12 Best Courses on Statistics for Data Science to Master in Statistics in 2024

Are you looking for the Best Courses on Statistics for Data Science? If yes, then don’t worry! I have chosen the 12 best courses on Statistics for Data Science after filtering out hundreds of courses. So, give your few minutes to this article and find out the Best Courses on Statistics for Data Science.

Courses List-

Best Courses on Statistics for Data Science

To become a successful data scientist or data analyst, you should have a good understanding of Statistics. Knowledge of statistics will give you the ability to decide which algorithm is good for a certain problem.

Statistics knowledge includes statistical tests, distributions, and maximum likelihood estimators. All are essential in data science.

As a Data Scientist or Analyst, you have to find useful insights from the data, and for that statistics, knowledge is crucial for you. Now, you might be thinking, OK fine, Statistical knowledge is required but from where to learn?

So, if you are thinking the same, then don’t worry. I have chosen the 12 best courses on statistics for data science. These courses will give you in-depth knowledge of statistics.

I have filtered these courses on the following criteria-

Criteria-

1. Rating of these Courses.
2. Coverage of Topics.
3. Engaging trainer and Interesting lectures.
4. Number of Students Benefitted.
5. Good Reviews from various aggregators and forums.

So, without wasting your time, let’s start finding the Best Courses on Statistics for Data Science.

1. Statistics with R Specialization– Duke University

Rating- 4.6/5

Provider- Coursera

This specialization program will give you in-depth Statistics knowledge with the help of R. In this program, you will learn how to analyze and visualize data in R and create reproducible data analysis reports, and much more.

R is much better than Python for performing statistical operations. So, if you want to master Statistics, then I would recommend this specialization program. This specialization program contains 5 Courses. Let’s see the course details-

Courses Include-

1. Introduction to Probability and Data with R
2. Inferential Statistics
3. Linear Regression and Modeling
4. Bayesian Statistics
5. Statistics with R Capstone

Now, let’s see what statistic skills you will gain after completing this specialization program-

Skills Gain-

• Bayesian Statistics
• Linear Regression
• Statistical Inference
• R Programming
• Statistics
• Rstudio
• Exploratory Data Analysis
• Statistical Hypothesis Testing
• Regression Analysis
• Bayesian Linear Regression
• Bayesian Inference
• Model Selection

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Now, let’s see whether you should enroll in this specialization program or not?

You Should Enroll if-

• You have basic math knowledge. No previous programming knowledge is required for this course.

Time to Complete-

• This program will take approximately 7 months to complete

What’s the Price?

• 7 Day Full Access Free Trial and after that 49$/month.

Interested to Enroll?

If yes, then check out all details here- Statistics with R Specialization

2. Practical Statistics– Udacity

Rating- NA

Provider- Mode

As the name sounds, “Practical Statistics“, this course is focused on the practical implementation of statistical concepts. In this course, you will understand how to tackle common real-world challenges, such as analyzing AB tests and building regression models.

In this course, there is a project, where you have to use statistical techniques to answer questions about the data and report your conclusions and recommendations in a report. Dataset will be provided.

Topics covered in this course are- Simpson’s Paradox, Probability, Binomial Distribution, Conditional Probability, Bayes Rule, Standardizing, Sampling Distributions, and Central Limit Theorem, confidence intervals, Hypothesis Testing, T-Tests, and A/B Tests, Regression, multiple linear regression, and logistic regression.

Extra Benefits-

• You will chance to work on real-world projects with industry experts.
• You will get Project feedback from experienced reviewers.
• You will also get Technical mentor support.

Who Should Enroll?

• Those who have experience working with SQL and with data in Python.

Interested to Enroll?

If yes, then check out all details here- Practical Statistics

3. Statistics with Python Specialization– University of Michigan

Rating- 4.5/5

Provider- Coursera

This specialization program is especially dedicated to statistics. In this program, you will learn basic and intermediate concepts of statistical analysis using the Python programming language.

In this program, you will learn all important concepts like- where data come from, what types of data can be collected, study data design, data management, and how to effectively carry out data exploration and visualization.

Along with that, you will work on a variety of assignments that will help you to check your knowledge and ability. This specialization program is a 3-course series.

Now, let’s see what statistic skills you will gain after completing this specialization program-

Skills Gain-

• Python Programming
• Data Visualization (DataViz)
• Statistical Model
• Statistical inference methods
• Statistics
• Data Analysis
• Confidence Interval
• Statistical Inference
• Statistical Hypothesis Testing
• Bayesian Statistics
• Statistical regression

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Now, let’s see whether you should enroll in this specialization program or not?

You Should Enroll if-

• You have Knowledge of basic Python and High school-level algebra.

