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Introduction to Deep Learning for HA AI Track - A Curriculum
🤩 Welcome to the Honors Academy AI Track Resource Hub! 🤩
Dive into the world of Deep Learning with the **Eindhoven University of Technology's Honors Academy AI Track **. This dedicated platform is tailored to provide our ambitious students with a comprehensive collection of materials, insights, and tools to excel in their AI endeavors. Whether you're embarking on a deep learning journey or exploring the intricacies of machine learning, our curated resources are here to guide you every step of the way.
Our commitment is to ensure that you have a solid foundation to kickstart your projects. From essential basics to advanced techniques, our materials encompass a wide spectrum of AI knowledge. Moreover, our expertly crafted tips and tricks are designed to enhance your project's efficiency and effectiveness. But that's not all! Dive deeper with our additional resources that offer a broader perspective and connect theoretical knowledge with practical application.
Embrace the future of AI with confidence. Let's embark on this transformative journey together, harnessing the power of technology to innovate, inspire, and impact. Welcome to the Honors Academy AI Track of the Eindhoven University of Technology.
✍️ Hearty thanks to our authors ........
🎨 Thanks as well to our illustrators .....
Getting Started
This repository includes pages with introductory tutiruals and materials that are crucial for the AI Track projects. The curriculum does not include all but necessary materials on deep leanring in Python as well as useful tips from the 2022-2023 HA AI Track members. In case you see there is more to be added, feel free to contribute and extend the materials or link your own project for reference in the topics.
For further study, we recommend following these ....................Microsoft Learn modules and learning paths.
Pedagogy
We have chosen two pedagogical tenets while building this curriculum: ensuring that it is hands-on project-based and that it includes frequent quizzes. In addition, this curriculum has a common theme to give it cohesion.
By ensuring that the content aligns with projects, the process is made more engaging for students and retention of concepts will be augmented. In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 12-week cycle. This curriculum also includes a postscript on real-world applications of ML, which can be used as extra credit or as a basis for discussion.
Find our Code of Conduct, Contributing, and Translation guidelines. We welcome your constructive feedback!
| Lesson Number | Topic | Lesson Grouping | Learning Objectives | Linked Lesson | Author |
|---|---|---|---|---|---|
| 01 | ⚡️ Introduction to Pytorch ⚡️ | Introduction | Learn the basic concepts of deep learning using Pytorch | Lesson | Muhammad |
Offline access
You can run this documentation offline by using Docsify. Fork this repo, install Docsify on your local machine, and then in the root folder of this repo, type docsify serve. The website will be served on port 3000 on your localhost: localhost:3000.
PDFs
Find a pdf of the curriculum with links here.
Help Wanted!
Would you like to contribute a translation? Please read our translation guidelines and add a templated issue to manage the workload here.
Other Curricula
Our team produces other curricula! Check out: