Why MIT’s Data, Economics, and Development Policy program

I’ve taken all 6-courses in the DEDP program over the past 18-months. I learned a lot, including a few things I’d have done differently. I wanted to share my experience in case it helps others considering the course.

For context, I took the program while working full-time as a software product manager. I had no prior economics experience or education.

Most material is delivered via pre-recorded lectures.

Program Overview

  • The program is composed of 5–7 graduate-level courses delivered online via pre-recorded lectures, readings, homework, and exams. More here.
  • Course pricing is income-based and (then) ranged between $100 to $1,000 USD. You can also take them free if you don’t want the certificate.
  • Content is delivered via 3 hours of pre-recorded lecture videos each week. Lectures are divided into 5–10 minute segments separated by 1–3 question quizzes (“finger exercises”).
  • Homework must be completed each week, but can be done at your own pace during the week. You can also work up to 3-weeks ahead of schedule.
  • There are open-book final exams, plus proctored final exams for credential-seekers. Grading is heavily weighted towards finals.

My Experience

I tried to complete all 6-courses in one semester, but quickly abandoned that idea. The sheer volume of material was overwhelming and it was very difficult to follow the advanced courses without doing the earlier ones first.

In the end, here’s how I approached it:

  1. February to April: Microeconomics, Challenges of Global Poverty
  2. May to July: Data Analysis for Social Scientists
  3. September to November: Political Economy, Randomized Evaluations
  4. February to April (2021): Foundations of Development Policy

If I could do it again, I would complete Khan Academy’s Calculus course before taking Microeconomics. Microeconomics required taking partial derivatives. I had taken Calculus in high school 10-years ago and Principles of Microeconomics in university 9-years ago, but never done this before and had only a rudimentary understanding of derivatives general. I got stuck and ended up learning mid-course via YouTube— not ideal.

I would also complete Statistics and Probability via Khan Academy before taking Data Analysis. I ended up taking Statistics and Probability in the 2-weeks between the end of the course and the proctored final exam, which saved my exam grade but was hectic. I had taken Business Statistics I & II in university, but the course required a much stronger understanding and ended up being the hardest part of the program for me.

Had I taken the two courses above, I’m reasonably confident I could’ve done the course in 3 semesters instead of 4, taking Randomized Evaluations and Foundations of Development Policy each one semester earlier.

I spent about 4–6 hours per week per course. Usually I would watch lecture videos in the evenings during the week and do homework on the weekend. I found the homework took about 1–3 hours for each course.

Where it got difficult for me was when I would run problem where I didn’t understand the underlying concept. For example, when taking a partial derivative in Microeconomics or an integral in Data Analysis. In these cases, I would try other sources, usually Khan Academy or YouTube, but these could be long, multi-day detours to address major gaps in my foundational understanding.

Final Thoughts

Prior to this program, I’d never taken an online course or studied economics. I was looking for something that would help me be more effective at work, seeing through complex problems, measuring outcomes, and predicting what will work.

I considered the course to have been a success in all of these areas, and would absolutely do it again. I recommend it highly. The opportunity to access world-class lecturers for free, on a flexible schedule is really quite an incredibly opportunity and one I am very glad MIT has made available.

Last updated June 6, 2021



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Wade Lahring

Wade Lahring

Product manager at Benevity, building software for the employee giving and volunteering programs of 35% of the Fortune 500, including Google, Apple, and Amazon.