Time to Complete-

• Approximately, it would take 3 months to complete the entire specialization program( all 3 courses).

What’s the Price?

• 7 Day Full Access Free Trial and after that 49$/month.

Interested to Enroll?

If yes, then check out all details here- Statistics with Python Specialization

4. Statistician with R– Datacamp

Time to Complete- 108 hours

This is a Career Track offered by Datacamp. In this career track, there are 27 courses. This career track will help you to gain essential skills to land a job as a statistician. In this career track, you will learn basic to advanced level concepts of statistics.

At the beginning of the career track, you will learn how to collect, analyze, and draw accurate conclusions from data, concepts of random variables, distributions, and conditioning, using the example of coin flips, and how to fit simple linear and logistic regressions, how to fit model binomial data with logistic regression and count data with Poisson regression, etc.

Then you will learn Sampling, Hypothesis testing, basic experimental design, A/B testing, how to deal with missing data, survey design, survival analysis, Bayesian data analysis, Factor Analysis, and much more.

Now let’s see whether you should enroll in this Career track or not-

You Should Enroll if-

• If you have previous knowledge in R programming.

Interested to Enroll?

If yes, then check out all details here-Statistician with R

5. Intro to Statistics– Udacity

This is a completely FREE course for beginners and covers data visualization, probability, and many elementary statistics concepts like regression, hypothesis testing, and more.

In this course, you will also learn visualization and relationships in data, Probability with Bayes Rule and Correlation vs Causation, estimation with Maximum Likelihood, mean, median, and mode, statistical inference, and regression analysis.

You Should Enroll if-

• You are a beginner, but it’s good if you have already heard of some easy statistical concepts.

Interested to Enroll?

If yes, then start learning- Intro to Statistics

6. Data Science: Statistics and Machine Learning Specialization– Johns Hopkins University

Rating- 4.4/5

Provider- Coursera

This is another Specialization program dedicated to statistics concepts. In this program, you will learn statistical inference, regression models, machine learning, and the development of data products.

At the end of this program, you will work on Capstone Project, where you will apply the skills learned by building a data product using real-world data. This specialization program uses the R programming language.

There are 5 courses in this specialization program.

Now, let’s see what statistic skills you will gain after completing this specialization program-

Skills Gain-

• Machine Learning
• Github
• R Programming
• Regression Analysis
• Data Visualization (DataViz)
• Statistics
• Statistical Inference
• Statistical Hypothesis Testing
• Model Selection
• Generalized Linear Model
• Linear Regression
• Random Forest

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Now, let’s see whether you should enroll in this specialization program or not?

You Should Enroll if-

• You have completed the Data Science: Foundations using R Specialization specialization in order to gain the right foundation. Or you have a good understanding of R programming.

Time to Complete-

• This program will take approximately 5 months to complete

What’s the Price?

• 7 Day Full Access Free Trial and after that 49$/month.

Interested to Enroll?

If yes, then check out all details here- Data Science: Statistics and Machine Learning Specialization

7. Business Statistics and Analysis Specialization– Rice University

Rating- 4.8/5

Provider- Coursera

This specialization program will teach you Business Statistics and Analysis. In this program, you will learn basic probability concepts, including measuring and modeling uncertainty, and you’ll use various data distributions, along with the Linear Regression Model, to analyze and inform business decisions. 

This specialization program has 5 courses. 

Now, let’s see what statistic skills you will gain after completing this specialization program-

Skills Gain-

• Microsoft Excel
• Linear Regression
• Statistical Hypothesis Testing
• Lookup Table
• Data Analysis
• Pivot Table
• Statistics
• Statistical Analysis
• Normal Distribution
• Poisson Distribution
• Log–Log Plot
• Interaction (Statistics)

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Now, let’s see whether you should enroll in this specialization program or not?

Who Should Enroll?

• There is no condition for enrolling in this program. Anyone can enroll in this specialization program. No prior experience is required to enroll in this program.

Time to Complete-

• This program will take approximately 5 months to complete.

What’s the Price?

• 7 Day Full Access Free Trial and after that 49$/month.

Interested to Enroll?

If yes, then check out all details here- Business Statistics and Analysis Specialization

8. Statistics Fundamentals with R– Datacamp

Time to Complete- 20 hours

This is a Skill Track offered by Datacamp. In this skill track, there are 5 courses. In this skill track, you will learn how to answer questions like, “what is the likelihood of someone purchasing your product?”, “how many calls will your support team receive?“, etc by using sales data.

You will also learn the two most widely used statistical models, Linear regression and logistic regression. And how to perform linear and logistic regression with multiple explanatory variables. Then you will learn about Sampling and Hypothesis testing.

