Fondamentaux de la science des données from edX

Les données sont omniprésentes dans nos vies modernes, et leur quantité est faramineuse. Elles peuvent nous être très utiles dans tous les domaines de l’activité humaine comme la santé, le commerce et l’environnement, pour n’en nommer que quelques-uns. Mais comment tirer profit de ces données sans s’y perdre? Le cours Science des données présente les concepts essentiels permettant de collecter les données, de les traiter statistiquement, de les vérifier, de les visualiser, de les structurer et de les analyser. Nous allons décrire certains algorithmes d'apprentissage automatique, et leurs applications aux données.

Ce cours s'adresse principalement aux professionnels du secteur et aux universitaires ayant des connaissances de base en mathématiques et en programmation (idéalement Python). Les étudiants diplômés en sciences et en ingénierie (principalement ceux qui ne sont pas encore familiarisés avec la science des données) peuvent trouver ce contenu instructif et convaincant. Le contenu de ce cours sera également d’une grande utilité pour quiconque utilise ou s’intéresse à la science des données, de quelque manière que ce soit.

Nous estimons qu’il faut environ 8 semaines pour suivre ce cours. Celui-ci est divisé en segments pertinents que vous pouvez regarder à votre propre rythme. Des quiz récapitulatifs sont prévus à la fin de chaque segment pour évaluer votre compréhension du contenu. Vous pourrez également mettre la main à la pâte en réalisant des exercices pratiques qui vous permettront de vous familiariser avec les principaux savoir-faire issus de la science des données.

Ce cours a été développé par des experts du domaine du département d’informatique et de recherche opérationnelle (DIRO) de l’université de Montréal.

L’Université de Montréal rayonne depuis de nombreuses années par la qualité de son enseignement et la diversité de son offre, ce qui en fait une des meilleures universités francophones au monde. Que vous choisissiez ce cours à titre personnel ou dans une perspective de carrière en science, le point de départ est ici. La matière parcourue vous permettra de vous préparer avant de commencer un programme d’études en science des données ou toute autre étude liée à ce domaine.

Nous vous souhaitons la bienvenue dans ce cours en sciences des données, une des pierres angulaires de l'intelligence artificielle.

What's inside

Learning objectives

D’expliquer les concepts essentiels de la science des données
D’appliquer les méthodes mathématiques et statistiques utilisées en science des données

À la fin de ce cours, vous serez en mesure de :

D’expliquer les concepts essentiels de la science des données
D’appliquer les méthodes mathématiques et statistiques utilisées en science des données
À la fin de ce cours, vous serez en mesure de :

Syllabus

Module 1 – Introduction et vulgarisation

Introduction

Survol des principaux thèmes

Formation pratique 1 : Introduction à la syntaxe en Python

Module 2 – Méthodologie

Méthodologie

Formation pratique 2 : Manipulation, analyse et gestion de données

Module 3 – Les données structurées

Données structurées

Préparation et nettoyage

Formation pratique 3 : Visualisation de données

Module 4 – Probabilités et statistiques

Rappel des probabilités

Distributions

Probabilités et statistiques

Formation pratique 4 : Analyse et traitement d’un jeu de données

Module 5 – Inférence probabiliste

Probabilités conditionnelles

Réseaux bayésiens

Module 6 – Prédiction

Notions d’apprentissage automatique

Les techniques de prédiction

Formation pratique 6 : k-NN, sklearn et arbres de décision

Module 7 – Évaluation et sélection de modèles

Introduction Sur-apprentissage et sous-apprentissage

Évaluation du modèle

Méthodes d’ensemble

Conclusion

Formation pratique 7 : Régression, biais et variance

Module 8 – Partitionnement des données

Qu’est-ce que le partitionnement des données?

Les techniques

Indices de qualité de partitionnement

Formation pratique 8 : Partitionnement, K-moyennes, GMM, DBSCAN

Module 9 – Réduction de dimensionnalité

Qu’est-ce que la réduction de dimensionnalité?

