### Top Statistics Certification Programs

A career in data science often requires more than just a passion for programming. It also requires an understanding of statistics. One of the best ways to build your foundation is through statistics certification programs. These statistic certification programs teach you statistical literacy and give you access to future job opportunities that require formal training in the field.

### Our Top 10 Picks

MicroMasters® Program in Statistics and Data Science
Best statistics certification for experts
Professional Certificate in Statistics, Confidence Intervals and Hypothesis Tests
Best for probability and statistics
Advanced Statistics for Data Science Specialization
Best advanced statistics courses
Professional Certificate in Statistical Analysis in R
Best statistics certification for learning R
Statistics Fundamentals with Python Skill Track
Best beginner statistics courses
Professional Certificate in Probability/Random Variables
Best introduction to probabilities
Building Statistical and Mathematical Models with R Learning Path
Best statistical modeling with R courses
Professional Certificate in Bayesian Statistics Using R
Best Bayesian statistics certification
Statistics with Python Skill Path
Best Python-based statistics courses
Statistics Fundamentals
Best for foundation statistics courses

## 1. MicroMasters® Program in Statistics and Data Science (MIT)

Get ready to make data-driven decisions that improve your business prospects. With the MicroMasters® Program in Statistics and Data Science, you will be able to use your skills to make predictions that matter. Learn about powerful methods to extract meaningful information from big data.

This online program provided by the Massachusetts Institute of Technology will teach you how to extract meaningful information from unstructured data, create efficient and accurate machine learning algorithms, and navigate through the various data analysis options available.

### Courses

1. Probability – The Science of Uncertainty and Data – Get a handle on the fundamentals of probability, so you can make informed decisions about your data. Learn everything you need to know about the basics of random processes and how to use inference from data. This course is designed for people who want to build their data science skills, and not just learn about statistics. It also covers Markov chains, the Central Limit Theorem, and Bernoulli (or Poisson) processes.
2. Fundamentals of Statistics – In this program, you will be able to make informed decisions about how to use statistics to answer questions. Learn how to use various statistical concepts such as dimension reduction with principal component analysis (PCA). It also covers topics like the goodness of fit, confidence intervals, and making predictions with linear models.
3. Machine Learning with Python: From Linear Models to Deep Learning – Learn how to design, train, and implement machine learning models using Python. Next, you will learn how to build linear models, deep learning models, and neural networks. This course is for anyone who wants to combine their skills in Python with machine learning.
4. Capstone Exam in Statistics and Data Science – Take this assessment to build your skills and knowledge in probability, data analysis, statistics, and machine learning. This culminating assessment will help you understand the principles behind these fields and solidify your skills.
5. Data Analysis Assessment – The final course you take in this program is a choice between two programs. First, you can use data analysis to answer questions of cultural, social, economic, and policy interest. Secondly, you can learn about the various computation tools and how to use them to make insights into real-world data.

### Skills Acquired

• Statistics
• Machine Learning
• Python
• Data Science
• Probabilistic Models
• Inference Methods
• Principal Component Analysis (PCA)
• Maximum Likelihood
• Hypothesis Testing
• Classification
• Regression
• Reinforcement Learning
• Kernel Machines
• Parameter Tuning
• Feature Engineering
• Data Analysis
• INFORMATION: This program contains 5 graduate-level courses over a duration of 1 year and 2 months.

## 2. Professional Certificate in Statistics, Confidence Intervals and Hypothesis Tests (Georgia Tech)

Gain the skills and confidence to tackle the most complex data analysis problems. The Professional Certificate in Statistics, Confidence Intervals and Hypothesis Tests is a 2-course program from Georgia Tech designed to prepare students for more advanced concepts.

First, you’ll receive a gentle introduction to statistics, including a walk-through of normal distributions and descriptive statistics. Finally, this program will teach you confidence intervals and hypothesis tests so you can test the validity and create probabilistic statements.

### Skills Acquired

• Statistics
• Confidence Intervals
• Hypothesis Tests
• Central Limit Theorem
• Descriptive Statistics
• Probabilities
• Goodness of Fit Tests
• Bernoulli Proportion
• Binomial Distributions
• Poisson Distribution
• Mean Squared Error
• Sampling Distributions
• Maximum Likelihood Estimation
• INFORMATION: This program consists of 2 skill-building courses and takes 2 months to complete.

## 3. Advanced Statistics for Data Science Specialization (Johns Hopkins University)

This is an advanced-level specialization from Johns Hopkins University that will take approximately 5 months to complete. During this 4-course specialization, you’ll learn everything from mathematical biostatistics to advanced linear models.

If you’re an aspiring data scientist, you’ll learn to use the tools from one of the world’s most prestigious universities. Overall, Advanced Statistics for Data Science Specialization will give you the skills you need to utilize statistical models and mathematical concepts to solve real-world problems in the field of data science.

### Skills Acquired

• Statistics
• Data Science
• Probabilities
• Linear Modeling
• Hypothesis Testing
• R Programming
• Confidence Intervals
• Biostatistics
• Least Squares
• Statistical Inference
• INFORMATION: This program consists of 4 advanced level courses and takes 5 months to complete.

