Are you searching for the best statistics courses to brush up on your skills? No worries. We have created a list for you that will cater to your needs.
While creating the list of best statistics courses, we have considered aspects like learners’ reviews, course offerings, extra features, the value of the course and its certificate, etc.
Statistics is an in-demand skill in today’s era. If you are aspiring to be a data analyst, data scientist, etc., Statistics is a must for you.
Moreover, you can consider the time span of the course you want. You can choose courses with degree certificates, choose specialization courses, or short-term courses.
What more are you waiting for? Go ahead and check the following list of the best statistics course that serves your needs.
List Of 11+ Best Statistics Courses: In a Nutshell
If you are in a hurry check out the gist of the courses listed.
|Statistics with R Specialisation||Coursera||Free|
|Statistics for Data Science and Business Analysis||Udemy||$99.99|
|Become a Probability & Statistics Master||Udemy||$199.99|
|Intro to Statistics||Udacity||Free|
|Mathematics for Machine Learning Specialization||Coursera||Free|
|Everyday Statistics, with Eddie Davila||Free|
|Statistical Thinking for Data Science and Analysis||EdX||Free|
|Statistical Learning||Stanford Online||Free|
|Data Analysis and Fundamental Statistics||FutureLearn||Free|
|MicroMasters program in Statistics and Data Science||Massachusetts Institute of Technology||$1,500|
|Statistics Foundations: Understanding Probability and Distributions||Plural Sight||Free|
1. Statistics with R Specialisation:
The course is offered by Duke University. The curriculum of the course consists of data with R, interferential statistics, modeling, linear regression, and probabilities.
From the specialization, you can complete all the courses or anyone as needed. At the end of the course, you will get familiar with topics like Rstudio, data analysis, R programming, statistics, and regression.
During the course, you will have to complete some quizzes and projects to get acquainted with the syllabus. After you successfully complete the course you will be able to analyze and visualize data and information.
- The course is a specialization course consisting of 3 basic courses.
- If you are a beginner or an intermediate the course is suitable for you.
- The deadlines are flexible.
- It is a self-paced course.
2. Statistics for Data Science and Business Analysis:
365 Careers Team offers this course. It is easy to understand, consists of practical knowledge, and is to the point.
In the course, the instructors cover the topics like R, Python, and data science basics. You will be introduced to statistical scientific lingo, data visualization, and pillars of quant research.
The course syllabus includes population, Central tendency, statistics and its fundamentals, understanding distributions, Estimates and estimators, variability and their measures, Inferential statistics, Calculating and working with confidence intervals, and hypothesis testing.
- The course is suitable for beginners and intermediates.
- The captions in the course are available in English and 15 other languages.
- A course made for learners aspiring to work as business intelligence analysts, marketing analysts, or data scientists.
3. Become a Probability & Statistics Master:
The course syllabus covers topics such as data analysis and visualization, independent and dependent probability, distribution of data, data sampling, hypothesis testing, regression, etc.
Instructor Krista King has done a great job in explaining the practical concepts of visualizing data and its analysis. You will also be able to work with discrete variables.
However, you must have a basic knowledge of simple equations and algebra, to begin with. In the course, learners are provided with quizzes, notes, and workbooks.
- The course consists of 10 sections and 141 lectures.
- Lifetime access as a statistics and probability master.
- At the completion of the course, you will receive a completion certificate.
- The course includes Q&A support.
4. Intro to Statistics:
The course covers topics such as probability, visualization, and regression. You will be able to learn the basics and understand the statistics.
You will be able to learn the foundation with the help of doing exercises and quizzes.
To begin with courses you should be familiar with the basics like mean, mode, and median of the numbers.
The course syllabus includes Visualization of data, probability, outliners, and normal, estimation, inference, and regression.
- The course is suitable for beginners.
- The course is taught by industry professionals.
5. Mathematics for Machine Learning Specialization:
The course is offered by Imperial College London. In the course, you will learn to implement mathematical concepts, and orthogonal projections, derive PCA from a projection perspective, and master PCA.
To complete the course you will have to go through the video lectures, complete the quizzes, and work on the hand on projects.
It is a specialization course consisting of 3 basic courses. You can either go through them all or choose the ones that you require.
The syllabus consists of topics like Linear Algebra, Multivariate Calculus, and Principal Component Analysis (PCA).
- The course helps you to work on making your mathematics foundation strong.
- The course is suitable for beginners.
- It has flexible deadlines.
- You will earn a completion certificate at the end of the course
- The course is a self-paced course.
6. Everyday Statistics, with Eddie Davila:
The course is instructed by Eddie Davila. She covers the fundamental concepts of statistics and its details.
If you want to learn the core of statistics, the course will surely fulfill your needs. The course curriculum includes statistics in everyday life and basic statistics concepts and modules.
At the end of each chapter, you will have access to the quiz to check the knowledge you have gained.
