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Learn Modern AI Python

This repo is part of the Certified Cloud Native Applied Generative AI Engineer program. It covers the first quarter of the course work:

AI-101: Modern AI Python Programming

The main focus in this course will be on mastering the fundamentals of Modern Python with Typing using Google Colab, the go-to language for AI and using AI to write Python Programs.

Python

Online AI-101 Project Classes every Tuesday 8:00 pm

Instructors: Hamza and Najam

In these online classes the main focus will be on doing the following projects in class: https://github.com/panaversity/learn-modern-ai-python/tree/main/PROJECTS/online_class_projects

The Zoom Link for the online classes: https://us06web.zoom.us/j/85338730622?pwd=KBNfeMPBhDTN7GMi7lH9K5UN6APAt9.1

You can also watch on YouTube if the Zoom class is full also recorded videos: https://www.youtube.com/@panaverse

Compulsory Projects for AI-101 Modern AI Python Students

All AI-101 students must complete these compulsory projects, or they will be removed from class until they complete and submit them:

https://github.com/panaversity/learn-modern-ai-python/tree/main/PROJECTS/projects_to_be_submitted_by_students

Your Instructors will assign a due date for the projects in class. You will submit your project in this form:

https://forms.gle/VPw9wnmt1j8e7bnb6

The instructors will check your project in the onsite class on the due date. If you do not submit on the due date, you will be removed from the class until you successfully complete your project and submit it.

For practice you should do the following homework projects (not to be submitted only for practice in class and at home): https://github.com/panaversity/learn-modern-ai-python/tree/main/PROJECTS/homework_projects

Additional Certification Program Material

Program Podcast

Agentic AI Detailed Intro Presentation

Program Review by ChatGPT

Read this article to understand The AI agents stack

We will following this course to get started AI Python for Beginners by Andrew Ng

We will be using Google Colab for development:

Google Colab is a free, cloud-based Jupyter Notebook service developed by Google. It enables users to write and execute Python code through a web browser, offering seamless integration with Google Drive for easy storage and sharing of notebooks. Colab is particularly beneficial for tasks in machine learning, data analysis, and education, as it provides access to powerful computing resources, including GPUs and TPUs, without requiring any local setup.

Key Features of Google Colab:

  • No Setup Required: Users can start coding immediately without the need to install any software or manage local environments.

  • Free Access to Computing Resources: Colab offers free access to computing resources, including GPUs and TPUs, facilitating the execution of complex computations and machine learning models.

  • Collaboration: Notebooks can be easily shared and collaboratively edited, similar to Google Docs, enhancing teamwork and knowledge sharing.

  • Integration with Google Drive: Notebooks are stored in Google Drive, allowing for straightforward organization and access across devices.

  • Support for Various Libraries: Colab supports popular Python libraries such as TensorFlow, Keras, and NumPy, making it versatile for various data science and machine learning projects.

Recent Developments:

Recently, Google expanded Colab's AI-powered code assistance features to all users in eligible locales, including those on free plans. These features assist in generating code from natural language prompts and provide a code-assisting chatbot to enhance programming efficiency and comprehension.

Getting Started with Google Colab:

To begin using Google Colab:

  1. Access Colab: Navigate to the Google Colab website.

  2. Create a New Notebook: Click on "File" > "New Notebook" to create a new Jupyter Notebook.

  3. Write and Execute Code: Enter your Python code in the code cells and execute them to see the results.

  4. Save and Share: Your notebooks are automatically saved in your Google Drive, and you can share them with others by clicking the "Share" button.

For more detailed information and tutorials, refer to the Colaboratory Frequently Asked Questions and the Colab Help Center.

Google Colab is a valuable tool for both beginners and professionals in data science and machine learning, offering an accessible platform to develop and share projects efficiently.