Python Courses & Resources
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Master Python with step-by-step courses – from basics to advanced projects and practical applications.
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📱 Python Data Analysis & Visualization Masterclass. (2025)

🎓 What will you learn?

📍Master Pandas Dataframes and Series
📍Create beautiful visualizations with Seaborn
📍Analyze dozens of real-world datasets.
📍Practice with tons of exercises and challenges
📍Learn all the ins and outs of Matplotlib
📍Organize, filter, clean, aggregate, and analyze DataFrames
📍Master hierarchical indexing
📍Merge datasets in Pandas
📍Create line, bar, column, square, pie, violin, carpet, swarm, band, and more!

Language: English
Price: $120
Size: 15GB
Duration: 20 hours

get it: https://t.me/+r_Tcx2c-oVU1OWNi
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1️⃣ Data Science
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6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

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Caltech's "Undergraduate Game Theory" lecture notes by Omer Tamuz

PDF: https://tamuz.caltech.edu/teaching/ps172/lectures.pdf

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🔅 Artificial Intelligence Foundations: Machine Learning

🌐 Author: Kesha Williams
🔰 Level: Beginner

Duration: 1h 50m

🌀 Learn about the machine learning lifecycle and the steps required to build systems in this hands-on course.

📗 Topics: Machine Learning, Artificial Intelligence
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🔅 Python Projects

🌐 Author: Barron Stone
🔰 Level: Intermediate

Duration: 1h 32m

🌀 Get hands-on practice building your own Python applications. Follow the development of a single project, from initial ideation to building the final installer for distribution.


📗 Topics: Software Projects, Python
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🔰  Python Web Scraping with Beautiful Soup and Regex

Check out the power of Python with a demonstration of web scraping using Beautiful Soup and also some Regex.

🖥 By: https://t.me/Python53

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📖 Data Structure and Algorithm Patterns for LeetCode Interviews – Tutorial

This is a comprehensive course on data structures and algorithms. algo monster will break down the most essential data structures—like arrays, strings, sets, hashmaps, and heaps, and he'll show you exactly how and when to use them. You’ll also master core algorithmic patterns such as two pointers, sliding windows, binary search, breadth-first search (BFS), depth-first search (DFS), and backtracking, all explained with clear examples and real interview problems.


⭐️ Contents ⭐️
⌨️ (0:00:00) Array
⌨️ (0:03:11) String
⌨️ (0:04:56) Set
⌨️ (0:06:40) Control Flow & Looping
⌨️ (0:07:32) Big O Notation
⌨️ (0:10:02) Hashmap
⌨️ (0:15:54) Hashmap practice problems
⌨️ (0:18:52) Two Pointers
⌨️ (0:22:56) Two Pointers practice problems
⌨️ (0:26:48) Sliding Window
⌨️ (0:31:45) Sliding Window practice problems
⌨️ (0:37:39) Binary Search
⌨️ (0:39:28) Binary Search practice problems
⌨️ (0:48:28) Breadth-First Search (BFS) on Trees
⌨️ (0:50:36) BFS on Graphs
⌨️ (0:52:13) BFS practice problems
⌨️ (0:57:31) Depth-First Search (DFS)
⌨️ (0:59:01) DFS on Graphs
⌨️ (1:00:24) DFS practice problems
⌨️ (1:05:01) Backtracking
⌨️ (1:08:14) Backtracking practice problems
⌨️ (1:10:27) Priority Queue/heap
⌨️ (1:11:36) Priority Queue/heap practice problems

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🔅 AI Engineering in 76 Minutes (Complete Course/Speedrun!)

All images are from the book AI Engineering unless otherwise credited.


Timestamps
00:00 What is AI Engineering?
01:49 Understanding Foundation Models
08:40 Evaluating AI Models
14:50 Model Selection
23:15 Prompt Engineering
30:20 RAG and Context Construction
36:56 Agents and Memory Systems
43:02 Finetuning
52:40 Dataset Engineering
59:45 Inference Optimization
01:09:01 Architecture and User Feedback.

🖥 By: https://t.me/Python53

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