The choice to pursue my Master's Degree was fueled by a desire to maintain a competitive edge, not to lose relevance in the job market, and to ensure I didn't get stuck in the first job I accepted after undergrad. However, I'm not sure I would have committed right away if it weren't for the program offering at Western Governors University (WGU).
WGU allows students to pace themselves through classes which permits them to work as quickly or as slowly as they would like (as long as they meet the minimum term requirements). Also, instead of paying per credit, students pay per six month “term”.
After hearing this, I knew I would be capable of completing courses quickly and potentially pay a lot less money than I would at a traditional program while saving a lot of time.
I finished my first few courses within a couple of weeks. My major was Data Analytics and the first three courses I tackled were: Fundamentals of Data Analytics, Programming in Python, and R for Data Analysts. These were easy for me as I had spent a lot of time working with statistics and learning how to program during undergrad.
The competency-based learning model helped a lot too. Instead of sitting through lectures pretending to learn things I already knew, I was able to almost immediately be tested and receive credit for all of the extracurricular learning I had already done in my academic career.
The next two classes took me about a month to complete. Advanced Data Visualization covered a lot of data visualization concepts I was already familiar with but it went in depth into how to create effective graphics in Tableau (a program I had used but not extensively), and Statistics for Data Analysis was a beast but I was ultimately able to complete it in a few weeks.
Prior knowledge played a role in these courses but effective study techniques were much more important (especially in statistics). For me, it was helpful to outline all of the core competencies and diagram the subcomponents that made them up. Then, make sure that each component was sufficiently understood, one-by-one.
Finally, I completed Data Mining and Analytics I in just under a month. This one took me longer as I began to venture into new topics that pushed me out of my comfort zone. For me, the biggest strategy for learning new topics is finding a way to relate the information to topics you already know and slowly build on that until you breach the gap.
Finishing these classes put me at an important milestone: finishing approximately half of my Masters in approximately two months. Since then, I have finished two more classes in about the same amount of time (SQL for Data Analysis and Data Mining and Analytics II) and have three more classes to go.
The structure of the program has allowed me to accomplish a lot in my personal life as well as my academic life. During this time I was able to maintain side projects (like my personal website), start a new job (sometimes working 70+ hours a week), and relocate for work.
I look forward to completing my degree this year and sharing what I've learned.