31 - Topological Sort Algorithm.zip
73.9 MB
31 - Topological Sort Algorithm
32 - Single Source Shortest Path.zip
97.7 MB
32 - Single Source Shortest Path
33 - Graph Algorithms - Dijsktra's Algorithm.zip
77.1 MB
33 - Graph Algorithms - Dijsktra's Algorithm
34 - Graph Algorithms -Bellman Ford Algorithm.zip
145 MB
34 - Graph Algorithms -Bellman Ford Algorithm
35 - All Pairs Shortest Path.zip
46 MB
35 - All Pairs Shortest Path
36 - Graph Algorithms - Floyd Warshall Algorithm.zip
101.5 MB
36 - Graph Algorithms - Floyd Warshall Algorithm
37 - Minimum Spanning Tree (Disjoint Set).zip
85.1 MB
37 - Minimum Spanning Tree (Disjoint Set)
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38 - Graph Algorithms - Kruskal and Prim's Algorithms.zip
130.4 MB
38 - Graph Algorithms - Kruskal and Prim's Algorithms
39_Cracking_Trees_and_Graphs_Top_Interview_Questions_Part_01.zip
306.7 MB
39 - Cracking Trees and Graphs Top Interview Questions - Part 01
39_Cracking_Trees_and_Graphs_Top_Interview_Questions_Part_02.zip
194.7 MB
39 - Cracking Trees and Graphs Top Interview Questions - Part 02
40 - Greedy Algorithms.zip
190.2 MB
40 - Greedy Algorithms
41 - Divide and Conquer Algorithms - Part 01.zip
383.4 MB
41 - Divide and Conquer Algorithms - Part 01
41 - Divide and Conquer Algorithms - Part 02.zip
20.5 MB
41 - Divide and Conquer Algorithms - Part 02
42 - Dynamic Programming.zip
383.3 MB
42 - Dynamic Programming
43 - A Recipe for Problem Solving.zip
148.7 MB
43 - A Recipe for Problem Solving
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🔅 Programming Foundations: Beyond the Fundamentals
🌐 Author: Sasha Vodnik
🔰 Level: Beginner
⏰ Duration: 2h 6m
📗 Topics: Programming
📤 Join Learn Python for more courses
🌀 Dive deeper into the foundational concepts, practices, and terminology of programming. Learn how to work with collections, use external code, find and fix bugs, and more.
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1. Web Development: Python frameworks like Django and Flask are popular for building dynamic websites and web applications.
2. Data Analysis: Python has powerful libraries like Pandas and NumPy for data manipulation and analysis, making it widely used in data science and analytic.
3. Machine Learning: Python's libraries such as TensorFlow, Keras, and Scikit-learn are extensively used for implementing machine learning algorithms and building predictive models.
4. Artificial Intelligence: Python is commonly used in AI development due to its simplicity and extensive libraries for tasks like natural language processing, image recognition, and neural network implementation.
5. Cybersecurity: Python is utilized for tasks such as penetration testing, network scanning, and creating security tools due to its versatility and ease of use.
6. Game Development: Python, along with libraries like Pygame, is used for developing games, prototyping game mechanics, and creating game scripts.
7. Automation: Python's simplicity and versatility make it ideal for automating repetitive tasks, such as scripting, data scraping, and process automation.
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What OS are you using to navigate our channel?
Anonymous Poll
53%
16%
5%
42%
8%
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