Learn Python programming from scratch with this beginner's course! In this complete tutorial, you'll master Python fundamentals while learning how to leverage modern AI tools like Claude and ChatGPT to accelerate your learning.
What you'll learn: * Python installation and setup * Variables and data types * Conditional statements (if/else) * Functions and scope * Loops and iteration * Keyboard shortcuts * Virtual environments * NumPy basics * Matplotlib visualization * Common beginner pitfalls and solutions 🔥 Special Features: * Modern approach integrating AI tools * Practical examples and best practices * Clear explanations of complex concepts * Tips from 4+ years of teaching experience and 20 years of programming experience * Focus on both fundamentals and real-world applications
00:00 Introduction to Python for Beginners 01:13 Chapter 1: Chapter 1: Basics & Installation 04:27 Section 1.3: Installation of Jupyterlab Desktop & Anaconda 6:16 Troubleshooting the installation 6:44 Jupyterlab usage & best practices 9:47 Get the exercises 10:42 Section 1.5 Anaconda Cloud 11:14 Section 1.6 AI Tools: ChatGPT, Claude, Anaconda Assistant 13:38 Section 1.7Jupyter Notebooks vs Python Scripts 16:08 Chapter 2: Python Variables and Data Types 17:45 Section 2.1: Strings & f-strings 19:56 Section 2.2: Integers & Basic Math 20:37 Section 2.3: Cell state 22:10 Section 2.4: Comments 24:18 Data structures: Tuples, Lists 30:09 Section 2.7: Dictionaries 31:30 Section 2.8: Comparison of different data structures 32:34 Chapter 3: If statements 34:34 Section 3.1: Boolean Variables and Logical Operators 35:08 Section 3.2: “and” operator 36:02 Section 3.3: “or” operator 36:57 Section 3.4: Boolean Logic Weather example 37:46 Section 3.5: Elif Statements and Multiple Conditions 40:39 Section 3.6: Creating Booleans by comparison 41:11 Summary Chapter 3: If statements 41:34 Chapter 4: Functions 45:47 Section 4.2: Multiple return values 47:09 Section 4.3: Scope 50:19 Section 4.8: Error Handling and Debugging 51:15 Anaconda Assistant for Debugging 54:17 Section 4.9: Common Errors 55:55 Chapter 5: Loops 58:17 Section 5.2: for loops 1:01:38 Chapter 6: Keyboard Shortcuts 1:04:50 Chapter 7: Virtual Environments 1:06:24 Section 7.2 Why use virtual environments? 1:08:20 Section 7.3: Managing Environments with Anaconda and Pip 1:11:08 Installing environments 1:12:16 Fixing Windows Powershell 1:12:35 Add conda to Powershell 1:13:33 Creating YAML files 1:15:45 Section 7.8: Environments in Anaconda Cloud 1:16:52 Section 7.9: Exporting & Sharing Environments 1:18:22 Chapter 8: First Steps with NumPy 1:24:46 Chapter 9: First Steps with Matplotlib 1:27:13 Section 9.2 Scatter Plots 1:28:48 Section 9.3 Histogram 1:29:32 Section 9.4 Contour Plots 1:30:31 Section 9.5 Pie charts 1:31:25 Section 9.6 Summary Chapter 9: Matplotlib 1:32:02 Chapter 10: FAQ 1:32:17 Section 10.1: Whenever I look at your code it makes sense, when I try it I get errors 1:33:30 Section 10.2: How to think like a programmer? 1:36:21 Section 10.3: Naming Variables: Avoid Keywords and Built-in Functions 1:36:55 Section 10.6: Which one of the AI tools should I be using? 1:38:04 Section 10.8: What are some common Python libraries for data analysis and when should I use them? 1:38:36 Section 10.9: How can I collaborate on Python projects with others using version control? 1:39:10 Section 10.10: How can I improve my skills further?
▬ *Commands used in the video:* ▬▬▬▬
To add conda to Powershell:
In Anaconda Prompt: conda init powershell
In Powershell: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
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