Formation pratique 9 : Réduction de dimensionnalité

Projet intégrateur : Confidentialité différentielle

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Renforce les fondations existantes pour les apprenants intermédiaires

Développe des compétences professionnelles ou une expertise approfondie dans un sujet ou un ensemble de sujets particulier

Développé par des experts du domaine du département d'informatique et de recherche opérationnelle (DIRO) de l'université de Montréal

Dispensé par Alain Tapp et Mohamed Nabil Lokbani

Couvre les concepts essentiels en science des données

Offre des exercices pratiques pour se familiariser avec les techniques de pointe en science des données

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Fondamentaux de la science des données with these activities:

Read 'Data Science for Business'

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Gain a comprehensive understanding of data science concepts and their application in real-world business scenarios.

View Data science pour l'entreprise on Amazon

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Read and summarize key chapters of the book.
Apply the concepts to case studies and discuss with peers.

Review Probability Theory

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Solidify understanding of probability theory concepts to enhance comprehension of data analysis techniques covered in the course.

Browse courses on Probability

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Review textbooks or online resources on basic probability theory principles.
Solve practice problems covering conditional probability, Bayes' theorem, and random variables.

Join a Study Group

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Collaborate with peers to discuss course concepts, reinforce understanding, and challenge perspectives.

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Identify classmates with similar interests or schedules.
Establish regular meeting times and create a study plan.
Facilitate discussions, present findings, and engage in critical thinking exercises.

Five other activities

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Solve Data Analysis Exercises

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Strengthen data analysis abilities through regular problem-solving practice.

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Access online platforms or textbooks with data analysis exercises.
Dedicate time to solving problems and reviewing solutions thoroughly.

Explore Data Visualization Tools

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Enhance data visualization skills by exploring popular tools and techniques.

Browse courses on Data Visualization

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Enroll in online tutorials or workshops on data visualization.
Practice using Tableau or Power BI to create interactive visualizations.

Develop a Data Analysis Project

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Apply acquired knowledge and skills to a real-world data analysis project.

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Identify a problem or question that can be addressed through data analysis.
Collect and preprocess the necessary data.
Analyze the data using appropriate techniques.
Create visualizations and present findings in a clear and compelling manner.

Contribute to Open-Source Data Science Projects

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Gain practical experience and enhance knowledge by contributing to open-source projects in the field.

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Identify open-source projects related to data science on platforms like GitHub.
Review the project documentation and identify areas where you can contribute.
Submit bug reports, feature requests, or code contributions to the project.

Volunteer for a Data Analysis Organization

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Gain hands-on experience and make a meaningful contribution by volunteering with organizations focused on data analysis.

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Research and identify organizations that align with your interests in data analysis.
Contact the organizations to inquire about volunteer opportunities.
Participate in data collection, analysis, or visualization projects.

Career center

Learners who complete Fondamentaux de la science des données will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist is a person who uses scientific methods to extract knowledge and insights from data in various forms, both structured and unstructured. Data Scientists are responsible for preparing, cleaning, and transforming data, as well as building, training, and evaluating machine learning models. The Foundations of Data Science course provides a strong foundation in many of the skills that Data Scientists need to succeed, such as data collection, data analysis, data visualization, data mining, and machine learning.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts collect, analyze, and interpret data to help organizations make better decisions. They use a variety of statistical and programming tools to analyze data and identify trends and patterns. The Foundations of Data Science course provides a strong foundation in the data analysis skills that Data Analysts need to succeed, such as data collection, data cleaning, data visualization, and statistical analysis. This course can help you develop the skills you need to succeed in a career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians use mathematical and statistical techniques to collect, analyze, interpret, and present data. They work in a variety of fields, including healthcare, finance, and marketing. The Foundations of Data Science course provides a strong foundation in the mathematical and statistical methods that Statisticians use, such as probability, statistics, and linear regression. This course can help you develop the skills you need to succeed in a career as a Statistician.

