Coursera class: Principles of Reactive Programming

A few weeks ago, I completed the "Principles of Reactive Programming" class led by Martin Odersky, Erik Meijer and Roland Kuhn. This Coursera class started in November 2013 and was around 7 weeks long. It was a great class in which we learnt how to write reactive programs in Scala. The course mainly covered Futures, Promises, Observables, Rx streams and Akka Actors. It was quite challenging but the assignments were very enjoyable. We wrote a virus simulation and a wikipedia suggestions app!

Update (30 Aug 2014): I have committed my assignment solutions to my GitHub repository.

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Coursera class: Functional Programming Principles in Scala
Stanford's Online Courses: ml-class, ai-class and db-class

Coursera class: Functional Programming Principles in Scala

I thought I'd mention that one of my highlights of last year was completing the "Functional Programming Principles in Scala" class led by Martin Odersky, the designer of Scala. This Coursera class started in September 2012 and was around 7 weeks long. Learning about functional programming was a rewarding experience and I found the course and assignments quite challenging, but immensely enjoyable. I even managed to get a distinction! I believe this course will be running again this year and I'd highly recommend it to people who wish to discover functional programming and Scala.

I have committed my assignment solutions to my GitHub repository.

I am now looking forward to starting some new classes in 2013!

Related posts:
Stanford's Online Courses: ml-class, ai-class and db-class

Stanford's Online Courses: ml-class, ai-class and db-class

About three months ago, I signed up to Stanford's first-of-its-kind, free, online courses on Artifical Intelligence, Machine Learning and Databases. I have now successfully completed all three courses!

• The Artifical Intelligence (ai-class) class, led by Sebastian Thrun and Peter Norvig, covered probability, Bayes networks, machine learning, planning, Markov decision processes (MDPs), particle filters, game theory, computer vision, robotics and natural language processing. There were in-class quizzes, homework exercises and two exams.
• The Machine Learning (ml-class) class, led by Professor Andrew Ng, covered supervised learning (linear regression, logistic regression, neural networks, support vector machines), unsupervised learning (k-Means clustering), anomaly detection and recommender systems. There were in-class quizzes, review questions and programming exercises.
• The Introduction to Databases(db-class) class, led by Professor Jennifer Widom, covered relational databases, relational algebra, XML, XPaths, SQL, UML, constraints, triggers, transactions, authorization, recursion and NoSQL systems. There were in-class quizzes, assignments, including practical exercises (such as creating triggers, writing SQL or XPaths that would run on a set of data) and two exams.

Even though I had studied these topics a long time ago at university, I found it really useful to refresh my memory. They took up quite a bit of time (about 2 hours a week for each class), but it was definitely worth it.

I am now looking forward to starting some new classes in 2012!