Computational thinking in Python from scratch

The course teaches systematic problem-solving through Python. You will learn: how to analyze a problem, how to divide and organize the problem into appropriate components, how to describe the problem in a computer language, how to test your programs.

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Course curriculum

1. Course learning outcomes
2. What is an algorithm?
3. Example algorithm
4. Algorithm highlights
5. IDLE introduction
6. IDLE installation
7. IDLE basics
8. IDLE class exercise
1. Module intro summary
2. Python interactive shell
3. Programming vs Mathematics
4. Variables
5. The assignment statement
6. Instruction ordering is important
7. Assignment vs. "Is Equal to"
8. Assignment statement workings-I
9. Assignment statement workings-II
10. Tracking updates to variables
11. Assignment vs Equations
12. Naming variables
13. Operator precedence
14. Integers and Decimals
15. int vs float variables
16. Mixing float and int variables
17. Explicit Type conversion
18. Approximation in float arithmetic
19. Class exercise
20. Strings
21. Strings are indexed
22. String slicing
23. Indexing errors in String slicing
24. String concatenation
25. Data Types
26. Operations on data types
27. Type conversion
28. Automatic Type conversion
29. Python is dynamically Typed
30. Summary
1. Module intro summary
2. Windchill calculation using Python interactive mode
3. Motivating Python scripts
4. What is a Module?
5. Writing first Python module
6. How to run a Python module?
7. Multiple Python statements on a line
8. Comments and readability
9. Docstrings
10. Trying different inputs
11. Sample run for input statement
12. More readable output
13. round() function
14. center() method
15. ljust() and rjust() methods
16. Demonstration: more readable output
17. The print statement
18. print with strings
19. Why program readability and style is important?
20. Info comments on top
21. Final example--compute radius from area of circle
22. The idea behind import
23. Class exercise
24. Class exercise solution
1. Module intro summary
2. Motivation for conditional statements
3. How does If-Else work? (Part-1)
4. How does If-Else work? (Part-2)
5. if-else construction (I)
6. if-else construction (II)
7. string example
8. if-else construction for a String example
9. Discussion of the previous solution
10. Relational operators
11. Boolean operations with Strings
12. Comparison operations with Strings
13. Relational operators in action
14. Example problem using String comparison
15. Indentation is important in Python
16. The If-Elif-Else construction
17. If-Elif-Else: How it works?
18. Equivalent scripts example
19. "Else" part is optional
20. Various if-else constructions
21. The and operation
22. Example-1: The and operation
23. Example-2: The and operation
24. Example-3: The and operation
25. The or operation
26. Example-1: The or operation
27. Example-2: The or operation
28. The not operator
29. A note on Boolean variables
30. Boolean variables for clarity
31. Summary example
32. The len function
33. Summary example solution (part-1)
34. Summary example solution (part-2)
35. Class exercise
36. Class exercise solution
37. Summary
1. Module intro summary
2. What is a function?
3. The process of implementing a function
4. Built-in functions
5. Function if Mathematics vs functions in Python
6. Modules
7. Our plan for learning functions in Python
8. Revisiting the import statement
9. math.floor, math.ceil, round, int
10. Finding out what's in a Module?
11. Importing modules--method 1
12. Importing modules--method 2
13. Importing modules--method 3
14. Pros and cons of different import methods
15. Building your own functions
16. How are functions defined?
17. A Square Root function
18. Fruitful functions
19. Making functions usable
20. Comparing our SimpleMath functions
21. Summary of what you need to know
22. Class exercise
23. Class exercise solution
1. Module intro summary
2. Let's talk about Modules
3. What does import allow?
4. What does import* allow?
5. Specific importing
6. Using stuff within a Module
7. Launching a Python computation
8. Example scenarios for Launching a Python computation
