Mechanical engineering and data science may appear vastly different on the surface. Mechanical engineers create physical machines, while data scientists deal with abstract concepts like algorithms and machine learning. Nonetheless, transitioning from mechanical engineering to data science is a feasible path, as explained in this blog.
It’s time to talk about the different data engineering projects you might work on as you enter the exciting world of data. You can add these projects to your portfolio and show the best ones to future employers. Remember, the world’s most successful engineers all started where you are now.
Artificial intelligence (AI) isn’t going to steal your data scientist job! Instead, AI tools like ChatGPT can automate some of the more mundane tasks in your future career, saving you time and energy. To make life easier, here are some data science prompts to get you started.
What should you put on your data science resume to stand out against the competition? We’ve talked to an elite resume writing service to get the details on everything you need in your resume to get hired fast.
You have a programming background. So do data scientists. So switching to a career in data science should be pretty easy, right? Yes, and no. While it’s not a seamless transition, it’s certainly doable, and we’ll tell you how.
You’ll hear the same things about data science time and time again—that you can get an entry-level position making six figures, you’ll never be out of work and it’s one of the most sought-after careers in the world. But one thing nobody mentions is how stressful this career can be at times. So, how stressful is it really?
