Last updated: June 19, 2025
Please note that for these workshops, some prior coding experience is needed. Elementary algebra and some knowledge of statistical measures will be helpful foundations for this experience.
Note: If you need to brush up on your knowledge of Python and conventional ML/AI, see the related pages:
Google Colab (Google Slides)
Fun with Python Programming, https://sites.google.com/view/funwithpythonwithali
Machine Learning For Non-Computer Science Majors, https://sites.google.com/view/aiandml4all/home
Download the free book 'The Python Handbook' by Flavio Copes', here.
June 17 and 18, 2025 | 1 - 4 pm
This part of the program is designed to provide an immersive introduction to the dynamic field of machine learning, welcoming participants from all backgrounds and experience levels. Throughout the course, you will develop a strong foundation in the core concepts and practical techniques of machine learning. The curriculum will guide you through the entire process - from preparing data, to building, evaluating, deploying machine learning models, and displaying results using colorful plots. By the end of the program, you will be well-prepared to leverage this powerful technology in a variety of real-world applications, regardless of your starting point.
If your knowledge of Python is a bit rusty and incomplete, you can search YouTube videos on the subject, especially looking for videos that use jupyter notebooks or Google Colab. See 'Welcome to Colab' by Google. Here is my 'Fun with Python Programming' page that can be of help. To setup Google Colab, first of all, you need an environment (called IDE or Integrated Development Environment, etc.) to type and execute your code. We'll use Google Colab and if you have a Gmail account, you already have access to it. Google Colaboratory is free and requires no setup and is great to start with Python. It has limited storage space and may be slow at times. But it is sufficient for this short course. Check this link and see if it works for you: https://colab.research.google.com/drive/1HEkVymxOvXvE77epZl_D2oQa2KWOrWeD?usp=sharing.If you have a Chromebook, it will run on that too as the only thing it needs is the Chrome browser. Hence Windows, Mac, Linux, Chromebooks, and cell phones/tablets of all types can be used and if it works, you are all set! Note that smaller devices like iPads may be showing you a reduced version of the site. In the settings of that page, there is an option called "Desktop site" or "Show Desktop site". Click on it to see the various options like File, Run, etc.
You may want to check a short video to make you feel better about Google Colab, https://www.youtube.com/watch?v=inN8seMm7UI
To give you some time to setup computers, here are some Intelligent looking applications:
Your own spell checker.ipynb (5 lines of code)
Remove Image Background.ipynb (5 lines of code)
Face Detection in Photos.ipynb (10 lines of code)
(For you to check later on) Simple Regression (Google Sheet)
(For you to check later on) Simple Clustering (Google Sheet - Data Only)
Neural Networks for classification <<<<===========
OR Gate - An example of Supervised Learning (Google Sheet).
Sentiment Analysis - Version 1.ipynb . Download corresponding data: movie_data_reduced.xlsx
Sentiment Analysis - Version 2.ipynb (You can give your review and the model will predict the sentiment)
Sentiment Analysis - Version 3.ipynb (Advanced Version is the same as above, but uses the FULL data, which it reads from a Google sheet. Accuracy of almost 90%.)
Sentiment Analysis - Julius Ceasar (text from Github)
Sentiment Analysis - Rosetta Stone (text from a webpage)
Sentiment Analysis using LLMs (Optional. DO NOT execute this code. Just see the results!)
Egyptian Hieroglyphics. Download images to your computer from here.
Deep Learning for Smiling Faces, https://colab.research.google.com/drive/1-gxRfydpJB0C7ymzsNqiKZVBcFlSqs1d?usp=sharing.
Download data from https://drive.google.com/file/d/1tDHi9upyR6wSeja86HzWYeBKGOsXlzSe/view?usp=drive_link (Originally from https://www.kaggle.com/datasets/chazzer/smiling-or-not-face-data )
Hopfield Networks (Google Sheet)
Hopfield Networks (Jupyter notebook with equations)
July 2 (Wednesday), 2025 | 1 - 5 pm
Building on the foundational knowledge gained in the initial program, our follow-up workshop, "Introduction to Generative AI," offers an engaging four-hour exploration into the rapidly evolving world of artificial intelligence that creates content. In this hands-on session, you will learn how to use Python API calls to generate text, images, and videos with state-of-the-art generative AI models. The workshop will guide you through practical examples and real-world applications, empowering you to experiment with cutting-edge tools and understand the underlying principles of generative AI. Whether you are curious about how AI can write stories, create artwork, or produce video content, this workshop will provide you with the skills and confidence to start building your own generative AI projects.