DeepAtlas: Cultivating a Community that Catalyzes Collective Excellence As an experienced Software Engineer, my decision to delve into ML stems from a desire to be at the forefront of the AI revolution, to not just witness but actively participate in shaping the future. With the proliferation of LLMs, the boundaries of what is possible with ML have expanded exponentially. While I had dabbled in self-teaching, I yearned for a more structured and supportive environment to accelerate my growth. There is simply too much to absorb alone, and missteps exploring this space is time consuming. DeepAtlas provided crucial guidance, making my learning journey remarkably efficient and effective. What truly set DeepAtlas apart was its vibrant community, brimming with like-minded individuals passionate about machine learning. Engaging in discussions, collaborating on projects, and receiving guidance from seasoned mentors created a nurturing environment. While I have a long way to go, I feel DeepAtlas provided me a roadmap and the much needed confidence to continue my journey from here.

My DeepAtlas experience I wanted to learn about ML because I was seeing it emerge in both my current job and my side interests and everything seemed to be speeding towards AI features. I'm not sure I would have been able to learn it on my own as I'm the type of person who benefits a lot from course structure and to really understand the core concepts I needed to test my understanding by discussing with others. Having a group of other highly motivated and talented individuals made the pace and the difficult topic so much more manageable, I don't think I could have done it without such an amazing community of students and instructors. I started the course with very basic understanding of neural networks but no understanding of the linear algebra or modern use cases of ML. I now have the skills needed to complete a passion project of mine that before I couldn't even imagine the pieces that needed to be done. Also I have the knowledge now to keep up and understand the AI team at my current company and how they are solving issues or techniques they use for building features. ML is going to become such a valuable skill that will be needed by every engineer and data scientist in the future so I'm thankful I had the opportunity to get ahead of the curve and start my journey into ML now.

Just the catch-up I needed I attended Deep Atlas because I felt like the software industry has started to go in a new direction, and I'd noticed conversations about ML and AI happening at work that I wasn't able to keep up with. Coming away from the class after two weeks, I felt ready to engage with a whole range of ML and AI topics. The class delivered on its promises for me, and I feel capable of both practical ML engineering and fighting my way through AI white-papers (e.g. "Attention Is All You Need") to learn more. Hugging Face now feels more like a useful library of tools than a pile of enigmatic repos! Deep Atlas was a big fast-forward for my learning. I might have eventually gotten there on my own, but it's hard to say how long (and how much effort) that might have taken. Learning everything in a condensed period was effective and honestly quite fun!