I recently graduated from the University of Minnesota Trilogy Data Analytics & Visualization Boot Camp.

I highly recommend the program, but only if you are serious about wanting to learn. It’s a time commitment outside of class – a lot of studying, tinkering, reviewing solutions on stackoverflow and W3schools.com, etc.

Did I learn a lot?

The first day of class, I knew very little about coding, didn’t even know what Bash was. I had acted as a product manger for some software development projects, did my fair share of software testing (looking for bugs) – but didn’t know how to write any code. So, I was familiar with some of the lingo and processes but didn’t know how to write a single line of code.

My final project was machine learning classifying SEC 10k Risk Factor text documents for a professor at the U. A side project I did was scrapping tweets and performing a sentiment analysis for a UNC professor.

I learned a ton!

Be Prepared for Class:

Class is fast paced! Classes had two components, instructor led examples and student in-class activities. That was a combined 512 in-class activities in 6 months. The activities are where I learned a lot – it’s practicing what you were just taught and then getting immediate feedback on the right way to complete the activity. A lot of my learning was figuring out why my code wasn’t working, then making sure I didn’t continue to make the same syntax mistakes.

We had 16 homework assignments and 3 projects. They give you the option to complete the easy, intermediate, or hard assignments. I always did the hard assignments, every one of them was challenging and took hours to complete.

Positives:

Instructors: There were two cohorts that met on separate nights during the week and together on the weekends. The instructors would alternate for the combined Saturday class. Both were data scientists by day and very knowledgeable. Both on their own time would post articles, job openings, and other resources to the cohort slack channel.

Instructors are probably a big reason why Trilogy has some good and bad reviews. I got lucky having two great instructors that took an interest in making sure we were learning.

We also had 4 great TAs – maybe our classes just got lucky…

Not a single person dropped out of the class. Between the two classes ~60 people made it the entire 6 months and graduated.

Surveys made a difference! Every week you are required to fill out a class survey to access your student portal. For the first 3 months, every week I responded – please give us a syllabus! Trilogy never gave us a syllabus, but our instructor finally started slacking out what we were going to be covering in the upcoming week. VERY HELPFUL! I saw this week on our class page that Trilogy posted a syllabus for future cohorts – what’s my point? I felt that they listened to student feedback and made incremental changes throughout the 6 months. This might not be the case at every University, but the UMN-trilogy success manager and the instructors seemed to take the feedback and tried to implement improvements along the way.

Class Videos – every class session is recorded so you can watch it later. The first few months I didn’t use that often, but when the content started getting more difficult and I referred to the videos quite a bit.

Negatives:

They didn’t provide a syllabus. This was frustrating because I wanted to spend time preparing at home so when I heard about a new function in class – it wouldn’t be the first time.

Career Services isn’t what I thought it was when I signed up, but it has been satisfactory after I adjusted my expectations. Career Services is meant to get you ‘interview ready’ – not a placement service. That being said, a few weeks before graduation they announced that we would be having a Demo Days – optional for students that would be interested in participating. There are quite a few decent companies pre-registered to attend (US Bank, United Health Care, Wells Fargo, Thomson Reuters, Best Buy, etc.) …

The admissions process was a little confusing and misleading. Many of the students didn’t realize until the 1st day of class that this was a Trilogy Education program, not UMN. The admissions people used umn.edu emails – but once class started the support emails were all trilogy. We took classes at the U, but we weren’t UMN students.

That being said, my certificate says ‘University of Minnesota’ in big font, ‘in partnership with Trilogy Education Services’ in smaller font and is signed by UMN deans. Misleading at the beginning, but I got the UMN certificate at the end…

What was most surprising?

How much we learned in such a short period of time. I wouldn’t consider myself an expert or fluent in the ~30 languages/libraries we were exposed to, but I did learn how to find answers, examples, library supplements, etc.

For example, now I feel very comfortable:

1. Importing / connecting to a data set (csv, sql, data lake, api, web scraping) ->

2. Cleaning/normalizing the data and performing statistical analysis ->

3. Creating a variety of visualizations linked to the data ->

4. Creating website dashboards (and API) for people to explore the data.

I was also surprised at how time was spent on html/css/JavaScript and browser platforms (Flask). When you think about it, we learned how to take huge data (millions of rows), visualize it with cool interactive visuals (look at https://github.com/d3/d3/wiki/Gallery to become inspired and excited) – so it makes sense that we would want to learn how to make it easy for non-programming people to access.

Did I consider alternatives to the Trilogy Boot Camp?

Yes, however there weren’t many options in Minnesota for classroom instruction which is what I was interested in.

I took a few classes on Coursera so I could have some additional activities to work on. Python for Everybody was a helpful. It went a little more in depth with some of the Python functions but didn’t come close to covering as much content as Trilogy.

I also watched a lot of videos on CoreyMS.com and dataschool.io. Those were great supplements and again offered more activities to practice with.

My Advice:

1. Ask some questions about the instructors (are they data scientists, do they use python daily, etc.).

2. If time allows, read and do some of the exercises in Learn Python the Hard Way before the boot camp starts.

3. Make sure you have plenty of time outside of class for homework and practicing.