From statistics to machine learning use cases in international business
Welcome to the course titled Quantitative Methods in International Business of the M.Sc. International Business offered by the International Business Department at HEC Montreal. In this course, we will aim at doing mainly two things:
The Quantitative Methods Domain: the first one is to have a conversation about the concept of “Quantitative Mehods in International Business” during this semester. We have organized synchronous and asynchronous sessions with material covering the topics of Quantitative Mehods in International Business as well as some of its elements: Data Science and AI. We will discuss the digital transformation of firms as well as our societies. We will have conversations about AI and Ethics for instance and AI and Public Policies.
The Practicum: The second goal is to work on a use case that will combine: (1) the mobilization of the whole perimeter of Data Science, (2) be at the heart of the question of digital transformation, (3) has an AI and ethics dimension and (4) has an AI and Public policy dimension. During this semester, we will help you get ready to offer an AI-related tool to the Covid-19 pandemic. The goal here is to mobilize your knowledge to offer a contribution to humanity’s fight against Covid-19.
In terms of pedagogical approaches, we can talk about (1) the content delivering methods and (2) the technological tools we will be using for the students to take ownsership of the learning process.
This course will have synchronous sessions with live conferences, synchronous sessions with breakout channels for team work, asynchronous material, synchronous sessions for Q&As and synchronous office hours in order to support students for their practicum.
This course will also rely on our technological platform. this platform is first designed for our research purposes - not for teaching - but we think it is an interesting set of tools for students to experience a hands-on experience on the cutting-edge tools we use in research. For this goal, students will have access to a communication platform - our Chat platform -, a virtual campus where they will have access to a lot of code we are using in research, and to a computing platform where they will be able to integrate their R code.
This course is also about using the whole Data Science perimeter, notably for their practicum. From Data Wrangling to predictive modelling through data visualization and GIS. You will use structured and unstructured data. To make you realize how large this perimeter of Data Science is, we will run a simulation about Covid-19.
In this course we will use R as the core programming language,and you will also be trained in Stata. And through all the sessions we’ll talk about digital transformation.
All the deliverables are due on Sunday April 19, 2020.
The course runs from January to April 2021. During this period, students will work on our communication platform as well as our analytical platform.
[Unfold some info by clicking on the triangle pictogram]
Session 1: Welcome to Quantitative Mehods in International Business here
During this first session instructors and students will introduce themselves. Instructors will present the course syllabus, objectives and evaluation criteria.
We will introduce our practicum and the associated resources that will help you realize your final project for this course.
Session 2: From Single to Multiple Linear Regression ? here
An introduction to the powerful Industrial Revolution 4.0 and its main engine: AI. In this course, we will explore AI, the differences between Automated Intelligence and Quantitative Mehods in International Business.
install R and Rstudio on your computer, create an account on github and connect to our account in your Rstudio session.
This session can be as long as 205 min instead of 180 min if the R material is very new to you. If it is not that new, then you should go faster.
Session 3: Interaction and Moderation here
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Session 4: Logistic Regression here
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Session 5: Multinomial Regression here
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Session 6: PCA and Factor Analysis here
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Session 7: Midterm exam here
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Session 8: Structured Data in IB I: Supervised Learning here
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Session 9: Structured Data in IB II: Unsupervised Learning here
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Session 10: Unstructured Data in IB I: Supervised Learning here
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Session 11: Unstructured Data in IB II: Unsupervised Learning I here
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Session 12: Unstructured Data in IB III: Unsupervised Learning II here
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Community Values
It Is Essential to Foster a Supportive Online Learning Environment.
At HEC Montreal, we believe it is essential for all participants to exemplify and uphold HEC’s Community Values in order to foster a supportive online learning environment where individuals can have open discussion, reflect on their thinking, and learn from each other.
Our Lab’s Honor Code
A Commitment of Honor, Honesty, and Stewardship.
Our Honor Code supplements the statement of Community Values and reflects the commitment participants make as members of the learning community to participate in, foster, and uphold our Lab’s Learning Model.
You will find some of the tools we will use here: www.lab.nuance-r.com:
Before Friday, you need to:
That’s it!
For attribution, please cite this work as
Warin (2020, Sept. 1). Thierry Warin, PhD: [Course] Quantitative Methods in International Business. Retrieved from https://warin.ca/posts/course-msc-qmib/
BibTeX citation
@misc{warin2020[course],
author = {Warin, Thierry},
title = {Thierry Warin, PhD: [Course] Quantitative Methods in International Business},
url = {https://warin.ca/posts/course-msc-qmib/},
year = {2020}
}