Who am I to say?

My name is Jeff Winchell and I live in Cambridge, MA. I am a dad, computational social scientist (formerly a data scientist), Harvard grad student, sporadic comedy writer, former racer (kind of an expensive hobby) and sometimes slam poet.


You can reach me at Jeff_Winchell@g.Harvard.Edu, on Skype at live:CompSocialSci or even by an actual phone call or a meeting for coffee. How non-virtual. πŸ˜‰

Returning to the theme of the above graphic, I’ve taken 5 courses towards my master’s – Big Data Analytics, Introduction to Data Science, Deep Learning, Advanced Scientific Computing and Probabilistic Programming. This semester I am taking Advanced Python for Data Science, Advanced Topics in Data Science and auditing two more courses Advanced Quantitative Research Methodology (Political Science) and Computational Analysis (Sociology). I had taken about 70 classes at Northwestern by the time I got my bachelor’s degree in math.

I’ve also completed 71 MOOCs over the past 6 years (and continue to take them concurrent with my master’s degree work). Here’s a list of my favorites (data science related courses listed first). In my view the first class in this list should be part of the required curriculum before taking any machine learning or deep learning class anywhere.

CaltechLearning from Data
Eindhoven Technische InstituteProcess Mining: Data Science in Action
DeepLearning.AIImproving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
StanfordMachine Learning
DeepLearning.AINeural Networks and Deep Learning

Convolutional Neural Networks

MITIntroduction to Computer Science and Programming Using Python
ColumbiaBig Data in Education
MichiganSocial Network Analysis
Johns HopkinsR Programming
Univ of IL-Urbana-ChampaignText Mining and Analytics
Univ of Texas-AustinLinear Algebra – Foundations to Frontiers
HarvardIntroduction to Linear Models and Matrix Algebra
Univ of IL-Urbana-ChampaignPattern Discovery in Data Mining
Johns HopkinsPractical Machine Learning
Steve BlankHow to Build a Startup
UC-San DiegoLearning How to Learn: Powerful mental tools to help you master tough subjects
WesleyanSocial Psychology
Ohio StateCalculus Two: Sequences and Series
Case Western ReserveInspiring Leadership through Emotional Intelligence
StanfordHow to Learn Math: For Students
HarvardLeaders of Learning
Univ of LondonSupporting children with difficulties in reading and writing
StanfordCrash Course in Creativity
StanfordGame Theory
VirginiaEffective Classroom Interactions: Supporting Young Children’s Development
UC-BerkeleyThe Science of Happiness
HarvardUnlocking the Immunity to Change: A New Approach to Personal Improvement
Higher School of EconomicsIntroduction to Neuroeconomics: how the brain makes decisions
EdinburghThe Clinical Psychology of Children and Young People
Ohio StateCalculus One
Cal Institute of the ArtsIntroduction to Programming for Musicians and Digital Artists