• Duración:
    15 semanas
  • Dedicación:
    10–15 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

Prerrequisitos

  • Undergraduate Python programming
  • Undergraduate multi-variable calculus, and linear algebra
  • Undergraduate probability theory and statistics
  • Undergraduate machine learning

Sobre este curso

Omitir Sobre este curso

If you have specific questions about this course, please contact us at sds-mm@mit.edu.

Data science requires multi-disciplinary skills ranging from mathematics, statistics, machine learning, problem solving to programming, visualization, and communication skills. In this course, learners will combine these foundational and practical skills with domain knowledge to ask and answer questions using real data.

This course will start with a review of common statistical and computational tools such as hypothesis testing, regression, and gradient descent methods. Then, learners will study common models and methods to analyze specific types of data in four different domain areas:

  • Epigenetic Codes and Data Visualization
  • Criminal Networks and Network Analysis
  • Prices, Economics and Time Series
  • Environmental Data and Spatial Statistics

Learners will be guided to analyze a real data set from each of these areas of focus, and present their findings in written reports. They will also discuss relevant and practical issues with peers.

This course is part of the MITx MicroMasters Program in Statistics and Data Science. It is at a similar pace and level of rigor as an on-campus course at MIT. Master the skills needed to be an informed and effective practitioner of data science. You will complete this course and three others from MITx and then take a virtually-proctored exam to earn your MicroMasters, an academic credential that will demonstrate your proficiency in data science or accelerate your path towards an MIT PhD or a Master's at other universities. To learn more about this program, please visit https://micromasters.mit.edu/ds/.

Lo que aprenderás

Omitir Lo que aprenderás
  • Model, form hypotheses, perform statistical analysis on real data
  • Use dimension reduction techniques such as principal component analysis to visualize high-dimensional data and apply this to genomics data
  • Analyze networks (e.g. social networks) and use centrality measures to describe the importance of nodes, and apply this to criminal networks
  • Model time series using moving average, autoregressive and other stationary models for forecasting with financial data
  • Use Gaussian processes to model environmental data and make predictions
  • Communicate analysis results effectively

Conoce a tus instructores

Stefanie Jegelka
X-Consortium Career Development Associate Professor
Massachusetts Institute of Technology
Caroline Uhler
Henry L. & Grace Doherty Associate Professor
Massachusetts Institute of Technology
Karene Chu
Lecturer and Research Scientist
Massachusetts Institute of Technology

Obtén un Certificado Verificado para destacar los conocimientos y las habilidades que adquieras
$300 USD

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¿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.