Deep AtlasReviews of deepatlas.ai

Excellent staff, well organized and encouraging.

Took this course after feeling behind on the AI/ML movement. I found having structure and being in a supportive community and cohort more effective than learning by myself. The course was hands on and got us involved with building our own projects from the get go. I found my confidence improving in the subject area after doing the course and feel more able to keep up with industry trends. The course was definitely challenging but well worth it!

The two weeks of the Deep Atlas course were as enjoyable as they were impactful and educational. I went in expecting to unwrap and peer inside the black box of AI. What I came out with was not only that, but also a community of fellow AI-enthusiasts, instructors that I consider mentors, a résumé-worthy project of fine-tuning LLMs to take on the persona of a character, and the confidence to walk into any job interview in the AI sector and know that I could hold my own. Three weeks after the course, I landed a dream job in AI and Deep Atlas absolutely played a role in that achievement. I could not recommend it enough or think more highly of the incredible team that made it all possible.

This program was exceptionally good. I went from very little understanding of the latest in machine learning and AI, to a very thorough understanding in two weeks. Marcus is the best instructor I have ever learned from. I would take any class that he architects on literally any subject. So well thought out and organized. Would recommend to anyone.

Neural networks, fine tuning, hyper parameters, transformers. These were some of the words flying around my feed that I couldn't quite grasp. I tried to learn them on my own, but then I uncovered even more arcane words: vectorization, embeddings, latent space, weights, gradient descent. Deep Atlas put together a masterclass in distillation. From linear algebra to transformers (the architecture that powers LLMs today), there was a crystal clear roadmap, paved with engaging lectures and solidifying real world projects. After the class, I feel ahead of this incoming wave. I’m well equipped to integrate AI into both my work and personal projects, and to continue my self-study at the cutting edge of this rapidly evolving industry.

Having worked as a software engineer for the past decade, I was excited by the new possibilities that the recent developments in AI have opened up. My experience at Deep Atlas has profoundly leveled up my knowledge and skillset to capitalize on these opportunities. The curriculum at Deep Atlas is efficient and effective. There’s so much educational content on the internet that it’s hard to map out a path on one’s own. It’s easy to get lost in the weeds of basic theory (e.g. linear algebra) and overwhelmed by the complexity of advanced concepts (e.g. transformers). I needed a system to take me from A to Z. The Deep Atlas curriculum trimmed the fat and delivered the highest density of educational nutrients. In order to achieve its goals, the program ran at a fast pace. We were given lectures on theory and many hands-on exercises to apply our learning. We covered so much in a relatively short period of time. Had it not been for the structured schedule, it would’ve been very easy to get sidetracked. Taking on an endeavor such as this would have been really difficult without community. I found my peers at Deep Atlas to be intelligent, passionate, and supportive. The culture was collaborative and encouraging, which greatly enhanced my learning experience. It was inspiring to be a part of a group that had technical depth. I enjoyed the wide breadth of industry experience we brought in. At the end of the program, we had a two-day capstone group project. I was so impressed by everyone’s projects. Our team built a classification model to determine whether a body of text (narrative) contained any cognitive distortions. We learned so much from the experience. Looking back, it’s pretty incredible that we gained the knowledge and skills to do that in less than two weeks. I couldn’t imagine doing this without Deep Atlas. And this is just the beginning. There’s so much more to learn, especially given the pace of new developments in this field. After Deep Atlas, I now have a map of the AI/ML terrain. I’m able to navigate my own career path through it and integrate new discoveries along the way. The tools I’ve gained allow me to solve so many more problems, and I’m excited for that!

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.

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.