creativity, and the basics of writing programs.
Understanding Python and Programs: Learn about computer hardware architecture, interpreters vs. compilers, and the building blocks of programs.
Debugging and Problem Solving: Identify common errors, debug effectively, and build confidence in troubleshooting.

2. Core Concepts

Variables, Expressions, and Statements: Explore values, types, operators, and how to write meaningful and error-free statements.
Conditional Execution (if/else): Master boolean logic, alternative executions, and nested/chained conditions for smarter decision-making.
Loops and Iteration: Learn while/for loops, loop patterns (counting, summing, max/min), and how to handle infinite loops.

3. Working with Data

Strings: Slicing and Methods: Understand strings as sequences, perform slicing, and use string methods for manipulation and parsing.
Files: Reading and Writing: Learn file handling basics, how to read/write text files, and search through file contents effectively.
Lists, Dictionaries, and Tuples: Explore these core data structures, their operations, traversal, and how they interact with other elements like strings.

4. Advanced Programming

Functions: Writing and Using Them: Use built-in functions, create custom ones, and understand parameters, arguments, and flow of execution.
Object-Oriented Programming (OOP): Learn to manage larger programs, work with classes/objects, understand inheritance, and apply OOP principles effectively.
Regular Expressions: Master pattern matching, data extraction, and advanced text parsing techniques.

5. Real-World Applications

Web Programming and APIs: Learn HTTP basics, retrieve data using urllib, scrape web pages with BeautifulSoup, and work with APIs using XML/JSON.
Databases and SQL: Understand database concepts, create and query tables, and model relationships with multiple tables.
Visualizing Data: Build visualizations using geocoded data, explore networks, and analyze real-world datasets.

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Below is a detailed list of the course contents

This course covers a wide range of topics and can be tailored to meet the specific needs of the student. Modules and concepts can be customized, expanded, or omitted based on individual preferences, with the option to focus on areas such as Web Development, Data Visualization, Data Analysis, or Machine Learning, among others.

Each section includes dedicated discussions and hands-on exercise sessions to reinforce learning.

Course Content

1. Why Should You Learn to Write Programs?

1.1 Creativity and motivation
1.2 Computer hardware architecture
1.3 Understanding programming
1.4 Words and sentences
1.5 Conversing with Python
1.6 Terminology: Interpreter and compiler
1.7 Writing a program
1.8 What is a program?
1.9 The building blocks of programs
1.10 What could possibly go wrong?
1.11 Debugging
1.12 The learning journey
1.13 Discussion / Revision
1.14 Exercises

2. Variables, Expressions, and Statements

2.1 Values and types
2.2 Variables
2.3 Variable names and keywords
2.4 Statements
2.5 Operators and operands
2.6 Expressions
2.7 Order of operations
2.8 Modulus operator
2.9 String operations
2.10 Asking the user for input
2.11 Comments
2.12 Choosing mnemonic variable names
2.13 Debugging
2.14 Discussion / Revision
2.15 Exercises

3. Conditional Execution

3.1 Boolean expressions
3.2 Logical operators
3.3 Conditional execution
3.4 Alternative execution
3.5 Chained conditionals
3.6 Nested conditionals
3.7 Catching exceptions using try and except
3.8 Short-circuit evaluation of logical expressions
3.9 Debugging
3.10 Discussion / Revision
3.11 Exercises

4. Functions

4.1 Function calls
4.2 Built-in functions
4.3 Type conversion functions
4.4 Math functions
4.5 Random numbers
4.6 Adding new functions
4.7 Definitions and uses
4.8 Flow of execution
4.9 Parameters and arguments
4.10 Fruitful functions and void functions
4.11 Why functions?
4.12 Debugging
4.13 Discussion / Revision
4.14 Exercises

5. Iteration

5.1 Updating variables
5.2 The while statement
5.3 Infinite loops
5.4 Finishing iterations with continue
5.5 Definite loops using for
5.6 Loop patterns
5.6.1 Counting and summing loops
5.6.2 Maximum and minimum loops
5.7 Debugging
5.8 Discussion / Revision
5.9 Exercises

