Statistics for Data Science | Probability and Statistics | Statistics Tutorial | Ph.D. (Stanford)



Author: Great Learning

???? Get the certificate of completion for the course, for Free: https://glacad.me/2MNrlYl ????
Looking for a career upgrade? We can help, choose from our programs for working professionals: https://glacad.me/3pDiXZm

More full courses from Dr Sarkar Ph.D. Stanford: https://www.youtube.com/watch?v=FPM6it4v8MY

Data Science is the hottest job of the 21st century with an average salary of 120k dollars per year.
Now, if you want to foray into the world of data science, you need to have good command over statistics, as it forms the base of all the data science concepts.

Visit Great Learning Academy, to get access to 80+ free courses with 1000+ hours of content on Data Science, Data Analytics, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity, and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. https://glacad.me/3duVMLE

Get the free Great Learning App for a seamless experience, enroll for free courses, and watch them offline by downloading them. https://glacad.me/3cSKlNl

So, keeping the importance of statistics in mind, we have come up with this comprehensive course by Dr.Abhinanda Sarkar.

This “Statistics for Data Science” Full course by Great Learning would help you to comprehensively learn all the basic and advanced topics in Statistics.

This course will be taught by Dr.Abhinanda Sarkar, Academic Director – Great Learning who has his Ph.D. in Statistics from Stanford University. He has taught applied mathematics at the Massachusetts Institute of Technology (MIT); been on the research staff at IBM; led Quality, Engineering Development, and Analytics functions at General Electric (GE); and has co-founded OmiX Labs.

These are the topics covered in this full course:
Introduction – 0:00
1. Statistics vs Machine Learning – 2:22
2. Types of Statistics [Descriptive, Prescriptive and Predictive] – 9:05
3. Types of Data – 1:50:45
4. Correlation – 2:46:02
5. Covariance – 2:52:33
6. Introduction to Probability – 4:26:55
7. Conditional Probability with Baye’s Theorem – 5:24:00
8. Binomial Distribution – 6:17:01
9. Poisson Distribution – 6:36:02
——————————————————————————————————————

Here are the links for our other full course videos:

Probability and Statistics Full Course: https://www.youtube.com/watch?v=z9siRCCElls

Machine Learning with Python: https://www.youtube.com/watch?v=RnFGwxJwx-0&t=287s

Hadoop Full Course: https://www.youtube.com/watch?v=JK2MdJAWEGc

Time series analysis: https://www.youtube.com/watch?v=FPM6it4v8MY&t=8209s

Tableau Training for Beginners: https://www.youtube.com/watch?v=6mBtTNggkUk&t=994s

Python for Data Science: https://www.youtube.com/watch?v=edvg4eHi_Mw&t=17669s

Artificial Intelligence Tutorial: https://www.youtube.com/watch?v=opgTF9Yf3Dk&t=729s .

Video source Youtube

Leave a Comment

19 + seventeen =