Welcome to the AI Python for Beginners repository, inspired by DeepLearning.AI's AI Python for Beginners course. This project is tailored for newcomers to Python, focusing on understanding and manipulating various data types using interactive notebooks and AI-assisted learning.
To introduce fundamental Python data types and structures, enabling learners to:
- Recognize and utilize basic data types: integers, floats, strings, and booleans.
- Understand and implement data structures: lists and dictionaries.
- Perform basic data operations and manipulations.
- Leverage AI tools for real-time coding assistance and feedback.
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Clone the Repository:
git clone https://github.com/PrasadRajeswar/AI-Python-For-Beginners cd AI-Python-For-Beginners
- Check the Repository structure for the course:
AI-Python-For-Beginners/
├── README.md # Repository overview, setup instructions, and course outline
├── Week_1/ # Folder containing Week_1 lesson files
│ ├── First_Program.md
│ ├── Data_in_Python.md
│ ├── Combining_text_and_calculations.md
│ ├── Variable.md
│ ├── Building_LLM.md
│ ├── Functions.md
├── Week_2/ # Folder containing Week_2 lesson files
│ ├── List.md
│ ├── Loop.md
│ ├── Dictionary.md
│ ├── List_Dictionary.md
│ ├── Comparing_Data.md
│ ├── AI_Decision.md
├── Week_3/ # Folder containing Week_3 lesson files
│ ├── Extracting Restaurant Information From Journal Entries.md
│ ├── Loading and Using Your Own Data.md
│ ├── Reading Journals From Food Critics.md
│ ├── Reusable Functions.md
│ ├── Using Files in Python.md
│ ├── Using of CSV Files.md
├── Week_4/ # Folder containing Week_4 lesson files
│ ├── API to Use AI Models.md
│ ├── Get Data From Web using API.md
│ ├── Using Functions From Local File.md
│ ├── Built-In-Packages.md
│ ├── Installing Packages.md
│ ├── Using Third Party Packages.md
└──
The AI-Python-For-Beginners GitHub repository covers:
- Python Fundamentals: Integers, floats, strings, booleans
- Data Structures: Lists and dictionaries
- Data Operations: Type casting, indexing, slicing, basic arithmetic, string manipulation
- AI-Assisted Learning: Using AI tools for explanations, debugging, and real-time feedback
- Project Work: Building AI-powered tools like custom recipe generators, smart to-do lists, and vacation planners
It’s structured into weekly lessons with markdown files for each topic.
You can explore it fully here. 🚀
Throughout the notebook, prompts are provided to encourage interaction with AI assistants. These prompts are designed to:
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Clarify complex concepts.
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Offer alternative explanations.
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Assist in debugging code.
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Provide real-time feedback.
Example Prompt:
"Explain the difference between a list and a dictionary in Python."
DeepLearning.AI for the foundational course content.
The AI community for tools and resources that enhance learning experiences.