Professional Training

Introduction to Probability

edX, Online
Length
10 weeks
Next course start
Start anytime See details
Course delivery
Self-Paced Online
Length
10 weeks
Next course start
Start anytime See details
Course delivery
Self-Paced Online
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Course description

Introduction to Probability

Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you tools needed to understand data, science, philosophy, engineering, economics, and finance. You will learn not only how to solve challenging technical problems, but also how you can apply those solutions in everyday life.

With examples ranging from medical testing to sports prediction, you will gain a strong foundation for the study of statistical inference, stochastic processes, randomized algorithms, and other subjects where probability is needed.

Upcoming start dates

1 start date available

Start anytime

  • Self-Paced Online
  • Online
  • English

Suitability - Who should attend?

>Prerequisites

Familiarity with U.S. high school level algebra concepts; Single-variable calculus: familiarity with matrices. derivatives and integrals.

Not all units require Calculus, the underlying concepts can be learned concurrently with a Calculus course or on your own for self-directed learners.

Units 1-3 require no calculus or matrices; Units 4-6 require some calculus, no matrices; Unit 7 requires matrices, no calculus.

Previous probability or statistics background not required.

Outcome / Qualification etc.

What you'll learn

  • How to think about uncertainty and randomness
  • How to make good predictions
  • The story approach to understanding random variables
  • Common probability distributions used in statistics and data science
  • Methods for finding the expected value of a random quantity
  • How to use conditional probability to approach complicated problems

Training Course Content

Syllabus

  • Unit 0: Introduction, Course Orientation, and FAQ
  • Unit 1: Probability, Counting, and Story Proofs
  • Unit 2: Conditional Probability and Bayes' Rule
  • Unit 3: Discrete Random Variables
  • Unit 4: Continuous Random Variables
  • Unit 5: Averages, Law of Large Numbers, and Central Limit Theorem
  • Unit 6: Joint Distributions and Conditional Expectation
  • Unit 7: Markov Chains

Course delivery details

This course is offered through The Georgia Institute of Technology, a partner institute of EdX.

5-10 hours per week

Expenses

  • Verified Track -$139
  • Audit Track - Free
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