Data Science Decisions in Time: Information Theory & Games
This is part of our specialization on Making Decision in Time. For this third course we start with an intriguing study on SFPark and build new insights into...
By Thomas Woolf on Coursera
About This Course
This is part of our specialization on Making Decision in Time. For this third course we start with an intriguing study on SFPark and build new insights into the ideas that flow from this direction. The ending point should bring new code and new algorithm insights into perspective, and use, by many computer and data scientists.
Topics Covered
Frequently Asked Questions
How much does Data Science Decisions in Time: Information Theory & Games cost?
Visit the Data Science Decisions in Time: Information Theory & Games course page for current pricing and available discounts.
Who teaches Data Science Decisions in Time: Information Theory & Games?
Data Science Decisions in Time: Information Theory & Games is taught by Thomas Woolf, Johns Hopkins University.
What skill level is Data Science Decisions in Time: Information Theory & Games for?
This course is designed for advanced learners.
Similar Courses
Minitab Applied Statistics & Hypothesis Testing Mastery
EDUCBA
Evaluate and Optimize Enterprise Log Analytics
EDUCBA
Linear Algebra from Elementary to Advanced
Johns Hopkins University
Data Science Fundamentals with Python and SQL
IBM