The great 2020 plan - revisited

I thought it would be good to revisit my great 2020 plan from the start of the year and see the progress that I’ve made. I’d say I’ve made reasonable progress, but not as much as I’d have liked. I put this partially down to my shifting interests - notably getting more and more interested in the world of blockchains and cryptocurrencies.

From the original plan I’d definitely still like to get the Brian Harvey lectures watched, a few more books read, and the rest of the freeCodeCamp syllabus completed. However, I have started to eye up courses in blockchain programming… 😊

Here’s the original plan -

Here’s an outline of what I’d like to achieve throughout 2020.

Math

I’ve decided to brush up on my math in preparation for a machine learning course that I’ll be starting in April.

• Complete Data Science Math Skills - Duke University
• Complete Mathematics for Machine Learning Specialization - Imperial College London
• Go through the 3Blue1Brown playlists
• Do some Khan Academy courses if necessary (Algebra I, Precalculus, Statistics & Probability, Calculus I, Multivariable Calculus, and Linear Algebra)

Data Science

Data Science-esque things took a back seat towards the end of last year (though I was using Juypter Notebooks/pandas here and there), but I’m going to be getting back into it.

• Complete Introduction to Data Analytics and Machine Learning with Python - City, University of London
• Complete the DataCamp - Data Scientist with Python career track

Web Stuff

Complete the freeCodeCamp syllabus.

The following certificates remain to be completed:

• Front End Libraries
• Data Visualization
• APIs and Microservices

Computer Science

I want to learn more about the fundamentals of computer science. These look pretty old-school but the word on the street is that they’re good:

• Brian Harvey’s Structure and Interpretation of Computer Programs lectures - University of California, Berkeley

• Ableson and Sussman’s Structure and Interpretation of Computer Programs lectures - MIT

Books

Books and essays that I’d like to read:

• Flatland (Abbott, 1884)
• A Mathematician’s Apology (Hardy, 1940)
• The Man Who Loved Only Numbers (Hoffman, 1998)
• What is Mathematics? (Courant and Robbins, 1940)
• The C Programming Language (Kernighan and Ritchie, 1978)
• The Pragmatic Programmer: From Journeyman to Master (Hunt and Thomas, 1999)
• The Mythical Man-Month: Essays on Software Engineering (Brooks, 1975)
• Hackers: Heroes of the Computer Revolution (Levy, 1984)
• As We May Think (Bush, 1945)
• Computing machinery and intelligence (Turing, 1950)
• The Annotated Turing (Petzold, 2008)
• Structure and Interpretation of Computer Programs (Abelson and Sussman, 1985)
• The Cathedral & the Bazaar: Musings on Linux and Open Source (Raymond, 1999)