Brief Overview of a 360-in-525 Minutes Course Set

For more details see Overview of a 360-in-525 Minutes Course Set in Data Sciences, Spring 2018

360-in-525-4: Mathematical, Statistical and Computational Foundations for Data Scientists

Three-full-day workshops (3 hp) on May 11, 18 and 25 2018. Prerequisites: current proficiency in high-school level mathematics (pre-calculus, geometry and algebra with some programming experience beyond Excel). Target Audience: any MSc or PhD student at UU who wants to understand the mathematical statistical foundations in the data scientist’s computational toolbox. The approach will use formal mathematical communication of concepts starting from sets and logic, but with concomitant development of computer programming skills to algorithmically construct and implement the concepts. Topics will include: Sets, Maps, Functions, Modular Arithmetic, Axiomatic Probability, Conditional probability, Pseudo-random constructive understanding of random variables and structures including graphs, Statistics, Likelihood Principle, Bayes Rule, Decisions (parametric and non-parametric) including tests and estimators, Markov chains and their pseudorandom constructions, etc. We will use SageMath locally and collaborate in COCALC during the lab/lectures.

Background and Context:

This is a mathematically more careful (at an advanced undergraduate level) version of UC Berkeley’s most popular freshman course:

  • with the formula:
    • computational thinking + inferential thinking = data science
    • as talked about at the end here.

Prepare your laptop:

SOFTWARE: We will be using SageMath/Python ecosystem for the next three Fridays. Follow the download and installation instructions for your Operating System from the following URL:

To test that you have installed correctly do the following:

  • On a Mac OS X or Unix/Linux syatem, say you installed sage in a directory inside your home directory called ~/all/software/sage/, then you can see if the following command launches a Jupyter notebook server successfully:

$ ~/all/software/sage/SageMath/sage -n jupyter

Course Content

Download the zip file of SageMath ipynb notebooks from:

After downloading the zip file, unzip it inside the directory you launched the sage jupyter notebook server from. You should be able to see all the jupyter .ipynb notebooks by navigating from your jupyter notebook server.

Individual SageMath Jupyter .ipynb Notebooks

Use the above archived .zip file directly!

YouTube Archive of lab/lectures