Objectives

Enterprises collect large amounts of data about their clients: historical purchases, responses to marketing events, web search logs, etc. In today’s data-driven economy, data can assist enterprises to better understand their customers, and to take more informed decisions about the business.

The objective of the course is to introduce concepts in Business Intelligence and Data Analytics. During the course we will review several methods to extract and manipulate data, visualize data and make predictive decisions from data. We will also highlight potential pitfalls. Students will get hands-on experience using Python code.

• Group A: English
• Group B: French

You can attend either the English or the French section of this course.

Contents

The course is organized as a blended learning experience: each week, and before coming to class, students will have to watch a video detailing the theoretical content. Class time will be devoted to discussion, practical activities, and answering students' questions. The exploration of relevant techniques presented in the theory will be tested in the labs in which students will put the theory into code. At the end of each lab, each student will have to submit answers to an electronic quiz and feedback will be provided.

Students completing the course will understand concepts in:

• Data Cleaning
• Exploratory Data Analysis
• Data visualization
• Concepts from data mining and machine learning
• Regression
• Clustering
• Association rules
• Classification

Assignments and Examination:

Your performance in this course will be evaluated across three dimensions:

(a) Written Exam: Your understanding of the theory and your ability to solve problems related to it, which will be evaluated with an exam. In the exam, you are given a limited time to respond to a series of questions (e.g., multiple-choice questions, and others). The exam is designed as an open book examination. The exam will be timed competitively and will equally challenge your ability to reproduce, transfer, and apply the lecture’s contents.

(b) Coding Assignment: Your ability to code the concepts introduced in this course which will be evaluated through a programming assignment.

(c) Lab activity: Throughout the semester the student will apply the concepts of the theory in the lab and test it via short quizzes. Students will obtain feedback for the lab activity, ie the quizzes, but no score will be provided. At the end of the semester, all lab activity will be reviewed as one item and graded to compute the individual grade for the lab activity. Missing many weekly deliverables will negatively impact the grade given to the lab activity.

References

The lecture material will consist of slides given by the instructor.

Pre-requisites

You should have taken these courses:

• Eléments de programmation
• Modèles Informatiques

Term project

- Type of project : -
- Maximum number of projects admitted for this course : -
- Deadline for applying to course professor for project : -
- Deadline for submitting finished project : -
- Method of evaluation (including resit options) : -
- Other information : -

Evaluation

First attempt

Exam:

Written 2h hours

Documentation:

Allowed with restrictions

Calculator:

Allowed with restrictions

Evaluation:

The grade for this course is calculated as follows:

• Lab Activity: 15%
• Coding Assignment: 15%
• Digital Exam on Zoom: 70%

The exam consists of multiple choice and open questions. The exam is open-book.

Retake

Exam:

Written 2h hours

Documentation:

Allowed with restrictions

Calculator:

Allowed with restrictions

Evaluation:

The grade is calculated as:

Examen intégratif (Digital Exam on Zoom): 100%

The written exam consists of multiple choice and open questions. The exam is open-book.