Where to Next?
In our lessons, we covered the fundamentals of AI, and you learned about concepts that are essential irrespective of your sub-area of interest. Now, it’s time for you to choose your path based on topics that are most relevant for you:
Are you dealing with computer vision, natural language processing, or ML algorithms in general? Does your work require you to stay on top of the latest trends and developments from the AI world or would it be more relevant for you to dive deeper into specific topics?
a) If you need to stay on top of the current trends and latest AI developments, here is a top quality resource that you can subscribe to:
- The Batch: a weekly newsletter presenting the most important AI events and perspective in a curated, easy-to-read report for engineers and business leaders. Every Wednesday, “The Batch” highlights a mix of the most practical research papers, industry-shaping applications, and high-impact business news.
b) If you need to dive deeper into specific topics, you will find many great online resources.
- You cannot go wrong with Andrew Ng, for example. Andrew is a top-notch instructor, co-founder of Coursera, and CS professor at Stanford.
Last but not the least, as you decide on your next steps, I want to leave you with a very important reminder:
We live with cognitive-biases about knowledge and learning. We have this notion in our heads of the things that we “should” know. We should know all the algorithms, we should be pros at all the latest tools and technologies, we should be proficient in this and that.
However, fields like AI are so vast that you can’t possibly know everything! Also, the more you learn, the more things you will find to learn further. The knowledge gap will seem to widen more and more. This can result in making you feel worthless, like someone who isn’t just able to keep up with everything they must learn. If you ever end up in this state, please remember that it is NOT possible to learn EVERYTHING! Knowledge-gaps are part of the learning process!