6. Strings

6.1 A string is a sequence
6.2 Getting the length of a string using len
6.3 Traversal through a string with a loop
6.4 String slices
6.5 Strings are immutable
6.6 Looping and counting
6.7 The in operator
6.8 String comparison
6.9 String methods
6.10 Parsing strings
6.11 Formatted String Literals
6.12 Debugging
6.13 Discussion / Revision
6.14 Exercises

7. Files

7.1 Persistence
7.2 Opening files
7.3 Text files and lines
7.4 Reading files
7.5 Searching through a file
7.6 Letting the user choose the file name
7.7 Using try, except, and open
7.8 Writing files
7.9 Debugging
7.10 Discussion / Revision
7.11 Exercises

8. Lists

8.1 A list is a sequence
8.2 Lists are mutable
8.3 Traversing a list
8.4 List operations
8.5 List slices
8.6 List methods
8.7 Deleting elements
8.8 Lists and functions
8.9 Lists and strings
8.10 Parsing lines
8.11 Objects and values
8.12 Aliasing
8.13 List arguments
8.14 Debugging
8.15 Discussion / Revision
8.16 Exercises

9. Dictionaries

9.1 Dictionary as a set of counters
9.2 Dictionaries and files
9.3 Looping and dictionaries
9.4 Advanced text parsing
9.5 Debugging
9.6 Discussion / Revision
9.7 Exercises

10. Tuples

10.1 Tuples are immutable
10.2 Comparing tuples
10.3 Tuple assignment
10.4 Dictionaries and tuples
10.5 Multiple assignment with dictionaries
10.6 The most common words
10.7 Using tuples as keys in dictionaries
10.8 Sequences: strings, lists, and tuples - Oh My!
10.9 List comprehension
10.10 Debugging
10.11 Discussion / Revision
10.12 Exercises

11. Regular Expressions

11.1 Character matching in regular expressions
11.2 Extracting data using regular expressions
11.3 Combining searching and extracting
11.4 Escape character
11.5 Summary
11.6 Bonus section for Unix/Linux users
11.7 Debugging
11.8 Discussion / Revision
11.9 Exercises

12. Networked Programs

12.1 Hypertext Transfer Protocol - HTTP
12.2 The world’s simplest web browser
12.3 Retrieving an image over HTTP
12.4 Retrieving web pages with urllib
12.5 Reading binary files using urllib
12.6 Parsing HTML and scraping the web
12.7 Parsing HTML using regular expressions
12.8 Parsing HTML using BeautifulSoup
12.9 Bonus section for Unix/Linux users
12.10 Discussion / Revision
12.11 Exercises

13. Using Web Services

13.1 eXtensible Markup Language - XML
13.2 Parsing XML
13.3 Looping through nodes
13.4 JavaScript Object Notation - JSON
13.5 Parsing JSON
13.6 Application Programming Interfaces
13.7 Security and API usage
13.8 Discussion / Revision

14. Object-Oriented Programming (OOP)

14.1 Managing larger programs
14.2 Getting started
14.3 Using objects
14.4 Starting with programs
14.5 Subdividing a problem
14.6 Our first Python object
14.7 Classes as types
14.8 Object lifecycle
14.9 Multiple instances
14.10 Inheritance
14.11 Summary
14.12 Discussion / Revision

15. Using Databases and SQL

15.1 What is a database?
15.2 Database concepts
15.3 Database Browser for SQLite
15.4 Creating a database table
15.5 Structured Query Language summary
15.6 Multiple tables and basic data modeling
15.7 Data model diagrams
15.8 Automatically creating primary keys
15.9 Logical keys for fast lookup
15.10 Adding constraints to the data database
15.11 Sample multi-table application
15.12 Many to many relationships in databases
15.13 Modeling data at the many-to-many connection
15.14 Summary
15.15 Debugging
15.16 Discussion / Revision

16. Visualizing Data

16.1 Building an OpenStreetMap from geocoded data
16.2 Visualizing networks and interconnections
16.3 Visualizing mail data

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