# Megan Taylor

## web developer, hack-n-slasher, freelancer, news & data junkie, bibliophile, Flyers fan, sci-fi geek and kitteh servant

My first instinct was to include the code for each course with my weekly update, but I’ve seen a lot of comments in the forums of most of these classes requesting that we not publish answers. So I’m just gonna go over what gets covered each week and my observations on MOOCs and the differences in each course.

#### Computing for Data Analysis:

Dropping this for now. I know R is very useful for data analysis, but I’ve made it 3/4 through the course without really learning ANYTHING, even though I’m getting perfect scores on the quizzes and assignments. The class is just going too fast for me to grasp the concepts without devoting a lot more time than I have now. Note to self: Come back to R at some point.

#### Learn to Program: The Fundamentals:

This week was all about string operations: comparisons, substrings, `len()`, string methods, `dir(str)`, indexing, slicing, and `for` loops over `str`. Also covered accumulators and IDLE’s debugger. Quiz was fairly easy, run things in IDLE, play with `str.find`. The assignment was fun and just hard enough to be interesting.

#### An Introduction to Interactive Programming in Python:

Really good lectures. And the RPSLS exercise was fun. But I still don’t understand modulo. Especially with negative numbers.

#### Introduction to Statistics:

Although the accent is sometimes hard to understand, I’m really enjoying this one. Slow enough that I can follow, interesting examples.

#### The Mechanical MOOC: A Gentle Introduction to Python:

Got an email containing the first week’s worth of work on Monday. This MOOC is different from the others; instead of a self-contained curriculum, they have chosen parts of existing platforms. For example, this week we needed to read some sections from How to Think Like a Computer Scientist, watch a lecture from MIT’s Introduction to Computer Science, do some exercises in Codecademy’s Python course, and work through exercises from MIT’s A Gentle Introduction to Computer Science.