Learn to program with Python 3, visualize algorithms and data structures, and implement them in Python projects
About This Video
In Detail
This course is one of the most comprehensive and beginner-friendly courses on learning to code with Python—one of the top programming …
Learn to program with Python 3, visualize algorithms and data structures, and implement them in Python projects
About This Video
In Detail
This course is one of the most comprehensive and beginner-friendly courses on learning to code with Python—one of the top programming languages in the World—and using it to build algorithms and data structures with projects from scratch.
We will walk you step-by-step through the fascinating world of Python programming using visualizations of programs as they execute, algorithms as they run, and data structures as they are constructed. Nothing is left to the imagination; you'll see it all and then build it all.
Since it caters to a broad spectrum of students, the course is split into two parts: part 1 focusing on the Python programming language and part 2 focusing on Algorithms, data structures, performance analysis, and larger-scale projects.
Part 1: Python and programming fundamentals
Part 2: Algorithms, Data Structures and Performance Analysis
Who this book is for
This course is designed for beginners who have never programmed before; programmers switching to Python; intermediate and advanced programmers looking to understand algorithms and data structures; Job interview candidates looking to understand the subject matter behind technical interview questions, and anyone keen to learn how to visualize programs and information flows.
Chapter 1 : Introduction
Introduction
Course structure and content overview
Chapter 2 : Development environment setup
Section intro and overview
Download and install Python
Setup Atom as text editor (setup used in this course)
Exploring Jupyter Notebooks interface (optional)
Chapter 3 : Python in-depth
Section intro and overview
Command line/Terminal basics
Strings, variables, top down execution flow
Strings: concatenation, indexing, slicing, python console
String methods, functions and import statements
Print formatting and special characters
Numbers, math, type casting and input
Introduction to branching (if, elif, else) and conditionals
Building if, elif, else blocks incrementally
Lists, dicts, sets and tuples - Intro to compound data types in Python
Lists - an in-depth look 1
Lists - an in-depth look 2
Dictionaries, sets and tuples
Iterators, for loops, generators, list comprehension
While loops, enumerate, zip
Functions - an introductory look
Functions - implementation step by step
Functions - execution context, frames, mutable vs. immutable arguments in-depth
Classes and objects - an introductory look
Building a custom Student class and intro to special methods
Add some methods to the class
Special methods and what they are
Reading from and writing to files
Add read functionality and utilize special and static methods
Inheritance, subclasses and complete example class
Lambda expressions and map function
Generators - under the hood
Build your own generators using yield
Chapter 4 : Algorithms - Sort, performance, complexity and big O notation
Introduction to section 4 and overview of the material covered in it
Bubble sort demonstration and complexity analysis
Bubble sort implementation
Selection sort demonstration and complexity analysis
Selection sort implementation
Insertion sort demonstration and assignment handoff
Insertion sort programmatic execution step by step
Performance measures - deep dive with a programmatic view
O(nlog(n)) performance and algorithm prerequisites
Analyze log(n), visualize the math behind it and how it relates to algorithms
Merge sort visualization and complexity analysis
Implement merge function - part 1
Implement merge function - part 2
Implement merge function - part 3
A look at the recursive divide function
In-depth look at execution context of recursive divide function
Recursion mini-project 1 - Countdown timer
Recursion mini-project 2 - Factorial
Recursion mini-project 3 - Fibonacci series
Complete merge sort algorithm and analyze updated execution context
Quicksort demo
Quicksort implementation
Section final project objective and motivation
Project specs and runtime execution intro
Project phase 1: Build random int list generator
Project phase 2: Get input from user for size and range
Project phase 3: Add functions, calculate and analyze runtime
Project phase 4: Extract redundancies, create function and cleanup code
Project phase 5: Add multiple run functionality and perform additional testing
Chapter 5 : Algorithms - Search and abstract data structures
Introduction to section 5
Intro to search - Linear, Bisection/Binary search
Bisection/Binary search - Iterative implementation
Bisection search - recursive implementation
Project handoff: Bringing it together
Project conclusion walkthrough
Hashmaps and O(1) search complexity
Hash project 1: Define and set up class blueprint with init and str
Hash project 2: Set up insert and hashing functionality for data structure
Hash project 3: Add update functionality
Hash project 4: Build search method
Project: Use hash structure in a practical exercise - Quote finder
Project: Complete quote finder using hash table
Intro to linear data structures - Linked Lists
Build a custom linked list
Recursively reverse a linked list
Visualize Stacks and Queues, and their operations
Introduction to Trees and Binary Search Trees
In-order traversal of a Binary Search Tree
Build a Binary Search Tree from scratch - Insert
BST from scratch - In-order traversal
BST from scratch - Search
BST from scratch - Delete demo
BST - Deleting leaf nodes
BST - Deleting nodes with 1 child node
BST - Deleting nodes with 2 children
Project: Job Scheduler using Binary Search Trees - Introduction
Project: Job Scheduler execution flow
Project: Job Scheduler implementation tips and notes
Thank you for taking the course and next steps