9. Function call vs function definition
10. How function call works? (Part-1)
11. How function call works? (Part-2)
1. Module intro summary
2. Data+Functions together
3. Three String methods
4. Designing count as a function vs method
5. Methods: The notation
6. String methods: count
7. Using count: An example
8. Designing find as a function vs method
9. Using find: A few examples
10. in: A handy Boolean device
11. Designing replace as a function vs method
12. Using replace: Some examples
13. replace does not modify the original String
14. The upper and lower methods
15. Some Boolean-valued methods
16. Boolean-valued methods: Examples
17. Useful String constants
18. String is a Module
19. Class exercise
20. Class exercise solution
1. Module intro summary
2. Iterating through a String
3. Using for statement to traverse a String
4. The reverse string problem
5. for-loop mechanics
6. Function for reversing strings
7. The number-of-digits problem
8. The number-of-digits problem: Solution
9. Class exercise
10. Class exercise solution
1. Module intro summary
2. Iteration through a String
3. for-loop mechanics with range
4. Summation example
5. Summation: How do we do it?
6. Summation solution code
7. for-loop mechanics with range
8. Counting: A special type of summation
9. Using for-loop to enumerate all possibilities
10. Finding the minimum value
11. More on for-loop range
12. Functions and for loops
13. Class exercise
14. Class exercise solution
1. Module intro summary
2. Generating random Integers
3. What does "random" mean?
4. Renaming imported functions
5. Random simulation: Coin toss
6. Coin toss: Sample outputs
7. Estimating probabilities: Dice roll
8. Discovery through simulation: An example
9. Generating random Floats (Part-1)
10. Generating random Floats (Part-2)
11. Uniform distribution illustration
12. Estimating the value of Pi using random numbers
13. An example computation of Pi
14. Estimating the value of Pi: Code (Part-1)
15. Estimating the value of Pi: Code (Part-2)
16. random.seed
17. Class exercise
18. Class exercise solution
19. TriStick game example (Part-1)
20. TriStick game example (Part-2)
21. TriStick game example (Part-3)
1. Module intro summary
2. Open-ended iteration
3. How does a while-loop work?
4. While-loop: Tracing the execution
5. The while-loop mechanism
6. Whie-loop: Indentation is important
7. Class exercise
8. Class exercise solution
9. Random walks
10. ShowRandomWalk.py implementation
11. The function RandomWalk(L)
12. Understanding the while-loop in random walk
13. The application script for random walk
14. The function AveRandomWalk()
15. Sample output for AveRandomWalk()
16. Class exercise
17. Class exercise solution
1. Module intro
2. Computing Square Root using while-loop
3. Template for while loops
4. The Up/Down sequence problem
5. Avoiding infinite loops
6. Class exercise
7. Class exercise solution
8. Fibonacci numbers and the Golden Ratio
9. Fibonacci numbers review
10. Generating Fibonacci numbers
11. Generating Fibonacci numbers using while-loop
12. Finding first Fibonacci number >= 1 million
13. Finding largest Fibonacci number < 1 million
14. Fibonacci ratios
15. Class exercise
16. Class exercise solution
1. Module intro
2. Loop-body returns
3. While-loop & for-loop solutions with loop body returns
4. Review: Variables, data types
5. Boolean variables example: Leap year
6. Boolean functions
7. Determining if a point is inside two squares
8. Exceptions
9. Assertions
10. Checking Pre, Post conditions
11. Class exercise
12. Class exercise solution
13. Type Checking
14. The try-except construction
15. Class exercise
16. Class exercise solution
17. break statement
18. break statement: A bad usage example
19. break statement: A good usage example (Pt-1)
20. break statement: A good usage example (Pt-2)
21. break statement: A good usage example (Pt-3)
22. Class exercise
23. Class exercise solution
1. Module summary
2. What is a list?
3. List length, accessing list items
4. List slicing
5. Lists in Python
6. Visualizing Lists
7. Lists vs Strings
8. List methods
9. List: append, extend, insert, sort
10. Void methods
11. List: pop, count
12. List: len, sum functions
