Having interviewed many people who have multiple specializations from deeplearning.ai, Coursera, Udacity, DataCamp, Udemy, etc, the candidates who tend to stand out are those who demonstrate a working knowledge of AI/DL.

How do you do that? With a portfolio of projects that involve different data domains (text, image, multimodal) and tasks (classification, generation).

Assuming that you have a good grasp of the theory and you're ready to take up a small project that allows you to practice your skills, it is a good idea to find a project that resembles something in the industry and work on it to improve the breadth of your knowledge and try things into production. Let's say for example that you decided to develop an image similarity search system that finds the closest image to a given query image. The following list of questions can help you, not only to prepare the project itself but also to get a good sense of the required skills and knowledge required:

- What would your complete end-to-end pipeline look like?
- How would you build a cloud API to serve the web frontend?
- How do you scale from hundreds of images vs millions to billions?
- What would be the cost involved in scaling this up?
- How would you evaluate performance metrics, eg latency, and accuracy for model drift?
- How would you index the new incoming data? Would you rebuild or incrementally update?
- While scaling up how do you make your network and pipeline efficient? How do you reduce the floating-point computations in your network? How would you reduce the size of the embeddings while still having the same representative power?
- What are the potential sources of bias?
- In retrospect, consider the effort you put into this. What would you have done differently if you had one day, one week, or one month to develop a solution?

Follow the trajectory of these questions in your projects and you’ll find yourself approaching problems from different perspectives, acquiring knowledge, developing multiple solutions, and evaluating the merits and demerits of each. Beyond technical skills, you should be looking for opportunities to elevate your profile with ideas such as:

- Communicating your work and its impact effectively, to both specific stakeholders and the general audience.
- Develop and engage in leadership roles be it for organizing the project or organizing people and teams.
- Maintain professional relationships.
- Create an identity for yourselves in the field, and market yourself.