Data Science for Non-Techies: Career Skills with Practical Examples (A Beginner's Guide to Big Data, Analytics, and Insights by Maxen Ford - Page 3 of 3

Data Science for Non-Techies: Career Skills with Practical Examples (A Beginner’s Guide to Big Data, Analytics, and Insights by Maxen Ford

Learning to spot opportunities where you can apply data is a key step toward becoming more valuable to your organization. You need to be curious and constantly ask questions like “what does the data say?” and “how can we measure success?” In finance, data can be used to spot fraud when a transaction is out of line. In HR you can use it to predict which potential hires are likely to stay. In marketing, you can use it to predict what specific people will purchase or want to see.
In any case, you should try to calculate your ROI (return on investment) for each data initiative in order to justify doing it. Ideally, you can quantify the value of a data effort, but qualitative benefits, which are harder to quantify, are also meaningful.

As you complete data projects, you need to put them into a portfolio. You should consider places like GitHub, LinkedIn, or a personal website (the most flexible) as places to display your work and tell your stories. Personal websites are easy to create with tools like WordPress (Doug: Which I use.), Wix, Carrd, and GitHub Pages. If you are looking for data sets to use for projects, try Kaggle, UCI Machine Learning Repository, or Google Dataset Search. Be sure to describe your context, your process, the tools you used, and the impact of your work for each project.
After you have developed some skill, consider becoming certified. Maxen describes five free and six paid options. Some are designed for beginners, while others are for more accomplished data professionals. Along your journey you should reach out to others in your community or online who are making similar efforts. Also, look for opportunities to share your work at conferences and less formal setting like lunchtime presentations.

The demand for data science skills is rising and you don’t need a computer science degree to get in the game. College students should look for internships where they can spend lots of time learning. If you have been working for a while, you have probably seen data being used and you have certainly acquired some industry-specific expertise. On top of what you know, aim to build some data skills. Look for free or inexpensive courses mentioned here.
Try to take on real projects that will let you build your data portfolio. Don’t hesitate to volunteer as nonprofits can use your skills. Try to become part of a local or online data community. Share your work beyond your organization. Make sure your resume touts your skills and that you show them off during interviews. Look for freelance work. Maxen tells you where to look. Find mentors who can also give you credible recommendations. To gain skill quickly, look for bootcamp experiences that are designed for rapid upskilling.

There are two pages with many links that are very valuable. They are almost worth the price of the book.

Maxen is known for breaking down complex technology into accessible, actionable guidance that helps readers succeed in the fast-moving digital world. He is also the author of Mastering Prompt Engineering, Tech Job Blueprint, Prompt Engineering Secrets, and Code Faster with Python. Maxen built his career without a formal computer science degree. (Doug: I did too.) This makes him uniquely qualified to help others do the same. Thanks Maxwn.