Spécialisation Analyse et interprétation de données

Commence le avr. 03

Spécialisation Analyse et interprétation de données

Learn Data Science Fundamentals

Drive real world impact with a four-course introduction to data science.

À propos de cette Spécialisation

Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions. The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.

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courses
5 courses

Suivez l'ordre suggéré ou choisissez le vôtre.

projects
Projets

Conçu pour vous aider à vous exercer et à appliquer les compétences que vous avez acquises.

certificates
Certificats

Mettez en évidence vos nouvelles compétences sur votre CV ou sur LinkedIn.

Cours
Beginner Specialization.
No prior experience required.
  1. COURS 1

    Gestion de données et visualisation

    Session à venir : avr. 3 — mai 8.
    Engagement
    4 semaines d'étude, 4-5 heures/semaine
    Sous-titres
    English

    À propos du cours

    Que ce soit pour personnaliser la publicité destinée aux millions de visiteurs du site ou pour rationaliser les commandes d'inventaire d'un petit restaurant, les données font de plus en plus partie intégrante du succès. Trop souvent pourtant, nous ne sommes même pas sûrs de savoir comment les utiliser pour trouver les réponses aux questions qui nous rendront plus efficaces dans ce que nous entreprenons. Dans ce cours, vous découvrirez ainsi ce que sont des données et quelles sont les questions auxquelles les données peuvent répondre - même si vous n'avez jamais pensé aux données avant. Sur la base de données existantes, vous apprendrez à élaborer une question de recherche, décrire les variables et leurs relations, effectuer des statistiques de base et présenter vos résultats clairement. À la fin du cours, vous serez en mesure d'utiliser de puissants outils d'analyse de données - comme SAS ou Python - pour gérer et visualiser vos données, y compris la façon de traiter les données manquantes, les groupes variables et les graphiques. Tout au long du cours, vous partagerez vos progrès avec d'autres personnes pour obtenir un retour précieux, tout en apprenant comment vos pairs utilisent les données pour répondre à leurs propres questions.
  2. COURS 2

    Data Analysis Tools

    Session à venir : avr. 3 — mai 8.
    Sous-titres
    English

    À propos du cours

    In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.
  3. COURS 3

    Regression Modeling in Practice

    Session en cours : mars 24 — mai 1.
    Engagement
    4 weeks, 4 - 5 hours per week
    Sous-titres
    English

    À propos du cours

    This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results. You will learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression model. Throughout the course, you will share with others the regression models you have developed and the stories they tell you.
  4. COURS 4

    Machine Learning for Data Analysis

    Session à venir : avr. 3 — mai 8.
    Sous-titres
    English

    À propos du cours

    Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering. By completing this course, you will learn how to apply, test, and interpret machine learning algorithms as alternative methods for addressing your research questions.
  5. COURS 5

    Data Analysis and Interpretation Capstone

    Session à venir : mai 15 — juin 19.
    Sous-titres
    English

    À propos du Projet Final

    The Capstone project will allow you to continue to apply and refine the data analytic techniques learned from the previous courses in the Specialization to address an important issue in society. You will use real world data to complete a project with our industry and academic partners. For example, you can work with our industry partner, DRIVENDATA, to help them solve some of the world's biggest social challenges! DRIVENDATA at www.drivendata.org, is committed to bringing cutting-edge practices in data science and crowdsourcing to some of the world's biggest social challenges and the organizations taking them on. Or, you can work with our other industry partner, The Connection (www.theconnectioninc.org) to help them better understand recidivism risk for people on parole seeking substance use treatment. For more than 40 years, The Connection has been one of Connecticut’s leading private, nonprofit human service and community development agencies. Each month, thousands of people are assisted by The Connection’s diverse behavioral health, family support and community justice programs. The Connection’s Institute for Innovative Practice was created in 2010 to bridge the gap between researchers and practitioners in the behavioral health and criminal justice fields with the goal of developing maximally effective, evidence-based treatment programs. A major component of the Capstone project is for you to be able to choose the information from your analyses that best conveys results and implications, and to tell a compelling story with this information. By the end of the course, you will have a professional quality report of your findings that can be shown to colleagues and potential employers to demonstrate the skills you learned by completing the Specialization.

Créateurs

  • Université Wesleyenne

    Wesleyan University is dedicated to providing an education in the liberal arts that is characterized by boldness, rigor, and practical idealism.

    At Wesleyan, distinguished scholar-teachers work closely with students, taking advantage of fluidity among disciplines to explore the world with a variety of tools. The university seeks to build a diverse, energetic community of students, faculty, and staff who think critically and creatively and who value independence of mind and generosity of spirit.

  • Lisa Dierker

    Lisa Dierker

    Professor
  • Jen Rose

    Jen Rose

    Research Professor

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