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Data Science: Probability Theory and Applications

This course is part of Data Science Professional Certificate.

This comprehensive course explores fundamental probability theory concepts essential for data scientists. Using the 2007-2008 financial crisis as a motivating example, students learn how probability theory impacts real-world risk assessment. The curriculum covers key topics including random variables, independence, Monte Carlo simulations, expected values, and the Central Limit Theorem. Through practical applications in R programming, participants develop skills in statistical inference and hypothesis testing. The course emphasizes understanding whether data patterns arise from experimental methods or chance, providing crucial insights for data analysis.

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Data Science: Probability Theory and Applications

This course includes

8 Weeks

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

12,292

Audit For Free

What you'll learn

  • Understand key probability concepts including random variables and independence

  • Perform Monte Carlo simulations for practical applications

  • Calculate expected values and standard errors using R

  • Apply the Central Limit Theorem in statistical analysis

  • Analyze real-world data using probability theory

Skills you'll gain

Probability Theory
Statistical Inference
Monte Carlo Simulation
Random Variables
Data Analysis
R Programming
Financial Risk Analysis
Central Limit Theorem

This course includes:

PreRecorded video

Graded assignments, exams

Access on Mobile, Tablet, Desktop

Limited Access access

Shareable certificate

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Module Description

This introductory course provides a solid foundation in probability theory for data science applications. Using the 2007-2008 financial crisis as a case study, students learn how probability concepts influence risk assessment and decision-making. The curriculum covers essential topics from random variables to the Central Limit Theorem, with hands-on practice using R programming. Through practical examples and simulations, participants develop skills in statistical inference and data analysis, crucial for understanding complex data patterns and making informed decisions.

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Science Professional Certificate

Instructor

Senior Lecturer in Public Leadership at Harvard Kennedy School

Ronald Heifetz is among the world's foremost authorities on the practice and teaching of leadership. He speaks extensively and advises heads of governments, businesses, and nonprofit organizations across the globe. In 2016, President Juan Manuel Santos of Colombia highlighted Heifetz's advice in his Nobel Peace Prize Lecture. Heifetz founded the Center for Public Leadership at Harvard Kennedy School where he has taught for nearly four decades. He is the King Hussein bin Talal Senior Lecturer in Public Leadership. Heifetz played a pioneering role in establishing leadership as an area of study and education in the United States and at Harvard. His research addresses two challenges: developing a conceptual foundation for the analysis and practice of leadership; and developing transformative methods for leadership education, training, and consultation. Heifetz co-developed the adaptive leadership framework with Riley Sinder and Marty Linsky to provide a basis for leadership research and practice. His first book, Leadership Without Easy Answers (1994), is a classic in the field and one of the ten most assigned course books at Harvard and Duke Universities. Heifetz co-authored the best-selling Leadership on the Line: Staying Alive through the Dangers of Change with Marty Linsky, which serves as one of the primary go-to books for practitioners across sectors (2002, revised 2017). He then co-authored the field book, The Practice of Adaptive Leadership: Tools and Tactics for Changing your Organization and the World with Alexander Grashow and Marty Linsky (2009). Heifetz began his focus on transformative methods of leadership education and development in 1983. Drawing students from throughout Harvard's graduate schools and neighboring universities, his courses on leadership are legendary; his core course is considered the most influential in their career by Kennedy School alumni. His teaching methods have been studied extensively in doctoral dissertations and in Leadership Can Be Taught by Sharon Daloz Parks (2005). A graduate of Columbia University, Harvard Medical School, and the Kennedy School, Heifetz is both a physician and cellist. He trained initially in surgery before deciding to devote himself to the study of leadership in public affairs, business, and nonprofits. Heifetz completed his medical training in psychiatry, which provided a foundation to develop more powerful teaching methods and gave him a distinct perspective on the conceptual tools of political psychology and organizational behavior. As a cellist, he was privileged to study with the great Russian virtuoso, Gregor Piatigorsky.

Data Science: Probability Theory and Applications

This course includes

8 Weeks

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

12,292

Audit For Free

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.