How to build you Career in IA

Today we take granted that many people know to read and write. Someday, I hope, it will be just as common that people know how to write code, specifically for AI.

The rapid rise of AI has led to a rapid rise in AI jobs, and many people are building exciting careers in this field. A career is a decades-long journey, and the path is not straightforward. Over many years, I’ve been privileged to see thousands of students, as well as engineers in companies large and small, navigate careers in AI.

One of my favorite books is BJ Fogg’s, Tiny Habits: The Small Changes That Change Everything. Fogg explains that the best way to build a new habit is to start small and succeed, rather than start too big and fail. For example, rather than trying to exercise for 30 minutes a day, he recommends aspiring to do just one push-up, and doing it consistently.

This approach may be helpful to those of you who want to spend more time studying. If you start by holding yourself accountable for watching, say, 10 seconds of an educational video every day — and you do so consistently — the habit of studying daily will grow naturally. Even if you learn nothing in that 10 seconds, you’re establishing the habit of studying a little every day. On some days, maybe you’ll end up studying for an hour or longer.

To figure out what’s important to know, I find it useful to ask what you need to know to make the decisions required for the work you want to do. At DeepLearning.AI, we frequently ask, “What does someone need to know to accomplish their goals?” The goal might be building a machine learning model, architecting a system, or passing a job interview.

Deep learning is still an emerging technology, so when you train a neural network and the optimization algorithm struggles to converge, understanding the math behind gradient descent, momentum, and the Adam optimization algorithm will help you make better decisions. Similarly, if your neural network does something funny — say, it makes bad