13. Initializing small Lists
14. Working with big Lists
15. Big Lists: A List of square roots
16. Lists: A random walk example
17. Be careful about Types
18. Functions can return Lists
19. Lists example: Two dice rolls (Pt-1)
20. Lists example: Two dice rolls (Pt-2)
21. Lists example: Two dice rolls (Pt-3)
22. Lists example: Two dice rolls (Pt-4)
23. Lists example: Two dice rolls (Pt-5)
24. Class exercise
25. Class exercise solution
1. Module intro
2. Example: Diameter of a cloud of points (Pt-1)
3. Example: Diameter of a cloud of points (Pt-2)
4. Example: Diameter of a cloud of points (Pt-3)
5. Nested loops
6. Example: Diameter of a cloud of points (Pt-4)
7. Example: Diameter of a cloud of points (Pt-5)
8. Example: Diameter of a cloud of points (Pt-6)
9. Class exercise
10. Class exercise solution
1. Module intro
2. Lists of numbers to Lists of Strings
3. A note about sort
4. Strings vs Lists of Characters
5. Note on sum
6. Visualizing Lists of Strings
7. Subscript reasoning
8. Three upcoming examples
9. Example-1: Function that returns a list of Strings
10. Helper function RandString
11. Class exercise
12. Class exercise solution
13. Example-2: Reading a text file into a List of Strings
14. Opening and reading a file
15. Removing newline and carriage return characters
16. Using fileToStringList
17. Class exercise
18. Class exercise solution
19. Example-3: Multiple data items per line
20. .csv file format
21. ReadMe files
22. CensusData.csv: Which county had max population growth?
23. Class exercise
1. Module intro
2. Comparing Lists
3. Aliasing
4. Tracking changes
5. The is Operator
6. Making a copy of a List
7. Slices create new objects
8. List sort() and void functions
9. Understanding function calls
10. Example: The perfect shuffle (Pt-1)
11. Example: The perfect shuffle (Pt-2)
12. Example: The perfect shuffle (Pt-3)
13. Example: The perfect shuffle (Pt-4)
14. Example: The perfect shuffle (Pt-5)
15. Class exercise
16. Class exercise solution
1. Module intro
2. Dictionary example
3. The methods .keys and .values
4. Deleting a Dictionary item
5. Some questions
6. Checking a particular key in a Dictionary
7. Checking a particular value in a Dictionary
8. Extracting a Value
9. Adding an item to a Dictionary
10. Changing the value of an item
11. Dictionaries vs Lists
12. Dictionaries and Lists are Objects (I)
13. Dictionaries and Lists are Objects (II)
14. For-loops and Dictionaries
15. For-loops and Dictionaries
16. Printing a small Dictionary
17. More Dictionary examples and rules
18. Some common errors
19. A Dictionary application
20. Updating a Dictionary
21. stringToWordList function
22. Update function
23. Sample output
24. Class exercise
25. Class exercise solution
1. Module intro
2. A simple class definition
3. Why use Classes?
4. Classes and Types
5. How to define a class?
6. Calling the constructor creates an object
7. Objects: The folder metaphor
8. Visualizing an Object
9. The __str__ function
10. Computing a random point: Example-1
11. Computing a midpoint: Example-2
12. Methods
13. A Point class method: Dist
14. Using the Dist method
15. Method implementation
16. Visualizing a method call
17. Summary: Base Types vs Classes
18. Copying an Object
19. Methods vs Functions
1. Module intro
2. Visualizing a List of Points
3. Working with a List of Objects
4. A List of random Points
5. Operations on a List of Objects
6. Printing a List of Objects
7. A Disk intersection problem
8. A Class for representing Disks
9. RandomDisk function
10. When does a pair of Disks intersect?
11. The Intersects method
12. outsideAll function
13. Class exercise
14. Sorting Objects
15. Sorting in the census data problem (Pt-1)
16. Sorting in the census data problem (Pt-2)
17. Class exercise
1. Abstract Data Type (ADT)
2. ADTs in Python
3. Introduction to Stacks
4. Basic Stack operations
5. Stack applications
6. Example operations on Stack
7. Implementing Stack ADT
8. Stack: Constructor
9. Stack: Push
10. Stack: Pop
11. Stack: Print_stack()
12. Stack: Main script
13. Class exercise
14. Python's built-in support for Stacks
15. Stack implementation using Lists
16. Class exercise
17. Queue ADT
18. Queue operations
