Notes: How to Build a Career in AI eBook

How to Build a Career in AI is a 41 page ebook with great insights, advice and suggestions from Andrew Ng, the founder of DeepLearning.AI and Coursera.

Highlights and excerpts:

Keeping up-to-date with changing technology is more important in AI than fields that are more mature.

The highly iterative nature of AI projects leads to special challenges in project management: How can you come up with a plan for building a system when you don’t know in advance how long it will take to achieve the target accuracy? Even after the system has hit the target, further iteration may be necessary to address post-deployment drift.

Exploratory Data Analysis (EDA) — using visualizations and other methods to systematically explore a dataset — is particularly useful in data-centric AI development.

The best way to build a new habit is to start small and succeed, rather than start too big and fail. 

Five steps to help you scope projects:

1. Identify a business problem (not an AI problem). Ask - “What are the top three things that you wish worked better? Why aren’t they working yet?”
2. Brainstorm AI solutions. Sometimes there isn’t a good AI solution, and that’s okay too.
3. Assess the feasibility and value of potential solutions. 
4. Determine milestones and metrics (machine learning metrics such as accuracy and business metrics such as revenue). 
5. Budget for resources. 

Given the huge number of possible AI projects, rather than the conventional “ready, aim, fire” approach, you can accelerate your progress with “ready, fire, aim.” by accepting a higher risk of pivoting or failing.

Building models is an iterative process. For many applications, the cost of training and conducting error analysis is not prohibitive. Furthermore, it is very difficult to carry out a study that will shed light on the appropriate model, data, and hyperparameters. So it makes sense to build an end-to-end system quickly and revise it until it works well.

You need to be able to explain your thinking if you want others to see the value in your work and trust you with resources that you can invest in larger projects. 

When faced with uncertainties, thinking through the possibilities and following through on plans can help you navigate the future effectively.

With training in AI and statistics, you can calculate a probability for each scenario. In the Superforecasting methodology, the judgments of many experts are 

synthesized into a probability estimate. 

Because AI is evolving, many companies use job titles in inconsistent ways.  Having informational interviews with people in companies that appeal to you can help sort out what the AI people in a particular company actually do.

An informational interview involves finding someone in a company or role you’d like to know more about and informally interviewing them about their work. Such conversations are separate from searching for a job. In fact, it’s helpful to interview people who hold positions that align with your interests well before you’re ready to kick off a job search.

Many successful people develop good habits in eating, exercise, sleep, personal relationships, work, learning, and self-care. Such habits help them move forward while staying healthy.

Meetups such as Pie & AI can help you build your network.

To become good at anything, the first step is to suck at it. If you’ve succeeded at sucking at AI — congratulations, you’re on your way!