The Summer of Machine Learning (SoM) is an integral component of the BSoC open-source initiative, designed to introduce contributors to the dynamic field of AI and ML.
SoM In a nutshell:
- 6 Weeks + Projects
- Online
- Prerequisites: None!
Explore Machine Learning, Data Science and Artificial Intelligence with our 6-week course. This course is designed to introduce you to the dynamic field of AI and ML. You will learn the basics of Python, Machine Learning, and Data Science. You will also get to work on projects that will help you understand the practical applications of these concepts.
In a world saturated with countless paid and free courses, diving into Data Science can feel overwhelming for students. To simplify this journey, we meticulously curate a focused path from over 25+ reputable websites. SoM, an integral part of our community, aims to demystify Data Science and ignite a passion for innovation.
Data Science revolves around extracting meaningful insights from vast datasets. Our online certification course, now transformed into the Summer of Machine Learning, delves into essential topics:
| Week | Content |
|---|---|
| Week 1 | Introduction to Python and Python Libraries |
| Week 2 | ML Algorithms |
| Week 3 | Model Tuning |
| Week 4 | Tree-based Algorithms |
| Week 5 | Neural Networks |
| Week 6 | Misc |
SoM is about making learning fun and interactive. We have a dedicated Discord server where you can interact with your peers, ask questions, and collaborate on projects. We also have a dedicated team of mentors who will guide you through your journey and help you with any doubts you may have.
So it's about learning, collaborating, and having fun! Just follow the course deligently and you will be good to go!
We encourage you to contribute to the Summer of Machine Learning. Here are some ways you can contribute:
- By sharing your knowledge with others.
- By updating the documentation.
We are grateful to all the external material providers and websites that have helped us create this course. We would also like to thank our mentors for their guidance and support.
