Probability - The Science of Uncertainty and Data, Certificate | Part time online | edX - online learning platform | United States
4 months
Duration
300 USD/full
300 USD/full
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About

EdX is an online learning platform trusted by over 12 million users offering the Probability - The Science of Uncertainty and Data course in collaboration with Massachusetts Institute of Technology - MITx. Build foundational knowledge of data science with this introduction to probabilistic models, including random processes and the basic elements of statistical inference.

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Overview

The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Probabilistic modeling and the related field of statistical inference are the keys to analyzing data and making scientifically sound predictions.

Probabilistic models use the language of mathematics. But instead of relying on the traditional "theorem-proof" format, we develop the material in an intuitive -- but still rigorous and mathematically-precise -- manner. Furthermore, while the applications are multiple and evident, we emphasize the basic concepts and methodologies that are universally applicable. This course is part of a MicroMasters® Program.

The  Probability - The Science of Uncertainty and Data  certificate at Massachusetts Institute of Technology - MITx, part of the MITx MicroMasters Program in Statistics and Data Science covers all of the basic probability concepts, including:

  • multiple discrete or continuous random variables, expectations, and conditional distributions
  • laws of large numbers
  • the main tools of Bayesian inference methods
  • an introduction to random processes (Poisson processes and Markov chains)

What you'll learn:

  • The basic structure and elements of probabilistic models
  • Random variables, their distributions, means, and variances
  • Probabilistic calculations
  • Inference methods
  • Laws of large numbers and their applications
  • Random processes

Programme Structure

Syllabus

Unit 1: Probability models and axioms

  • Probability models and axioms
  • Mathematical background: Sets; sequences, limits, and series; (un)countable sets.

Unit 2: Conditioning and independence

  • Conditioning and Bayes' rule
  • Independence

Unit 3: Counting

  • Counting

Unit 4: Discrete random variables

  • Probability mass functions and expectations
  • Variance; Conditioning on an event; Multiple random variables
  • Conditioning on a random variable; Independence of random variables

Unit 5: Continuous random variables

  • Probability density functions
  • Conditioning on an event; Multiple random variables
  • Conditioning on a random variable; Independence; Bayes' rule

Unit 6: Further topics on random variables

  • Derived distributions
  • Sums of independent random variables; Covariance and correlation
  • Conditional expectation and variance revisited; Sum of a random number of independent random variables

Key information

Duration

  • Part-time
    • 4 months
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Prerequisites:

  • College-level calculus (single-variable & multivariable). Comfort with mathematical reasoning; and familiarity with sequences, limits, infinite series, the chain rule, and ordinary or multiple integrals.

Tuition Fee

To always see correct tuition fees
  • International

    300 USD/full
    Tuition Fee
    Based on the tuition of 300 USD for the full programme during 4 months.
  • National

    300 USD/full
    Tuition Fee
    Based on the tuition of 300 USD for the full programme during 4 months.
  • Add a Verified Certificate for $300 USD
  • Limited access:free

Funding

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