- The course is suitable for beginners and intermediates.
- You will receive a certificate of completion at the end of the course.
- Course access on tablets and mobile phones.
|Price||Free (1 month free Linkedin trial)|
7. Statistical Thinking for Data Science and Analysis:
The course is offered by Columbia University. It will help you to clear your concepts of data collection and analysis, what is linear regression, and its basics.
You will also get a gist of conditional probabilities and data visualization, in the course.
The course syllabus consists of an introduction to statistics and data science, the bayesian model, statistical thinking, linear regression, probability, statistics details, big data, visualization using graphs, etc.
- The course has flexible deadlines.
- It is self-paced.
- You will need to invest 7 to 10 hours per week in the course.
- Suitable for beginners and intermediates.
8. Statistical Learning:
The instructors of the course are Robert Tibshirani and Trevor Hastie from Stanford university.
The syllabus of the course includes linear regression, polynomial and logistic regression, linear discriminant analysis, bootstrap, cross-validation, regularization methods, model selection, nonlinear models, tree-based methods, splines, generalized additive models, support vector machines, and random forests and boosting.
The instructors make the complex formulas, easy to u understand. The lectures also include the R tutorials, and each session progresses with more detailed lectures.
The course covers the topics from Applications in R and An introduction to statistical learning.
- You will need to dedicate 3 to 5 hours per week to work on the exercises, materials, and study sections.
- This is a free online course with flexible deadlines.
- The instructors convert difficult topics into easily understandable concepts.
9. Data Analysis and Fundamental Statistics:
The course is suitable for enthusiasts who want to explore the fundamentals of data analysis, functions, and statistical models.
In the course, you will get a gist about data analysis and its fundamentals and excel formula syntax.
Moreover, the syllabus includes topics like data analysis, fundamental statistics, application of statistics and its techniques, and process for data drove decision-making and its tools.
- The course requires 4 hours/ week.
- The platform rewards you with a certificate of completion at the end of the course.
- The course fulfills the requirements of beginners and intermediates.
- You will be provided with flexible deadlines.
|Price||Free (7-day free trial on the platform)|
10. MicroMasters program in Statistics and Data Science:
The course is offered by the Massachusetts Institute of Technology. It is a micro-master degree course. The course is well-suited for graduate-level students.
You will have to stick to the course classes and attend them regularly as it does not have flexible deadlines.
You will have to earn credits in order to receive the degree. The course will help you with a deep understanding of the topics like data science, and machine learning, and in laying a strong foundation in statistics.
If you want to be job ready for the jobs like business analyst, data analyst, data scientist, etc. this course will surely help you out. It will provide you an edge over others’ profiles.
The syllabus of the course includes probability, data analysis, linear models, machine learning and deep learning, statistics, and its fundamentals.
- The course requires 10-14 hours per week.
- Instructor-led course.
- You will receive a degree certificate.
|Platform||Massachusetts Institute of Technology|
|Duration||1 year and two months|
11. Statistics Foundations: Understanding Probability and Distributions:
The instructor of the course is Dmitri Nesteruk. He is a developer, analyst, podcaster, and speaker.
The course covers Statistics foundations, probability, distributions, set theory, statistical research, probability density functions, discrete and continuous random variables, and moment generating functions. You will be using key distribution measures like mean and variance to explore the topics of covariance and correlation.
The course syllabus includes an introduction to the basic concepts of probability, Calculation of the conditional probability of events, an understanding of the concepts of random variables and distributions, an Introduction to the concept of expectations, and insights into some special statistical distributions.
- The course is for beginner-level learners.
- The course is led by experts.
- The instructor of the course simplifies the hard concepts into simple topics.
|Price||Free (10-day free trial)|
That’s all with the best statistics courses. In the list above we have provided you with all the available statistics courses that are worth learning. If you want to learn statistics you must surely check them out.
If you are still confused about which one to start with, here are our top picks.
- Statistics with R specialization
The course provides you an insight into statistics with R, regression, and modeling. The course is worth giving a try if you are interested to pursue your career in data analysis.
- Statistics for Data Science and Business Analysis:
This course offered by Udemy is a suitable option for learners aspiring to become data scientists or data analysts. The course includes data science with python and R.
Now that you have chosen a course to start with, I think you should share your choices with us in the comment section. I hope that the course will help you out in learning statistics and help you grow in your school or career.
Frequently Asked Question:
The best statistics course online is Statistics with R Specialisation. The course is offered by Duke university and is available on the Coursera platform.
Yes, you can study statistics online. There are many courses available on different platforms. You can choose either free or paid self-paced courses.
Coursera offers free and paid courses. You can select free courses from the variety of options available.
Yes, statistics offer a lot of great career options. You will surely land a high-paying job if you master statistics. Various jobs like data analyst, data scientist, etc. require statistics as basic skills.