Data Science: Capstone
- Certificate
Individual Course
Course Length
8 weeks
1-2 hours a week
Featuring faculty from:
Harvard T.H. Chan School of Public Health
Enroll as Individual
Certificate Price:
$ 149
On demand
Enroll on edXEnroll as Individual
Certificate Price:
$ 149
On demand
Enroll on edXIn this online course taught by Harvard Professor Rafael Irizarry, learn probability theory—essential for a data scientist—using a case study on the financial crisis of 2007-2008.
In this course,part of our Professional Certificate Program in Data Science, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007-2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.
We will introduce important concepts such as random variables, independence, Monte Carlo simulations, expected values, standard errors, and the Central Limit Theorem. These statistical concepts are fundamental to conducting statistical tests on data and understanding whether the data you are analyzing is likely occurring due to an experimental method or to chance.
Probability theory is the mathematical foundation of statistical inference which is indispensable for analyzing data affected by chance, and thus essential for data scientists.
Self-Guided
edX
Important concepts in probability theory including random variables and independence
How to perform a Monte Carlo simulation and the importance of the Central Limit Theorem
The meaning of expected values and standard errors and how to compute them in R
Program in this topic
These courses can be bundled together to receive a professional certificate at a discounted price.
See programYour Instructor
Professor of Biostatistics, Harvard T.H. Chan School of Public Health
Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute. For the past 15 years, Dr. Irizarry’s research has focused on the analysis of genomics data. During this time, he has also taught several classes, all related to applied statistics. Dr. Irizarry is one of the founders of the Bioconductor Project, an open source and open development software project for the analysis of genomic data. His publications related to these topics have been highly cited and his software implementations widely downloaded.
Read full bio.
Ways to take this course
A Verified Certificate costs $149 and provides unlimited access to full course materials, activities, tests, and forums. At the end of the course, learners who earn a passing grade can receive a certificate.
Alternatively, learners can Audit the course for free and have access to select course material, activities, tests, and forums. Please note that this track does not offer a certificate for learners who earn a passing grade.
No prerequisites are required. However, courses later in the series will assume you have the knowledge and skills acquired from earlier courses.
We suggest learners take the courses in the order in which they appear on the HarvardX Data Science Professional Certificate page.
Yes, to maximize flexibility learners can complete the courses across different runs of the course.
However each individual course must be completed within the same course run as progress on an individual course will not transfer between course runs.
Yes! You don’t need to be a data scientist to take these courses. The HarvardX Data Science Professional Certificate is designed for those who want to learn the fundamentals of data science and programming with R.
Courses in the HarvardX Data Science Professional certificate teaches learners the fundamental knowledge of data science, including essential data science skills such as data wrangling, programming with R, data visualization and other skills.
The HarvardX CS50 courses teaches learners the fundamentals of computer science including some commonly used programming languages such as C, Python, SQL, JavaScript plus CSS, and HTML.Learners in CS50 can explore computer science, mobile app and game development, business technologies, and the art of programming in other CS50 courses.
For more information on CS50 on edX visit the CS50 page.