• Duración:
    6 semanas
  • Dedicación:
    8–10 horas por semana
  • Precio:

    GRATIS
    Agregar un Certificado Verificado por $300 USD

  • Institución
  • Tema:
  • Nivel:
    Advanced
  • Idioma:
    English
  • Transcripción de video:
    English
  • Tipo de curso:
    Al ritmo del instructor

Programas asociados:

Prerrequisitos

You should be familiar with an undergraduate level, or have a background, in mathematics and statistics. Previous experience with a procedural programming language is beneficial (e.g. Python, C, Java, Visual Basic).

Learners pursuing the MicroMasters programme are strongly recommended to complete PA1.1x Introduction to Predictive Analytics using Python and PA1.2x Successfully Evaluating Predictive Modelling on the verified track prior to undertaking this course.

Sobre este curso

Omitir Sobre este curso

In this course, you will learn three predictive modelling techniques - linear and logistic regression, and naive Bayes - and their applications in real-world scenarios.

The first half of the course focuses on linear regression. This technique allows you to model a continuous outcome variable using both continuous and categorical predictors. This technique enables you to predict product sales based on several customer variables.

In the second half of the course, you will learn about logistic regression, which is the counterpart of linear regression, when the response variable is categorical. You will also be introduced to naive Bayes; a very intuitive, probabilistic modeling technique.

Lo que aprenderás

Omitir Lo que aprenderás

In this course, you will:

  • Discover how predictive models influence real-world business scenarios
  • Translate business challenges into predictive modeling solutions
  • Develop experience with implementing theoretic models in Python

Plan de estudios

Omitir Plan de estudios

Week 1: Simple Linear Regression
Week 2: Multiple Linear Regression
Week 3: Extensions and Applications
Week 4: Introduction to Naive Bayes
Week 5: Logistic Regression
Week 6: Estimation and Comparison

Conoce a tus instructores

Dr Galina Andreeva
Senior Lecturer in Management Science
The University of Edinburgh
Dr Matthias Bogaert
Assistant Professor in Data Analytics
Ghent University
Sofia Varypati
Course Tutor
University of Edinburgh

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Preguntas frecuentes

What type of activities will I complete on the course?
This course foregrounds self-directed and active ways of learning: reading, coding in Python, knowledge check quizzes and peer discussion. In addition, the course features videos that demonstrate relevant predictive analysis techniques and concepts.

What software will I be required to use?
All coding activities on this course will be hosted on Vocareum. You will be able to access this free software directly within the edX platform. There is no requirement to purchase further software in order to complete this course.

What do I need to complete the course?
For successful completion of this course, you will need access to a computer or mobile device and a reliable internet connection.

What is the University of Edinburgh Accessibility Guidance?

The University of Edinburgh is committed to providing online information and services accessible to all. Edx provide an accessibility statement which is available via the footer of all edx.org pages and includes an 'Accessibility Feedback' form which allows Learners to register feedback directly with the edx. Courses created by the University of Edinburgh contain an Accessibility Statement which addresses equality of access to information and servicesandis available via the 'Support' page.

¿Quién puede hacer este curso?

Lamentablemente, las personas de uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.