Now, let’s see whether you should enroll in this specialization program or not?

You Should Enroll if-

• You are comfortable in R programming.

Interested to Enroll?

If yes, then check out all details here- Statistics Fundamentals with R

9. Statistical Analysis with R for Public Health Specialization– Imperial College London

Rating- 4.7/5

Provider- Coursera

This specialization program is especially dedicated to the Statistical Analysis for Public Health. In this program, you will learn key statistical concepts like sampling, uncertainty, variation, missing values, and distributions.

Along with that, you will get your hands dirty with analyzing data sets covering some big public health challenges – fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalization – using R.

This specialization consists of 4 courses.

Now, let’s see what statistic skills you will gain after completing this specialization program-

Skills Gain-

• Statistical Thinking
• Survival Analysis
• Logistic Regression
• Data analysis with R
• Linear Regression
• Run basic analyses in R
• R Programming
• Understand common data distributions and types of variables
• Formulate a scientific hypothesis
• Correlation And Dependence
• Understand common ways to choose what predictors go into a regression model
• Run and interpret Kaplan-Meier curves in R

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Now, let’s see whether you should enroll in this specialization program or not?

Who Should Enroll?

• Anyone can enroll who has an interest in medicine and statistics. This is a Beginner Level program. No medical, statistical, or R knowledge is assumed.

Time to Complete-

• This program will take approximately 4 months to complete.

What’s the Price?

• 7 Day Full Access Free Trial and after that 49$/month.

Interested to Enroll?

If yes, then check out all details here- Statistical Analysis with R for Public Health Specialization

10. Basic Statistics– University of Amsterdam

Rating- 4.7/5

Provider- Coursera

In this course, you will learn the basics of statistics like what cases and variables are and how you can compute measures of central tendency (mean, median, and mode) and dispersion (standard deviation and variance).

Along with that, you will learn the basics of probability- calculating probabilities, probability distributions, and sampling distributions. You will also learn inferential statistics.

Now, let’s see the syllabus of the course-

Syllabus of the Course-

1. Introduction
2. Exploring Data
3. Correlation and Regression
4. Probability
5. Probability Distributions
6. Sampling Distributions
7. Confidence Intervals
8. Significance Tests

Now, let’s see what statistic skills you will gain after completing this course-

Skills Gain-

• Statistics
• Confidence Interval
• Statistical Hypothesis Testing
• R Programming

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Now, let’s see whether you should enroll in this course or not?

You Should Enroll if-

• You want to learn the basics of statistics at a beginner level.

Time to Complete-

• This course will take approximately 26 hours to complete

What’s the Price?

• 7-Day Full Access Free Trial and after that 39$/month.

Interested to Enroll?

If yes, then check out all details here- Basic Statistics

11. Statistics Fundamentals with Python– Datacamp

Time to complete- 19 hours

This is another skill track offered by Datacamp. This skill track is for those who want to learn statistics using Python. In this skill track, you will learn the foundation you need to think statistically using Python. Then you will learn how to perform the two key tasks in statistical inference, parameter estimation, and hypothesis testing.

In this career track, you will also learn about exploring, quantifying, and modeling linear relationships in data using Python. Then you will learn how to solve increasingly complex problems using simulations to generate and analyze data.

Now, let’s see whether you should enroll in this specialization program or not?

You Should Enroll if-

• You have previous knowledge of Python.

Interested to Enroll?

If yes, then check out all details here- Statistics Fundamentals with Python

12. Learn Statistics with Python– Codecademy

This course will teach you some different descriptive statistics including the mean, median, mode, standard deviation, and variance of different datasets. Along with that, you will learn how to calculate these statistics and how to interpret them. This course uses Python Programming language for coding.

Topics Covered in this Course-

1. Mean, Median, and Mode
2. Variance and Standard Deviation
3. Histograms
4. Describe a Histogram.
5. Quartiles, Quantiles, and Interquartile Range
6. Boxplots

Projects You will build in this Course–

• Variance in Weather
• Find the Best time to visit Acadia.
• Central Tendency for Housing Data

Who Should Enroll?

• There is no prerequisite. Anyone can enroll who wants to learn the basics of statistics.

Time to Complete-

• Approximately, it would take 15 hours to complete.

Interested to Enroll?

If yes, then check out all details here- Learn Statistics with Python

So, that’s all. These are the 12 Best Courses on Statistics for Data Science. Now, it’s time to wrap up.

Conclusion

I hope these courses will help you to learn statistics for data science. I aim to provide you with the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.

Tell me in the comment section, which is the Best Course on Statistics for Data Science?

All the Best!

Happy Learning!

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