Introduction to Probability

About

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.

What you will 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

Skills you learn

• Prediction
• Economics
• Statistical Inference
• Finance
• Algorithms
• Engineering Economics
• Probability
• Statistics
• Forecasting
• Medical Testing
• Stochastic Process
• Data Science

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

Auto Summary

"Introduction to Probability" by edX offers essential tools to understand data, randomness, and uncertainty in IT & Computer Science. This 30-hour awareness-level course is available through Professional and Starter subscriptions, ideal for those looking to gain foundational knowledge in probability.