I use DataCamp to improve my knowledge and raise my bar. It helps me save the time it would take to attend offline courses. I like the interaction on DataCamp, even though I am still learning and listening to topics, and I appreciate how simple it was to set up. Also, we switched from LinkedIn Learning to DataCamp because it focuses on the future, AI, and data learning, which are essential for us.

DataCamp covers a broad range of techniques related to data science, deep learning, software engineering, data engineering, MLOps, and AI/LLM. It also provides a variety of different learning formats, such as real-world projects and hands-on practice. As an ML architect, my work spans a wide range of tasks, from predictive model development and deployment to our production ML infrastructure. I need to choose the right tech stack, integrate techniques, demo the technique and platform, and educate the team. DataCamp is a very good platform for quickly picking up a new technique from zero to one, and it helps me complete prototypes within a reasonable timeframe. The interactive practice lets me not only learn the theory, but also connect the code to the concepts quickly, so I can apply the technique efficiently.

I like the way we watch videos and then do exercises to reinforce the theory we’ve just learned. I also enjoy the XP and daily streak system.