Love of learning

I’ve surely reached the point where every new thing that goes into my brain knocks at least one thing out, but I haven’t stopped trying.

Not content with an undergraduate degree from Penn State and an MS from University of Washington, I’m still at it, taking online classes and even some in real life. I suppose that means I should have done a PhD.

There’s always more to learn.

2024 Large Language Model Agents Dawn Song, Xinyun Chen UC Berkeley
2024 DLRL Summer School   Vector Institute
2023 AIML 420 Artificial Intelligence Heitor Murilo Gomes, Fangfang Zhang, Yi Mei Victoria University of Wellington
2022 Fast.ai Jeremy Howard Fast.ai
2021 Deeplearning.ai Natural Language Processing Younes Bensouda Mourri & Łukasz Kaiser Coursera / deeplearning.ai
2020 Functional Programming in Haskell Jeremy Singer & Wim Vanderbauwhede FutureLearn / University of Glasgow
2019 Tensorflow Laurence Moroney Coursera / deeplearning.ai
2019 Applied Functional Programming in Haskell Wouter Swierstra Utrecht University
2018 Deep Learning Andrew Ng Coursera / deeplearning.ai
2016 Building the Data Pipeline Jason Kolter UW
2015 Scalable Machine Learning Anthony D. Joseph Edx / UC Berkeley
2015 Introduction to Big Data with Apache Spark Ameet Talwalkar EdX / UC Berkeley
2014 Introduction to Functional Programming Erik Meijer EdX / Delft University of Technology
2014 Statistical Learning Robert Tibshirani & Trevor Hastie Stanford
2013 Data Analysis Jeff Leek Coursera / Johns Hopkins
2012 Functional Programming Principles in Scala Martin Odersky Coursera / École Polytechnique Fédérale de Lausanne
2012 Probabilistic Graphical Models Daphne Koller Coursera / Stanford
2011 Machine Learning Andrew Ng Coursera / Stanford