Python 3: Project-based Python, Algorithms, Data Structures [Video]
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Free ChapterIntroduction
-
Development environment setup
-
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
-
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
-
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
About this
video
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
• Text - Strings
• Numbers - ints and floats
• Execution flow control - branching with if/elif/else
• Compound data types - lists, dictionaries, tuples, and sets
• Iterables and iteration with generators, for and while loops, and more!
• Functions, execution context and frames, and building custom functions
• List comprehension
• Lambda expressions
• Generators and creating your own generators with yield
• Objects and building classes, methods, and special methods
• Reading from and writing to files using context managers
• Visualization with each topic and more!
Part 2: Algorithms, Data Structures, and Performance Analysis
• Sorting algorithms (basic) - bubble sort, selection sort, and insertion sort
• Sorting algorithms (advanced) - merge sort and quick sort
• Big O notation, complexity analysis, divide and conquer, and math visualizations
• Recursion in-depth with examples
• Searching algorithms - bisection search and hashing
• Data structures with linked lists, stacks, queues, trees, and binary search trees
• Operations with data structures - insert, search, update, and delete
• Multiple projects with increasing levels of complexity to tie concepts together
• Visualizations of all algorithms, data structure, operations, and more!
All the codes and supporting files for this course are available at - https://github.com/PacktPublishing/Python-3-Project-based-Python-Algorithms-Data-Structures
- Publication date:
- September 2019
- Publisher
- Packt
- Duration
- 14 hours 29 minutes
- ISBN
- 9781839216510
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