In this article, you will find the Best Statistics Courses on Udemy & advanced like Beginner courses, and Practice test courses. So, check these Best Statistics Courses on Udemy and find the Best Statistics Courses on Udemy for Beginners to Advanced according to your need. In the previous article, I have shared the best free Data Analysis courses for Beginners to advance that help you get practical skills with those courses.
Here we have covered the Best Statistics Courses on Udemy. Let’s go through the list of Udemy Statistics Courses one by one.
Best Statistics Courses on Udemy 2022
Statistics for Data Science and Business Analysis
In no time, you will acquire the fundamental skills that will enable you to understand complicated statistical analysis directly applicable to real-life situations.
It is no secret that a lot of these topics have been explained online. Thousands of times. However, it is next to impossible to find a structured program that gives you an understanding of why certain statistical tests are being used so often
Modern software packages and programming languages are automating most of these activities, but this course gives you something more valuable – critical thinking abilities. Computers and programming languages are like ships at sea. They are fine vessels that will carry you to the desired destination, but it is up to you, the aspiring data scientist or BI analyst, to navigate and point them in the right direction.
- Understand the fundamentals of statistics
- How to plot different types of data
- Understand the concepts needed for data science even with Python and R!
- Learn how to work with different types of data
- Calculate the measures of central tendency, asymmetry, and variability
- Distinguish and work with different types of distributions
- Understand the mechanics of regression analysis
Best for: Beginners | Course Duration: 5 hrs | Course Provider: Udemy
Total Articles: 28 | Downloadable Resources: 98
Visit this Course and get amazing offers on this course
Statistics for Business Analytics and Data Science A-Z
Rating: 4.6
If you are aiming for a career as a Data Scientist or Business Analyst then brushing up on your statistics skills is something you need to do.
But it’s just hard to get started… Learning / re-learning ALL of stats just seems like a daunting task. That’s exactly why I have created this course! Here you will quickly get the absolutely essential stats knowledge for a Data Scientist or Analyst.
This is not just another boring course on stats. This course is very practical.
I have specifically included real-world examples of business challenges to show you how you could apply this knowledge to boost YOUR career.
At the same time you will master topics such as distributions, the z-test, the Central Limit Theorem, hypothesis testing, confidence intervals, statistical significance and many more!
- Understand what a Normal Distribution is
- Explain the difference between continuous and discrete variables
- Understand the Central Limit Theorem
- Apply the Central Limit Theorem in practice
- Apply Hypothesis Testing for Means
- Apply Hypothesis Testing for Proportions
- Understand the difference between a normal distribution and a t-distribution
- Understand and apply statistical significance
Best for: Beginners | Course Duration: 6hrs | Course Provider: Udemy
Info: Visit this course and get amazing offers on this course
Become a Probability & Statistics Master
Rating: 4.7
This Probability and Statistics Master course includes video and text explanations of everything from Probability and Statistics, and it includes 45 quizzes (with solutions!) and an additional 8 workbooks with extra practice problems, to help you test your understanding along the way. Become a Probability & Statistics Master is organized into the following sections:
- Visualizing data, including bar graphs, pie charts, Venn diagrams, histograms, and dot plots
- Analyzing data, including mean, median, and mode, plus range and IQR and box-and-whisker plots
- Data distributions, including mean, variance, and standard deviation, and normal distributions and z-scores
- Probability, including union vs. intersection and independent and dependent events and Bayes’ theorem
- Discrete random variables, including binomial, Bernoulli, Poisson, and geometric random variables
- Sampling, including types of studies, bias, and sampling distribution of the sample mean or sample proportion, and confidence intervals
- Hypothesis testing, including inferential statistics, significance levels, type I and II errors, test statistics, and p-values
- Regression, including scatterplots, correlation coefficient, the residual, coefficient of determination, RMSE, and chi-square
Best for: Beginners | Course Duration: 14 hrs | Course Provider: Udemy
Total Articles: 79 | Downloadable Resources: 134
Info: Visit this course and get amazing offers on this course
Statistics for Data Analysis Using Excel 2016
Rating: 4.6
This course is about Statistics and Data Analysis. The course will teach you the basic concepts related to Statistics and Data Analysis, and help you in applying these concepts. Various examples and data sets are used to explain the application.