## 4. Professional Certificate in Statistical Analysis in R (University of Canterbury)

Unlock your future with a degree that will prepare you for a career in the global workforce. The Professional Certificate in Statistical Analysis in R will equip you with the tools to analyze, predict and make decisions about data using R.

Gain a strong understanding of statistical inference and modeling by learning the basics including the Central Limit Theorem, exploratory analysis, and hypothesis testing.  Next, you’ll learn more advanced concepts including linear regression modeling and the basics of power analysis.

### Skills Acquired

• Statistical Inference
• Confidence Intervals
• Hypothesis Testing
• ANOVA
• P-Values
• Numerical Methods
• ANCOVA
• Mixed Effects Linear Models
• Sample Size Evaluation
• Experimental Design
• INFORMATION: This program consists of 2 skill-building courses and takes 3 months to complete.

## 5. Statistics Fundamentals with Python Skill Track (DataCamp)

Learn the fundamentals of statistics, and use them to explore real-world datasets. Whether you want to learn sampling, regression, or hypothesis testing, Python has the tools to help you and DataCamp can lead you on the right path to success.

The Statistics Fundamentals with Python Skill Track by DataCamp has a clear focus on learning by doing. Whether you want to be a statistician, data scientist, or just want to better understand statistics, this skill track will help you master the fundamentals of statistical programming with Python.

### Skills Acquired

• Statistics
• Regression + statsmodel
• Cluster Sampling
• Hypothesis Testing
• T-Tests
• Proportion Tests
• Chi-Square Tests
• Python
• INFORMATION: This program consists of 5 courses with 20 hours of course material.

## 6. Professional Certificate in Probability/Random Variables (Georgia Tech)

Gain a solid understanding of the concepts, methods, and applications of probability and random variables, and build a career in statistics. The Professional Certificate in Probability/Random Variables is a 2-course program from Georgia Tech.

You will learn discrete and continuous random variables, independence, correlation, and more – all while working with the R statistical package. By the end of this program, you will be able to understand and apply the principles of probability and random variables to a variety of different fields.

### Skills Acquired

• Permutations and Combinations
• Conditional Probability
• Bayes Theorem
• Continuous Random Variables
• R Statistical Package
• Probability
• Bell Curves
• Inverse Transform Theorem
• INFORMATION: This program consists of 2 skill-building courses and takes 2 months to complete.

## 7. Building Statistical and Mathematical Models with R Learning Path (Pluralsight)

Gain new skills and knowledge in statistical and mathematical models while learning advanced use of the R language. This course will teach you how to utilize many more statistical packages in R and how to implement these packages in real-world applications.

The Statistical and Mathematical Models with R Learning Path from Pluralsight will teach you dimensional analysis, Monte Carlo methods, and Mathematical MASS models using R. By the end of this program, you will gain a deeper understanding of statistical and mathematical models and their implementation in the R language.

### Skills Acquired

• Statistics
• R Language
• Dimension Analysis
• Linear Algebra
• Mathematical MASS Models
• Monte Carlo Method
• Statistical Summaries
• INFORMATION: This program consists of 9 courses with 21 hours of coursework.

## 8. Professional Certificate in Bayesian Statistics Using R (University of Canterbury)

Gain a competitive edge when applying for jobs in data analysis and statistical consulting. The 2-course Professional Certificate in Bayesian Statistics Using R from the University of Canterbury will teach you how to apply the Bayesian approach with practical examples.

First, you will use R and apply it to Bayesian statistics and answer real-life questions including ANOVA, simulations, cluster analysis, and more. Finally, you will learn more advanced Bayesian statistics concepts such as modeling latent variables and linear models.

### Skills Acquired

• Statistics
• Bayesian Inference
• Posterior Probabilities
• ANOVA
• Descriptive Statistics
• Markov chain-Monte Carlo (MCMC)
• Cluster Analysis
• Multivariate Analysis
• Metropolis-Hastings Algorithm
• Linear Regression
• INFORMATION: This program consists of 2 skill-building courses and takes 3 months to complete.

## 9. Statistics with Python Skill Path (Codecademy)

The Statistics with Python Skill Path from Codecademy is a hands-on, practical program where you will learn the basics of data analysis, exploratory data analysis, and hypothesis testing.

During this program, you’ll learn summary statistics, probability, hypothesis testing, and linear regression. Overall, you will gain a skill set that is in demand and can make a big difference in your career.

### Skills Acquired

• Statistics
• Experimental Design
• Python
• Probability
• Hypothesis Testing
• Summary Statistics
• matplotlib
• Linear Regression
• INFORMATION: This program consists of 9 courses and takes 4 weeks to complete.

## 10. Statistics Fundamentals (Dataquest)

Learn the basics of statistics with this introductory course. The Statistics Fundamentals course from Dataquest is designed to provide a solid foundation for understanding statistical principles and the application of these concepts in the solution of statistical problems.

Throughout the program, you’ll learn about sampling, variables, and distributions and be prepared to tackle statistics problems with confidence. At the end of this program, it will test you with a guided project where you investigate fan ratings using what you’ve learned in the course.

### Skills Acquired

• Statistics
• Simple Random Sampling
• Frequency Distribution Tables
• Cluster Sampling
• Stratified Sampling
• Scales of Measurement
• Statistical Variables
• INFORMATION: This program consists of 6 courses with 11 hours of coursework.