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Python 3: Project-based Python, Algorithms, Data Structures


MP4 | Video: AVC 1920x1080 30fps | Audio: AAC 48KHz 2ch | Duration: 14h 29m
Genre: eLearning | Language: English | Size: 3.9 GB

Learn to program with Python 3, visualize algorithms and data structures, and implement them in Python projects

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Learn
Learn Python 3 from scratch, in-depth
Understand the fundamentals of programming languages
Learn to visualize algorithms, data structures, program executions, and information flows
Learn to use Python to build projects
About
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!
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