The following areas of statistics are covered:
Descriptive Statistics – Mean, Mode, Median, Quartile, Range, Inter Quartile Range, Standard Deviation
Data Visualization – 3 commonly used charts: Histogram, Box and Whisker Plot and Scatter Plot
Probability – Basic Concepts, Permutations, Combinations
Population and Sampling
Probability Distributions – Normal, Binomial and Poisson Distributions
Hypothesis Testing – One Sample and Two Samples – z Test, t-Test, p Test, F Test, Chi-Square Test
ANOVA – Perform Analysis of Variance (ANOVA) step by step by doing manual calculations and by MS Excel.
Best for: Beginners | Course Duration: 14.5 hrs | Course Provider: Udemy
Total Articles: 2 | Downloadable Resources: 53
Info: Visit this course and get amazing offers on this course
Master statistics & machine learning: intuition, math, code
Rating: 4.7
If you want to make yourself a future-proof employee, employer, data scientist, or researcher in any technical field — ranging from data scientist to engineering to research scientist to deep learning modeler — you’ll need to know statistics and machine-learning. And you’ll need to know how to implement concepts like probability theory and confidence intervals, k-means clustering and PCA, Spearman correlation and logistic regression, in computer languages like Python or MATLAB.
There are six reasons why you should take this course:
- This course covers everything you need to understand the fundamentals of statistics, machine learning, and data science, from bar plots to ANOVAs, regression to k-means, t-test to non-parametric permutation testing.
- After completing this course, you will be able to understand a wide range of statistical and machine-learning analyses, even specific advanced methods that aren’t taught here. That’s because you will learn the foundations upon which advanced methods are build.
- This course balances mathematical rigour with intuitive explanations and hands-on explorations in code.
- Enrolling in the course gives you access to the Q&A, in which I actively participate every day.
Best for: Beginners | Course Duration: 38.5 hrs | Course Provider: Udemy
Total Articles: 3 | Downloadable Resources: 4
Info: Visit this course and get amazing offers on this course
Statistics & Mathematics for Data Science & Data Analytics
Rating: 4.6
this course is equipping you with the practical knowledge needed to master the necessary statistics.
It is very important if you want to become a Data Scientist or a Data Analyst to have good knowledge of statistics & probability theory.
Sure, there is more to Data Science than only statistics. But still it plays an essential role to know these fundamentals ins statistics.
This course is giving you the chance to systematically master the core concepts in statistics & probability, descriptive statistics, hypothesis testing, regression analysis, analysis of variance and some advance regression / machine learning methods such as logistics regressions, polynomial regressions , decision trees and more.
In real-life examples you will learn the stats knowledge needed in a data scientist’s or data analyst’s career very quickly.
If you feel like this sounds good to you, then take this chance to improve your skills und advance career by enrolling in 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.
Best for: Beginners | Course Duration: 11.5 hrs | Course Provider: Udemy
Total Articles: 3 | Downloadable Resources: 5
Info: Visit this course and get amazing offers on this course
Statistics for Data Analysis Using Python
Rating: 4.7
The course not only explains, how to conduct statistical tests using Python but also explains in detail, how to perform these using a calculator (as if, it was the 1960s). This will help you in gaining the real intuition behind these tests.
Learn statistics, and apply these concepts in your workplace using Python.
The course will teach you the basic concepts related to Statistics and Data Analysis, and help you in applying these concepts. Various examples and data-sets are used to explain the application.
I will explain the basic theory first, and then I will show you how to use Python to perform these calculations.
The following areas of statistics are covered:
Descriptive Statistics – Mean, Mode, Median, Quartile, Range, Inter Quartile Range, Standard Deviation.
Data Visualization – Commonly used plots such as Histogram, Box and Whisker Plot and Scatter Plot, using the Matplotlib.pyplot and Seaborn libraries.
Probability – Basic Concepts, Permutations, Combinations
Population and Sampling – Basic concepts
Probability Distributions – Normal, Binomial and Poisson Distributions
Hypothesis Testing – One Sample and Two Samples – z Test, t-Test, F Test and Chi-Square Test
ANOVA – Perform Analysis of Variance (ANOVA) step by step doing the manual calculation and by using Python.
Best for: Beginners | Course Duration: 16 hrs | Course Provider: Udemy
Total Articles: 32 | Downloadable Resources: 24 | Coding Exercises: 23
Info: Visit this course and get amazing offers on this course
And here the list ends. So, these are the Best Statistics Courses on Udemy for Beginners to Advanced. I will keep adding more Best Statistics on Udemy to this list.
Conclusion
I hope these Best Statistics Courses on Udemy for Beginners to Advanced will definitely help you to enhance your skills. If you have any doubts or questions, feel free to ask me in the comment section.