I Graduated from the Harvard MDE Program, and this is the Recap of My Wonderful 2 Years
On May 28th, 2020, I finally graduated from the Design Engineering Program at Harvard University. I spent over three and a half years of my life since the very first moment I started considering going to graduate school.
This blog, which I started as a record of my graduate school life, has successfully continued, ending up writing in both Japanese and English with a total of 54 entries. Average that out with 24 months of my approximate graduate school length; I’ve been writing about 2.25 entries per month.
Many people around me were kind enough to let me know that they’ve been reading the blog, so although I graduated from Harvard already, I intend to continue my newly acquired writing habit.
Blog entries of my graduate school life at Harvard in Japanese.
Blog entries of my graduate school life at Harvard in English.
Dreamt of Going to Graduate School
After numerous failed attempts to apply for graduate schools, I was determined to make it happen this time, and I meant it. To finance my education, I applied for the Fulbright Scholarship Program and went through the interview process. I was lucky enough to earn this scholarship has enabled me to study in the United States.
The reason I went to graduate school.
How would I finance myself?
Applying to MIT Media Lab.
Applying to Harvard GSD.
So I Came to Harvard
After applying to various schools, I got admitted to Harvard. I took a leave of absence from my job and moved with my family to Cambridge, Massachusetts, in August 2018. Settling down to Cambridge, my adventurous two years began.
Things I made Part 1 / Part 2 / Part 3
I’d also like to list the things I have covered during these two years. As a way to get exposed to various experts efficiently, I think going to graduate school is a great way to achieve this.
Design Engineering Topics
design thinking / systems thinking / creativity / design strategy / design research / prototyping / visualization / stakeholder analysis / root cause analysis / sustainability analysis / standards & intellectual property /manufacturing processes & operations / organizational behavior and leadership / government & public policy / basic accounting & finance / society & culture / strategic foresight / material life cycles / business modeling / value proposition map / conflict management and resolution / ethnography / entrepreneurship / innovation / storytelling etc…
Technical Topics
Processing / p5.js / firebase / openFrameworks / ml5.js / tensorflow.js / R / ggplot2 / dplyr / Python / scikit learn / numpy / matplotlib / seaborn / pandas / Rhino / Grasshopper / C# / Unity / openCV / Runway ML etc…
Statistics / Probability Related Topics
multiplication rule / sampling table / naive definition of probability / independent events / conditional independence / De Morgan’s Laws / joint probability / marginal probability / conditional probability / intersections / unions / simpson’s paradox / Law of Total Probability (LOTP) / Bayes’ Rule / probability mass function (PMF) / Cumulative Distribution Function (CDF) / expected value / linearity /conditional expected value / indicator random variables / Continuous Random Variables (CRVs) / Law of the Unconscious Statistician (LOTUS) / Universality of Uniform (UoU) / moments / mean / variance / skewness / kurtosis / Moment Generating Functions (MGF) / Joint CDF / marginal distributions / multivariate LOTUS / covariance / correlation / transformations / convolutions / poisson process / count-time duality / order statistics / conditional expectation / Adam’s Law / Eve’s Law / Law of Large Numbers (LLN) / Central Limit Theorem (CLT) / Markov Chains / uniform distribution / normal distribution / exponential distribution / beta distribution / chi-square distribution / Bernoulli distribution / binomial distribution / geometric distribution / first success distribution / negative binomial distribution / hypergeometric distribution / Poisson distribution / multinomial distribution / multivariate uniform distribution / multivariate normal distribution etc…
Data Science / AI Related Topics
data scraping / knn regression / linear regression / polynomial regression / multiple regression / regularization / exploratory data analysis / logistic regression / multiple logistic regression / knn classification / PCA / simple decision trees / bagging / boosting / stacking / XGBOOST / Random Forest / perceptron / back propagation / regularization / dropout / batch normalization / stochastic gradient descent / MLP / AB testing / causal inference / randomization testing / adaptive and multi-arm bandit designs / smoothing / basis functions / generalized additive models / unsupervised learning / bayesian statistics / text analysis / CNN / RNN / GAN / Cycle GANs / Reinforcement Learning / Deep Reinforcement Learning / Variational Inference / Transfer Learning etc…
I wrote about the things I learned in a few of the entries in the past.
Jumping into statistics without almost no background
Data Science Part 1 / Part 2
Making the Knowledge Work for You
Not just the knowledge, but I found it extremely helpful to work on projects, organically connecting the things I learned and putting the theory into actual practice. This process was even made better by being exposed to work on projects collaboratively with my fellow cohorts.
Engaging in Mental Health and Artificial Intelligence at MIT
Things I learned through my design engineering classes Part 1 / Part 2 / Part 3 / Part 4 / Part 5 / Part 6
The past two years, I went through was like an arrow. Not just by myself, but I was able to accomplish so much through the help of my family. I want to connect the things I’ve learned in graduate school into real life and work on something impactful, and hopefully build an ongoing career.
So, my challenge of going to graduate school has come to an end finally!
For those who have read so far, thank you for your readership, and I genuinely appreciate it!😀