19. Queues in Computer Science
20. Example operations on Queue
21. Implementing Queue ADT
22. Queue: Constructor
23. Queue: Enqueue
24. Queue: Dequeue
25. Queue: Print
26. Class exercise
27. Class exercise solution
28. Updated Dequeue()
29. Issues with updated Dequeue()
30. Class exercise
31. Class exercise solution
1. Module intro
2. Multiplying fractions
3. Fraction class
4. Fraction: Constructor
5. Methods in Class Fraction
6. Fraction Class: negate method
7. Fraction Class: invert method
8. Operator overloading
9. Fraction Class: Overloading + Operator
10. Fraction Class: Overloading * Operator
11. More flexible __add__, __mul__
12. Caution with add, multiply
13. Example: Sum of a series
14. Class exercise
15. Class that supports computations with dates
16. Class variables
17. The Leap year problem
18. Class SimpleDate: Constructor
19. Class SimpleDate: Some methods
20. Class SimpleDate: Tomorrow method
21. Class SimpleDate: The __eq__ method
22. Class SimpleDate: The __add__ method
23. Class SimpleDate: The __sub__ method
24. Referencing a Class variable
25. Class exercise
26. More on copying Objects (Pt-1)
27. More on copying Objects (Pt-2)
28. More on copying Objects (Pt-3)
29. Class exercise
1. Learning objectives
2. Concept of recursion
3. How is recursion used in algorithms?
4. Iteration vs Recursion
5. Implementing Iteration
6. Implementing Recursion
7. Base cases and recursive cases
8. Recursive call
9. Base case and Recursive case
10. Recursion and Stack
11. How to write recursive functions?
12. Example: Factorial
13. Implementing factorial recursively
14. Recursive Factorial
15. Example: power(base, exponent)
16. Example: countVowels(s)
17. Multiple recursive calls
18. Class exercise
1. Module intro
2. Search problem
3. Linear Search (Pt-1)
4. Linear Search (Pt-2)
5. Linear Search: While-loop implementation
6. Binary Search
7. Binary Search efficiency
8. Binary Search implementation (Pt-1)
9. Binary Search example
10. Binary Search implementation (Pt-2)
11. Measuring execution time
12. Binary search vs linear search execution times
13. Using the timeit Module
14. Why benchmarking is important?
15. Class exercise
1. Module intro
2. Selection Sort: How it works? (I)
3. Selection Sort: How it works? (II)
4. How does Select work?
5. SelectionSort() implementation
6. Class exercise
7. Merging two sorted lists
8. Merge() function implementation
9. Merge() implementation using Pop
10. Merge Sort
11. Merge Sort: Toy example
12. How to manually use merge() to sort?
13. Recursive mergesort
14. Mergesort: Recursion tree
15. Some Conclusions
16. Class exercise
1. Analysis of Algorithms Issues
2. Baic approaches to algorithm analysis
3. Measuring algorithm efficiency
4. Factors impacting time efficiency
5. Drawbacks of reporting execution time
6. Theoretical analysis of algorithm efficiency
7. Review example: Calculating the Mean
8. Order of magnitude
9. Big-O
10. Rate of growth
11. Example: Rate of growth
12. Tightest upper bound
13. Best-, average-, worst-case
14. Simple array search algorithm
15. Comparing growth rates
16. Sum() example
17. magicSum() example
18. Simplifying the complexity analysis
19. General rules for complexity estimation
20. Important complexity rules
21. Practice problem-1
22. Practice problem-2
23. Complexity practice problems
24. Practice problem-3
1. Congratulations!

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523 lessons
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Computational thinking in Python from scratch

Course curriculum

Course introduction

The Assignment Statement and Types

Modules, Scripts, and I/O

Conditional Execution

Modules and Functions

How Modules and Functions Work

String Methods

Iteration: Strings

Iteration with range

Random Simulations

Iteration: The while-Loop

The while-Loop examples

Logical Maneuvers

Lists of Numbers

Loops and Lists

Lists of Strings

Lists are Objects

Dictionaries

Introduction to Classes

Lists of Objects

Abstract Data Type, Stack, Queues

More Complicated Classes

Recursion

Searching a List

Sorting a List

Analysis of Algorithms

Congratulations!

About this course

Discover your potential, starting today