Statistics for Data Science
A course from scratch providing a thorough grounding in essential statistical concepts, tailored specifically for aspiring data scientists. A blend of theoretical instruction with practical application, utilizing real-world data sets for hands-on learning.
Prabhakaran SPrincipal Data Scientist
Included in All-Access, one membership for every course.
- Lessons
- 29, in 3 chapters
- Video
- 2 h 49 min
- Certificate
- On completion
What you'll be able to do
- Fundamental Principles of Statistics
- Data Collection and Analysis Techniques
- Application of Descriptive and Inferential Statistics
- Hypothesis Testing and Regression Analysis
- Hands on reproducible Python Codes
- No prior knowledge of statisctics needed
Course content
3 chapters · 29 lessons · 2 h 49 min
01Introduction to Statistics2 lessons · 8 min
- Why learn Statistics?1:37
- Types of Data6:21
02Descriptive Statistics11 lessons · 1 h 2 min
- Measures of Central Tendency10:16
- Quantiles vs Percentiles vs Quartiles vs Deciles4:51
- Measures of Dispersion8:06
- Standard Error5:14
- Course Review1:00
- Population vs Sample7:40
- Why divide variance by n-1 - Part 19:49
- Why divide variance by n-2 - Part 22:29
- Law of Large Numbers3:30
- Law of Large numbers Exercise3:30
- Normal Distribution5:57
03Normal Distribution and More16 lessons · 1 h 41 min
- CDF of Normal Distribution10:33
- Probability Density Function (PDF) of Normal Distribution8:22
- Standard Normal Variate (z Score) and Standardization5:59
- Central Limit Theorem4:17
- Power Law and Pareto Distribution5:00
- Box Cox Transformation4:52
- Kernel Density Estimation4:55
- How distributions are used in the real world?5:32
- Bernooulli Distribution5:47
- Binomial Distribution10:08
- Exercise - Binomial Distribution9:54
- Exercise 2 - Binomial Distribution (Hard)6:54
- Difference between PDF vs PMF3:32
- Log Normal Distribution5:29
- Poisson Distribution using Example8:45
- Actively Updated1:00
What you need
- Basics of Python
- Foundational knowledge of Data Science
- High school maths
Who this course is for
- Data Science Aspirants
- Data Science Professionals
- Software/Data engineers interested in quantitative analysis
- Professionals working with large datasets
- Data analysts, economists, researchers
Your instructor
Prabhakaran S
Principal Data Scientist
My name is Selva, and I am super excited to mentor you on this course!
I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.
I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!
- from 3,965 ratings
- 4.92
- learners
- 57K+
- courses
- 85
Questions
How do I get this course?
It is part of All-Access: one membership that opens all 85 courses. The plans and prices are on our course site. You can watch the free preview lessons before you join.
Can I get a refund?
Yes. If the membership is not right for you, ask for a refund within 30 days of your first payment.
Can I learn on my phone?
Yes. Lessons play in the browser on any phone, tablet or computer, and your place is saved for the next device.
I am already a member. Where are my courses?
On our course site, edu.machinelearningplus.com. Sign in there with the email you joined with. The courses move to this site later, with your access, and you will not pay again.
