3.87 (149 reviews)
☑ Understand the fundamentals of statistics
☑ Understand the Stats concepts needed for data science using Python
☑ Distinguish and work with different types of distributions
☑ Calculate the measures of central tendency, asymmetry, and Skewness in Data
☑ Under-stand Hypothesis Testing & its use-cases too
☑ Get hands-on stats
☑ if you do have a math background, you’ll definitely enjoy this fun, hands-on method too.
If You want to be a Data Scientist or Data Analyst then brushing up on your statistics skills is something you need to do.
But it's just hard to get started with Data Science in most of the course you will find theoritical knowledge on stats not having practical knowledge
I have explained Each topic in a easiest way as well as its implementation in Python from Scratch (most demanding language of Data Science Industry)
That's exactly why I have created this course for you!
Here you will quickly get the essential stats knowledge for a Data Scientist or Analyst.
I have included real-world use-cases of business challenges to show you how you could apply Stats knowledge to boost your career.
At the same time you can master topics such as Descriptive Stats, distributions, z-test, the Central Limit Theorem, hypothesis testing, & many more!
So what are you waiting for?
Enroll now and & get a transition into Data Science
Why should you take this course?
This course is the one course you take in statistic that is equipping you with the actual knowledge you need in statistics if you work with data
This course is taught by an actual mathematician that is in the same time also working as a data scientist.
This course is balancing both: theory & practical real-life example.
After completing this course you ll have everything you need to master the fundamentals in statistics & probability need in data science or data analysis.
Intro to Stats
Why to Learn Statistics?
What Is Statistics?
Use of Statistics in Data Science
Intro to Python for Statistics
What is Python & need of Python in Data Science!
How Python works
Installation of Anaconda Navigator
Basics of Python (Python Module 1)
Variables in python & its use
Rules for Variable-Declaration in Python
What are Keywords in Python?
Data types In Python
Operators In Python
Indentation in Python
Conditional Statements in Python
Loops in Python (For loop)
Python Module 2 (Data Structures in Python)
List & various operations on list
List in Python
Set & its use-cases
Set in Python
Dictionary & its applications
Dictionary in Python
Python module 3
Intro to Pandas
Intro to Numpy
Intro to Seaborn
Statistics Module 1
Random Variable, Population and Sample Statistics
Types of Statistics
What are Outliers & Measures of Central Tendancy(Mean,Median,Mode) ?
Mean,Mode Median implementation using Python
Measures of Spread (Variance,Standard Dev. ,Range,Inter-Quantile Range)
Outliers Detection and Removal using Python
Skewness in Data
Statistics Module 2
Frequency Tables & Histogram
Frequency Tables & Histogram in Python
Types of Analysis
Types of Analysis in Python
Covariance and Co-relation
Co-relation using Python
Statistics Module 3
Intro to Probability
What is Prob. Density Function(PDF) & Cumalative Demnsity Function(CDF) ?
What is a Distribution and why we use it?
Binomial Dist. in Python
Poisson Distribution in Python
Normal Distribution in Python
Implementation of Z-score(Standarization) in python
Log-Normal Distribution and Heavy-Tailed Distribution
Log-Normal and Heavy Tailed Dist.. in Python
Central Limit Theorem
Central Limit Theorem implemntation in Python
Estimation Problem based on Z-stats
Statistics Module 4
1-tailed and 2-Tailed Test
Level of Significance
T-test and various types of T-test
T-test in Python
Topic and content doesnt matches well. Statistics for DataScience using Python and only 3-4 lectures where actually python used. All are theoritical and Python basics were too much basics and not helpful.
Excellent Course. The explanation of Statistics was way too good. I have subscribed to several similar courses, but this course exactly gave me a good understanding of Statistics and need for it in Datascience and EDA
No python explanation in Stats module 4 and even in some parts of stats module 3. Many topics not covered.
the teacher is BEYOND TERRIBLE !! if your looking for T tests, Leave now there is NO CODE HERE ...I wish I could rate him again..with a ZERO only 5 % is code , only 5 % is math , rest is him just talking generally ...not in depth
I found it interesting, informative and accurately paced. However,this course has so much potential to be excellent with few tweaks!
Excellent way of teaching also my confidence level is very high. I have learned so many skills from udemy but you are the best instructor.
This course is good for teaching how to perform statistics with Python and some useful libraries like pandas, numpy, and seaborn.
This course is Helpful in clearing all the doubts of Statistics.. Team solves my doubt Nice course .. please upload more courses on Data science
Python basics for Stats are damn good whereas Statistics is beautifully explained.. This course is better than Course-era Courses of 75K Beginners and intermediate guys will be lucky if they opt for it.. Not for those who just want over-view of Statistics .. Bcz if u really want to be Data scientist/Data analyst or any other role Statistics is a God
Loves the way in which instructor explains Python basics and Statistics in depth using real-life Use-cases..
Love the way of teaching Shan sir.. One of the best Data science Courses on Udemy I have ever seen..
Highly recommended to those..who really want to Learn Statistics behind Data science.. Feeling confident
I am going to rate it 5 star bcz I have seen YouTube videos on Statistics and even I have take Courses of 50K but still my concepts were not clear .. thanks to Shan sir who beautifully explained concepts as well its implementation in Python.