[bioundgrd] Fwd: IAP 2018 Offering: - 15.S41, Software Tools for Business Analytics

[Janice Chang]

Begin forwarded message:

From: Scott Alessandro <salessan at mit.edu<mailto:salessan at mit.edu>>
Subject: IAP 2018 Offering: - 15.S41, Software Tools for Business Analytics
Date: January 16, 2018 at 11:10:23 AM EST

Hello All.
Would you mind sending the below course announcement to students in your department. There are still seats available in this IAP course. Thanks!

15.S41: Software Tools for Business Analytics
January 22-26, 1-4 pm in E52-164
3 units, P/D/F grading
Because of the "big data revolution," there is an ever-increasing need for techniques for analyzing data, developing mathematical models, and using these models to make informed decisions.   To get started in this process, one needs a working knowledge of business analytic software tools.
The goal of this course is to provide students with a baseline knowledge of business analytics software tools that they can use in MIT courses, UROPs involving data analysis, and summer internships or jobs after graduation.
Questions?: Scott Alessandro, salessan at mit.edu<mailto:salessan at mit.edu> . Stellar Site: http://stellar.mit.edu/S/course/15/ia18/15.S41/index.html.

Session 1 (Terminal and Github) – Monday, January 22, 1-4 pm, E52-164
Description: In this session we will give an overview to working with the terminal, Github, and an introduction to the R programming language.

Session 2 (Data Wrangling and Visualization) – Tuesday, January 23, 1-4 pm, E52-164
Description: This session introduces basic techniques for data wrangling and visualization in R. Using contemporary best practices in statistical programming, we will explore a powerful set of tools for efficiently preparing, analyzing, and visualizing complex data sets. Our working example is a set of publicly available data from AirBnB. By the end of the session, students will construct a simple business intelligence dashboard for informing a realistic decision process. The session does not require previous experience with R.

Session 3 (Introduction to Machine Learning) – Wednesday, January 24, 1-4 pm, E52-164
Description: This session introduces elementary methods for machine learning in R, focusing on the two classical supervised contexts of regression and classification. Building on our data preparation techniques from Session 2, we execute a complete pipeline from “raw data,” to model training to model evaluation and communication. By the end of the session, students will creatively build and report on their own classification model. This session requires the material from Session 2.

Session 4 (JuMP/Julia) – Thursday, January 25, 1-4 pm, E52-164
Description: This session introduces the programming language "Julia" and the "JuMP" library. Julia is a high-level, high-performance dynamic programming language for technical computing, and JuMP is a library that allows us to easily formulate optimization problems and solve them using a variety of solvers. We will see how Julia and JuMP can be applied to solving real-world problems in operations and analytics.

Session 5 (Excel) – Friday, January 26, 1-4 pm, E52-164
Description: Introduce and practice with concrete real life examples on how to use the most important functions and shortcuts in Excel. The goal is to enable students to face a wide variety of problems in an efficient way in Excel. Students will be given a problem with a series of tasks to accomplish. These tasks will be solved using different Excel functionalities. Most of these problems have been based on real company spreadsheet problems.



Best,
Scott

_____________________________________________


[cid:8C0432F3-D44A-48DC-BAAF-991CC937C9F0 at mit.edu]<http://mitsloan.mit.edu/>


Scott Alessandro | Director
Undergraduate Education
MIT Sloan School of Management
Building E52-150 (in Suite 133)
50 Memorial Drive, Cambridge, MA 02142
o: 617.253.6296  |  c: 617-631-5619
e: salessan at mit.edu<mailto:salessan at mit.edu>
Pronouns: he, him, his
mitsloan.mit.edu/undergrad<http://mitsloan.mit.edu/undergrad>
MIT Sloan Commitment to Diversity<x-msg://1/mitsloan.mit.edu/about-mit-sloan/commitment-to-diversity/>

“I’m nothing without glitter” – Callie Alessandro (Age 9)


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