Open Sourced Curriculum and Lessons for an Introductory AI/ML Course
Open Sourced Materials for the Intro to AI Course
Medium Article on the course: https://medium.com/better-programming/how-to-teach-ai-and-ml-to-middle-schoolers-34bf59262ea8
This is a detailed repository for an introductory AI and Machine Learning course for complete beginners. The course begins by covering the basics of AI and Machine Learning, and has lots of code and notebook examples. The course covers standard machine learning algorithms and progresses to building full-scale deep neural networks. By the end of the course, you will be able to build your own machine learning algorithms and deep neural networks and complete many different types of projects. At the end of the course, we have a variety of to explore, ranging from topics of image classification, time series analysis, and natural langauge processing.
To use this repository, follow the order of notebooks/presentations. This course can be completed over any period of time, but it is recommended that the notebooks are completed in order. The examples are coded primarly with Sci-kit (traditional machine learning algorithms) and Keras (Deep Learning/Neural Networks). A background in coding and python is highly recommended, but not entirely necessary.
Please star this repo if you found it helpful! If you want to use this repository, please fork it to get the materials. This will help us with exposure and growing our course. If you would like to join the organization to add your own repository with code, please email us! ([email protected], [email protected])
Here are pre-recorded lectures for each of the 6 lessons. Watch them in order, and whenever there are code examples, just open up the notebook and follow along.
The entire playlist is here: https://www.youtube.com/playlist?list=PLWj-3LXfs4r0pD_fzYXUa2PFJ5JHKwaaW
Overview of AI/ML (Lesson 1): https://youtu.be/pWXR7kh_65g
Machine Learning Theory (Lesson 2): https://youtu.be/RHcKxr0cbj4
Deep Learning Theory and Concepts (Lesson 3): https://youtu.be/8oROUOisDzI
CNN Theory (Lesson 4): https://youtu.be/0RFPyCBoa20
CNN and NN Examples in Keras (Lesson 5): https://youtu.be/pGWwDAiB3Ic
Natural Language Processing Theory and Examples (Lesson 6): https://youtu.be/y6swv4GhU
Summer 2020, June 23 - August 11, 8 classes once every week on Tuesdays 5 PM.
The Intro to AI course is a free course for middle school students to gain a basic understanding of Artificial Intelligence and Machine Learning. Throughout 8 weeks, Ayaan Haque and Viraaj Reddi covered various machine learning topics, from the mathematical theory to neural networks to NLP. By open sourcing these materials, we hope that others can begin guiding young students into the field of AI/ML.
To use the lessons, follow the presentations/notebooks in order, and watch the video associated with the lesson.
Note: Weeks 7 and 8 were for individual projects, so the videos aren't provided.
Week 1: https://www.youtube.com/watch?v=3O0umGVjwW8&feature=youtu.be (Introduction)
Week 2: Currently Unavailable (Linear Regression)
Week 3: https://www.youtube.com/watch?v=kwzVjyIwcwU&feature=youtu.be (Deep Learning Introduction)
Week 4: https://www.youtube.com/watch?v=3e3v1MXOTo4&feature=youtu.be (CNN Theory and Explanation)
Week 5: https://www.youtube.com/watch?v=UvsA06Bz7mo&feature=youtu.be (Building a Neural Network with Keras)
Week 6: Currently Unavailable (Introduction to Natural Language Processing)
Week 7-8: Worked on Projects(No Video)
Summer 2021, June 20 - August 15, 8 classes once every week on Sundays 4 PM.
Week 1: Introduction to Artificial Intelligence (AI) and Machine Learning (ML)
Week 2: Overview of Machine Learning Concepts
Week 3: Machine Learning Code
Week 4: Overview of Deep Learning
Week 5: Convolutional Neural Networks
Week 6: Keras CNN Walkthrough
Weeks 7-8: Projects