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 (pszufe@sgh.waw.pl) 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.
