Python for Everybody Specialization

I’m starting off the new year by learning something new. I am a big fan of non-traditional education, and Coursera is a platform I’ve used a few times before. You may not get courses that qualify as university credit, but I’ve found it to be a useful resource for learning. I might be biased (my university degree is in Economics, which I’ve never used), but in some ways, I actually prefer a MOOC (that’s a Massively Open Online Course) to a typical formal university course for a few reasons:

  • MOOCs are entirely online, which means it’s more accessible - I don’t need to physically be in the US to take a course at Harvard

  • MOOCs are usually self-paced - perfect for someone working full-time like me

  • MOOCs are free or cheap - no huge student loans here; MOOCs are democratizing education and making it available to more people

  • Good online education tends to be more practical. There is none of the intellectual posturing that I’ve seen in physical classrooms; there are no random classes you need to take to get a fancy piece of paper. I love being able to choose a topic and learn ONLY that– and get right down to business in the first lesson.

  • Formal education is often centered around getting students jobs, not helping workers do their jobs well. I already have a job, and I want to learn real, usable skills, not “marketable” ones.

My main complaint with MOOCs was that they tend to be short (in comparison to a formal course), but Coursera has addressed that somewhat with their specializations. A specialization is a series of courses, but it’s more than just disparate courses that are strung together; it’s a thoughtfully designed curriculum that builds up on knowledge from previous courses. Last year, I began learning Python.

Why Python? Others might have different reasons, but here were mine:

  • Python is one of the best languages to learn for data analysis (the other being R). I’ve always been interested in data visualization, and as a load tester, I’m frequently exposed to large quantities of data that I somehow need to make sense of.

  • Python is pretty good at retrieving data from websites, and I wanted to explore how good it is to use in load testing. I’m always eager to learn different ways to test, and I’ve wanted to try Locust for a while.

  • Python is increasing in popularity, and I wanted to see why.

So I decided to take the Python for Everybody Specialization from the University of Michigan (via Coursera) to get an introduction to this cool language. The specialization consists of five modules, each of which I had to take separately:

  • Programming for Everybody (Getting Started with Python)

  • Python Data Structure

  • Using Python to Access Web Data

  • Using Databases with Python

  • Capstone: Retrieving, Processing, and Visualizing Data with Python

The specialization was really fun, and the teacher, Charles Severance, is fantastic. I’d taken courses from him before, so I knew what to expect. He didn’t disappoint. He has a way of explaining daunting technical concepts in a way that’s easy to digest for beginners.

You can check out my certificate here. I’m pretty happy with my progress. I’m by no means a Python expert now, but I’m definitely eager to keep learning how to do more things with this new knowledge.