MIT_18.S097

Dates: Jan 17-20, 2023

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

Room: This class will meet in 2-131.

(The lectures have been recorded and links to videos are available below)

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, like Python, 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 deploy such model in production environments and scale the computations beyond a single computer.

This course does not require from the participants prior detailed knowledge of advanced machine learning algorithms not the Julia programming language. What we assume is basic knowledge data science tools (like Python or R) and techniques (like linear regression, basic statistics, plotting).

Installation instructions Installation instructions can be found in materials for the day 1

Once installed the code can be run as

using Pkg
Pkg.activate(".") # assumes running the code in the main folder of this repository
using IJulia
notebook(dir=".")

Schedule (all times are EST time zone)

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.