subject

Coursera: An Intuitive Introduction to Probability

 with  Karl Schmedders
This course will provide you with an intuitive and practical introduction into Probability Theory. You will be able to learn how to apply Probability Theory in different scenarios and you will earn a "toolbox" of methods to deal with uncertainty in your daily life.

The course is split in 5 modules. In each module you will first have an easy introduction into the topic, which will serve as a basis to further develop your knowledge about the topic and acquire the "tools" to deal with uncertainty. Additionally, you will have the opportunity to complete 5 exercise sessions to reflect about the content learned in each module and start applying your earned knowledge right away.

The topics covered are: "Probability", "Conditional Probability", "Applications", "Random Variables", and "Normal Distribution".

You will see how the modules are taught in a lively way, focusing on having an entertaining and useful learning experience! We are looking forward to see you online!

Syllabus

Probability
In this module we will learn about probabilities and perform our first calculations using probability formulas. We want to get comfortable with the idea that probabilities describe the chance of uncertain events occurring.

Conditional Probability
The arrival of new information may lead us to alter our probabilistic assessments of uncertain events. In this module, we will learn how the concept of "conditional" probabilities allows us to make these changes correctly.

Application
We will discuss some fascinating every-day applications of probability. In addition to entertaining examples, we will also review very serious applications from finance and law.

Discrete Random Variables
In this module we move beyond probabilities and learn about important summary measures such as expected values, variances, and standard deviations. We also learn about the most popular discrete probability distribution, the binomial distribution.

Normal Distribution
We want to get comfortable with the normal distribution. We will discuss what the famous bell curve really represents. And we will learn how easy it is to calculate normal probabilities.

2 Student
reviews
Cost Free Online Course (Audit)
Pace Upcoming
Institution University of Zurich
Provider Coursera
Language English
Certificates Paid Certificate Available
Calendar 5 weeks long
Sign up for free? Learn how
+ Add to My Courses
Learn Data Analysis udacity.com

Learn to become a Data Analyst. Job offer guaranteed or get a full refund.

Advertisement
Become a Data Scientist datacamp.com

Learn Python & R at your own pace. Start now for free!

Advertisement
FAQ View All
What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

2 reviews for Coursera's An Intuitive Introduction to Probability

Write a review
3 months ago
profile picture
Yueyun completed this course, spending 3 hours a week on it and found the course difficulty to be medium.
This is the first course related to Maths that I took so I am not really making a comparison. The course introduces me to a more complicated use of probability (beyond what I've been taught, i.e. high school maths). Generally, the professor explains the concepts really well. It is not difficult to follow his instructio Read More
This is the first course related to Maths that I took so I am not really making a comparison. The course introduces me to a more complicated use of probability (beyond what I've been taught, i.e. high school maths). Generally, the professor explains the concepts really well. It is not difficult to follow his instructions and understand his explanations. The fact that the professor demonstrates the real world applications of probability (there are many case studies) helps me appreciate the concepts that have been taught. And the final exercise at the end of each week (where I have to look at the data given and calculate the probability or some related concept) is also really helpful. However, sometimes, the professor doesn't spend enough time on certain concepts (in my case, Standard normal distribution) which makes it challenging to follow his instructions. And the in-video quizzes are predictable (because the right answer is usually at the same position in the multiple choice quiz). And I think it would really help me learn if there are more exercises for me to try out (and explanations if I get stuck: when I usually get the wrong answer, I either have to check whether my calculations are wrong or review the lecture videos again, which doesn't always help). Overall, it's a good course that covers various areas of probability. As an A-level student, I can say this course really helps me get ahead in my studies
Was this review helpful to you? YES | NO
4 months ago
Ashlynn Pai completed this course.
Was this review helpful to you? YES | NO

Write a review

How would you rate this course? *
How much of the course did you finish? *
Review
Create Review