pszufe/2024_mit_18.s097_introduction-to-julia-for-data-science

MIT_18.S097 Special Subject in Mathematics: Introduction to Julia for Data Science

MIT_18.S097

Dates: Jan 16-19, 2024

Time: TWRF 11am-12:30pm; 1pm-3pm

Location: Matchessusets Institute of Technology, Boston, MA, USA

Room: This class will meet in 2-132. See http://whereis.mit.edu/?mapterms=2-132 for location.

Data analysis has become one of the core processes in virtually any professional activity. The collection of data becomes easier and less expensive, so we have ample access to it.

The Julia language, which was designed to address the typical challenges that data scientists face when using other tools. Julia is like Python, in that it supports an efficient and convenient development process. At the same time, programs developed in Julia have performance comparable to C.

During this short course, you will learn how to build data science models using Julia. Moreover, we will teach you how to scale your computations beyond a single computer.

This course does not require the participants to have prior detailed knowledge of advanced machine learning algorithms nor the Julia programming language. What we assume is a basic knowledge of data science tools (like Python or R) and techniques (like linear regression, basic statistics, plotting).

Schedule (all times are EST time zone)

Day 1 (Tuesday, Jan 16, 2024)	11am-12:30pm	Your first steps with Julia	https://youtu.be/LKXoL3-RgAA
	1pm-3pm	Working with tabular data	https://youtu.be/J8j1FUFMxpQ
Day 2 (Wednesday, Jan 17, 2024)	11am-12:30pm	Classical predictive models	https://youtu.be/l6EABeDO6gE
	1pm-3pm	Advanced predictive models using machine learning	https://youtu.be/6o_e65_0JY0
Day 3 (Thursday, Jan 18, 2024)	11am-12:30pm	Numerical methods	https://youtu.be/z85xnl7CfSA
	1pm-3pm	Solving optimization problems	https://youtu.be/2PzuwDUIV3A
Day 4 (Friday, Jan 19, 2024)	11am-12:30pm	Differential equations	https://youtu.be/4Q6RhKbpaiI
	1pm-3pm	Scaling computations using parallel computing	https://youtu.be/XtMZmSz5yMk

Grading

You can register for this course for credit. The contact point regarding the registration process is Professor Alan Edelman, Julia Lab Research Group Leader. The evaluation of the course will be based on assessment of a homework that will be distributed during the last day of the course and should be sent back to Przemysław Szufel ([email protected]) no later than after one week.

This course has been supported by the Polish National Agency for Academic Exchange under the Strategic Partnerships programme, grant number BPI/PST/2021/1/00069/U/00001.