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Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. They work with data scientists and other engineers to build and maintain machine learning systems. The Foundations of Data Science course provides a strong foundation in the machine learning concepts and algorithms that Machine Learning Engineers need to succeed, such as supervised learning, unsupervised learning, and deep learning. This course can help you develop the skills you need to succeed in a career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Engineer

Data Engineers design, build, and maintain data pipelines and systems. They work with data scientists and other engineers to ensure that data is available, reliable, and secure. The Foundations of Data Science course provides a strong foundation in the data engineering skills that Data Engineers need to succeed, such as data collection, data cleaning, data transformation, and data storage. This course can help you develop the skills you need to succeed in a career as a Data Engineer.

See salaries and explore the career path for Data Engineer

Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to solve complex business problems. They work in a variety of industries, including manufacturing, logistics, and healthcare. The Foundations of Data Science course provides a strong foundation in the mathematical and statistical methods that Operations Research Analysts use, such as optimization, simulation, and queuing theory. This course can help you develop the skills you need to succeed in a career as an Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. They work in a variety of financial institutions, including investment banks, hedge funds, and asset management companies. The Foundations of Data Science course provides a strong foundation in the mathematical and statistical methods that Quantitative Analysts use, such as probability, statistics, and linear regression. This course can help you develop the skills you need to succeed in a career as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Business Analyst

Business Analysts use data to help organizations make better decisions. They work with stakeholders to understand business needs and identify opportunities for improvement. The Foundations of Data Science course provides a strong foundation in the data analysis skills that Business Analysts need to succeed, such as data collection, data cleaning, data visualization, and statistical analysis. This course can help you develop the skills you need to succeed in a career as a Business Analyst.

See salaries and explore the career path for Business Analyst

Software Engineer

Software Engineers design, develop, and maintain software systems. They work in a variety of industries, including technology, finance, and healthcare. The Foundations of Data Science course provides a strong foundation in the computer science skills that Software Engineers need to succeed, such as programming, data structures, and algorithms. This course can help you develop the skills you need to succeed in a career as a Software Engineer.

See salaries and explore the career path for Software Engineer

Data Architect

Data Architects design, build, and maintain data architectures. They work with data engineers and other engineers to ensure that data is available, reliable, and secure. The Foundations of Data Science course provides a strong foundation in the data engineering skills that Data Architects need to succeed, such as data collection, data cleaning, data transformation, and data storage. This course can help you develop the skills you need to succeed in a career as a Data Architect.

See salaries and explore the career path for Data Architect

Systems Analyst

Systems Analysts design, implement, and maintain computer systems. They work in a variety of industries, including technology, finance, and healthcare. The Foundations of Data Science course provides a strong foundation in the computer science skills that Systems Analysts need to succeed, such as programming, data structures, and algorithms. This course can help you develop the skills you need to succeed in a career as a Systems Analyst.

See salaries and explore the career path for Systems Analyst

Database Administrator

Database Administrators design, build, and maintain databases. They work with data engineers and other engineers to ensure that data is available, reliable, and secure. The Foundations of Data Science course provides a strong foundation in the data engineering skills that Database Administrators need to succeed, such as data collection, data cleaning, data transformation, and data storage. This course can help you develop the skills you need to succeed in a career as a Database Administrator.

See salaries and explore the career path for Database Administrator

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. The Foundations of Data Science course provides a strong foundation in the mathematical and statistical methods that Actuaries use, such as probability, statistics, and financial mathematics. This course can help you develop the skills you need to succeed in a career as an Actuary.

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Technical Writer

Technical Writers create and maintain documentation for software, hardware, and other products. They work with engineers and other technical professionals to ensure that documentation is accurate, clear, and easy to understand. The Foundations of Data Science course provides a strong foundation in the communication skills that Technical Writers need to succeed, such as writing, editing, and technical writing. This course provides a foundation in the concepts of data science as well as provides hands-on experience with programming and data analysis tools.

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Consultant

Consultants provide advice and guidance to organizations on a variety of topics, including data science, technology, and business strategy. They work with clients to identify opportunities for improvement and develop solutions to complex problems. The Foundations of Data Science course provides a strong foundation in the data science skills that Consultants need to succeed, such as data analysis, data visualization, and machine learning. This course can help you develop the skills you need to succeed in a career as a Consultant.

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