Probability for Statistics and Data Science
Probability for improved business decisions: Introduction, Combinatorics, Bayesian Inference, Distributions
4.53 (1173 reviews)
14 011
students
3.5 hours
content
Feb 2024
last update
$74.99
regular price
What you will learn
Understand probability theory
Discover Combinatorics
Learn how to use and interpret Bayesian Notation
Different types of distributions variables can follow
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Our Verdict
This course offers an extensive introduction to probability theory, emphasizing applications in data science. Despite minor drawbacks such as underdeveloped practical exercises and scant explorations of advanced mathematical methods, its accessible language, engaging examples, and real-world context prove effective in building foundational knowledge. Boasting numerous updates since 2019, the course remains modernized with timely content for aspiring data scientists.
What We Liked
- Comprehensive coverage of probability theory, combinatorics, Bayesian inference, and distributions
- Accessible language and substantial working material catering to various learning styles
- Enhances understanding of vital data science concepts, such as normal distribution and z-value
- Well-paced visuals and audio supplemented with helpful real-life examples
Potential Drawbacks
- Quizzes are overly simple; lack advanced problem sets to solidify understanding of complex mathematical concepts
- Inadequate explanation of key differences between Bayesian and Frequentist inference approaches
- Limited discussion on practical applications for calculating PDFs, CDFs, and their significance within data science
- Concise presentations may result in some students feeling that terminology isn't thoroughly explained
Related Topics
2182258
udemy ID
28/01/2019
course created date
20/11/2019
course indexed date
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