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Open Educational Resources

You can follow the links below to sites on which I post a variety of educational resources.  Everything from video lecture series to notebooks hosted on Github.  Follow the links and never stop learning.

One of the many services provided to achieve my goal of empowering research, is the development of teaching and learning material.  I provide many certified courses and tutorials, on the web.

My educational resources are available on Coursera, Udemy, YouTube, GitHub, and RPubs.  Please click through the links below.


Coursera brings official courses from leading Universities all over the world, right to your computer, no matter where you are.  The Klopper Research Group has two courses available on this platform.  Successful completion of these courses will see you getting an official certificate from the University of Cape Town.

The first is on biostatistics and gives you an intuitive understanding of this difficult topic, all without a single equations in sight.  It will empower you to understand the results in published papers and to conduct your own research.

The second course teaches you how to code in the newest, fastest growing, technical computer language, Julia.  It is the ideal computer language for data analysis and machine learning.


Udemy is a massive open educational platform that allows anyone to share their knowledge.  The Klopper Research Group currently has three courses available for you.

The first teaches the fundamentals of the Wolfram Language in Mathematica.  This is a choice computer language for all data analysis.  It makes knowledge computable and is the only language to have data built right into its core.

The second course shows you how to leverage the power of the Wolfram Language to do your own data analysis and statistics.

The third course show you how to use the perennial biostatistics favorite, SPSS.

A new course on the fundamentals of biostatistics using Python is now also available.  If you are new to research and want to learn how to do your own data analysis, then this course is for you.


YouTube is everyone’s favorite site, not only to consume entertainment, but also as a go-to place to learn.  The Klopper Research Group has over 1,300 tutorials on this platform.  Click on the PLAYLIST tab to view all the available courses.

There are quite a few new additions to my YouTube playlists.  I am most excited about the series on deep neural networks using Keras and TensorFlow for R.  It is a series of tutorials for domain experts (healthcare, business, etc.) who want to learn about this form of machine learning, from scratch.  The files for this series are available on GitHub and RPubs.  There are also video tutorials on how to use the Wolfram Language to create deep neural networks.

I have started a video tutorial series on human anatomy using the Wolfram Language in Mathematica.  This series aims to teach both anatomy, but also introduces the use of computer code through the idea of a computational essay.  The Wolfram Language is ideal for this.  I think it is a very interesting teaching concept.  Take a look.

Now Instagram has joined my list of platforms for education.  My docjuank account has become a mini textbook for surgical topics.  The InstagramTV feed for this account also contains short videos to help medical students prepare for their written exam.

My MOOCs on Coursera®

Continue on the my two massive open online courses on Coursera®.  The first teaches an intuitive understanding of healthcare statistics and the second using medical data to teach you how to write code in Julia, the scientific computing language.

Mathematics lectures on YouTube®

My various video lecture series on YouTube covering a variety of courses in mathematics.

Python and Julia lectures on YouTube®

My video lecture series on YouTube covering Python for statistical analysis and the Julia computer language.

Jupyter notebooks on Discrete Mathematics

This is a link to my notes on discrete mathematics.  These notes are made in downloadable Jupyter notebooks using Python in which I explain both the concepts of discrete mathematics and how to use Python to solve problems.  I also add all the PNG images files and even the original Adobe Illustrator files that are used in the notebooks.


Jupyter notebooks for MIT 18.06 Linear Algebra

Now, this is very exciting for me.  Quite some time ago I first watched the Massachusetts Institute of Technology (MIT) OpenCourseWare (OCW) lectures on Linear Algebra (18.06).  In this series the wonderful Gilbert Strang gives a most fantastic introduction to the topic.

I could not resist making my small contribution  and created a Jupyter notebook for each of the lectures.  I took a chance and contacted Prof Strang to ask permission to make this work available on the web.  He immediately replied in the affirmative and I am both thankful and honored.  The actual .ipynb files are available on my GitHub page.