Data Science Decisions in Time: Using Data Effectively
Master sequential testing and decision-making in data science through practical applications in healthcare, business, and AI. Perfect for data professionals.
Master sequential testing and decision-making in data science through practical applications in healthcare, business, and AI. Perfect for data professionals.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science Decisions in Time Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
English
Not specified
Powered by
What you'll learn
Understand sequential testing and data collection optimization
Master Thompson sampling for A/B testing
Identify and analyze change points in data streams
Implement Markov chains for complex system modeling
Optimize decision processes using Markov Decision Processes
Skills you'll gain
This course includes:
1.8 Hours PreRecorded video
5 quizzes, 6 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 5 modules in this course
This course builds from fundamental mathematics and algorithms to advanced concepts in sequential decision-making. Students learn to program optimal decisions for data streams, define error metrics, and understand Markov Chains and Processes. The curriculum covers time-independent and time-dependent data analysis, connecting these concepts to reinforcement learning. Special focus is placed on practical applications in healthcare, business analytics, and manufacturing.
Wald and Sequential Decisions
Module 1 · 4 Hours to complete
Thompson Sampling
Module 2 · 4 Hours to complete
Change Points
Module 3 · 4 Hours to complete
Markov Chains
Module 4 · 4 Hours to complete
Markov Decision Processes
Module 5 · 7 Hours to complete
Fee Structure
Instructor
Distinguished Biophysicist and Computational Science Leader at Johns Hopkins
Dr. Thomas Woolf serves as a Professor at Johns Hopkins University School of Medicine since 1994, bringing expertise in biophysics and computational science. After earning his Ph.D. in Biophysics from Yale University and B.S. in Physics from Stanford University, he has established himself as a leader in membrane protein research and computational biophysics. His work combines high-performance computing, machine learning, and molecular dynamics to understand complex biological systems. As director of his research lab, he focuses on studying membrane proteins using advanced computational methods and the molecular dynamics program CHARMM. Beyond his academic work, Dr. Woolf is also CEO and co-founder of DaiWare, Inc., a healthcare company focusing on patient data interpretation using streaming data and machine learning technologies. He teaches courses in stochastic differential equations, probabilistic graphical models, and statistics, while conducting research in time-series analysis, cellular biophysics, and metabolic processes.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
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.