Online Statistics Courses & Certifications

The most important aspect of the business is Statistics. The Statistics for Business - II is designed by professionals which covers various topics and strategies of Business Statistics.

This course focuses on probability which is useful to follow a specified data distribution. Students represent real-life events using variables such as Normal, Binomial, and Poisson. They learn how to counterfeit data that is distributed using these variables. The duration of the course is 7 weeks which is divided into 2-4 hours per week. After the completion of the course, edX provides a certificate of completion. It is a self-paced course that lets the students study at their own comfortable pace. EdX brings this course in association with IIM Bangalore which is one of the most prestigious institutions in India. It is a bilingual course such that it teaches in both English and Hindi. It also provides video transcripts in both English and Hindi so that students won’t face any difficulty in following the lectures. 

Overall, this course nurtures the students and transform them into professionals in Business Statistics.  

Bayesian Statistics certification is a 7-week long programme where all the participants enrolling must devote approximately 34 hours of their time. This certification course is available on the Coursera platform but has been designed by Duke University. Also, this course is part 4 of 5 in the specialization of Statistics with R Specialization offering a free trial that is valid for 7 whole days. Whoever the interested participants must make sure that they have some kind of prior knowledge of what all is taught in the precious course parts of the specialization.

The Bayesian Statistics training will be responsible for introducing Bayesian comparisons related to means, credible regions, and Bayesian regression using multiple models to the participants. The course finally teaches all the applicants to learn the application of Bayesian methods to several practical issues and implementation in R programming. Apart from providing a certificate that is shareable, the candidates will be able to change the course timings with respect to their convenient schedules.

If you want to learn how to analyse medical data but do not know where to begin, the Introduction to Applied Biostatistics programme is for you. It provides an introduction to all the essential statistics and reasoning concepts used in medicine. The curriculum will introduce each topic using examples published in clinical research papers. You will work with real-life datasets in your homework assignments for practice in hands-on data analysis.

The Introduction to Applied Biostatistics certification syllabus covers basic epidemiological concepts, including study designs and sample size computation. Open-source software like R Commander and PS Sample Size, which are easy to download and install, are used in training.

The six-week Introduction to Applied Biostatistics training is an Osaka University (Japan) offering, aimed towards an intermediate-level. Learners can watch the video lectures at their own pace and follow English transcripts. The weekly effort required on their part is just three to five hours.

The students will be taught the rudimentary concepts and basic statistical theories along with the many applications of statistics in real life. Designed both for experienced professionals and students the techniques involved in evaluating theories, testing and ideas to unravel the truth will be covered in the Introductory Statistics: Analyzing Data Using Graphs and Statistics certification course.

The programme will teach the students the data and statistical concepts and hence allow the participants to analyze the given data with the help of graphs. The syllabus involves- histograms, standard deviation, correlation, and error for regression among many other topics.  The methods using “approximation” will also be covered by the students for solving the problems. The four-week Introductory Statistics: Analyzing Data Using Graphs and Statistics online course will thus help the participants to easily arrange data and also distribute the given numerical data into simplified methods. The self-paced course has two enrollment options; verified and audit. In the verified track, the leaners will be given unlimited access whereas, in the audit track, they will be provided with limited access to the programme. 

Inferential Statistics certification is a 5 weeks online course that belongs to the specialization of Statistics with R. This programme is course number 2 of 5 whose main focus is inferential statistics. The course belongs to a beginner level which only has a time requirement of 16 hours spread over the 5 weeks duration. Not only an end certificate is provided but also the study time can be reset at whatever time suits the candidates, 

Inferential Statistics training does help perform hypothesis testing, report the analysis of results by interpreting p-values, so that whatever is reported can be interpreted easily for the public or even the clients. Participants can learn to use the data examples that will help to report the estimates related to quantities that can express the uncertainty of interests. The participants can also learn the installation of R and RStudio software that is for the project in the final week of this course.

The Introduction to Statistical Hypothesis Testing certification course provides a comprehensive understanding of hypothesis testing, a critical aspect of data analysis. Through practical applications and theoretical foundations, students learn to evaluate postulates empirically, covering topics like null hypotheses, significance levels, and hypothesis tests for averages, variability, proportions, and regression analysis.

With the Introduction to Statistical Hypothesis Testing certification by NPTEL, learners delve into advanced concepts like constructing confidence regions and intervals. By mastering hypothesis testing techniques, students acquire the skills to make informed decisions and draw meaningful conclusions from empirical data, enhancing their analytical capabilities across diverse domains.

The Probability and Statistics III: A General Introduction to Statistics programme provides an amazing learning opportunity for all candidates who want to pursue careers in the field of statistics. The duration of the statistics and probability training programme is 4 weeks. Participants should spend 6-10 hours each week completing this certificate training programme. 

The Probability and Statistics III: A General Introduction to Statistics online course is in association with the institution of Georgia Tech. Learners will be able to learn about the concepts of Statistics and Data Analytics by studying in this course curriculum. Certification for this curriculum is available through the platform of Edx. Verified certification contains the achievement of the students, the name of the participants and the logo of the university. Students can avail of the certification for this training programme in probability and statistics by paying the course certification fee. Students can manage their schedules as this Probability and Statistics III: A General Introduction to Statistics certification syllabus is a self-paced learning programme. Probability and statistics training course is an intermediate learning course. After the course, the learners will get a certificate of completion if they take it in the verified track by paying the fee. In the audit mode, the students can have a limited period of access to the programme. 

The Probability and Statistics II: Random Variables – Great Expectations to Bell Curves program is an online and self-paced course where the candidates can feel free to take the course at any time through devices with a good internet connection. The basic knowledge required for the random variables is also offered as Probability and Statistics II: Random Variables –Great Expectations to Bell Curves certification syllabus and materials to the students who join this course.

This is an intermediate-level course that teaches them the concepts of continuous and discrete random variables. The topics include variance, joint random variables, expected value, bivariate random variables, univariate random variables; functions of random variables, and moment-generating function are covered in this course. 

The Probability and Statistics II: Random Variables –Great Expectations to Bell Curves certification consisting of the institution logo and the signature of the instructors from Georgia Tech is given to the candidates who complete the course. Learners who joined the course in the verified track will be given a shareable certificate which can be shared with platforms like LinkedIn and added to the resume to get more career opportunities. Those who choose to audit for free will be given only a limited duration of access. 

The Probability and Statistics IV: Confidence Intervals and Hypothesis tests certification course is supported by GTx and comprises the two most important methodologies used in Statistics: confidence intervals and hypothesis testing. This intermediate course is easy to learn and interesting.

By pursuing this probability and Statistics IV: Confidence Intervals and Hypothesis tests online course, candidates can solve basic probabilistic equations and can use them in their daily lives. Hypothesis testing allows them to either support, or oppose the proposed hypothesis and its validity, including the strength of the classroom, or test results of drugs. With these results, technical errors can be rectified by applying formulas. 

In this Probability and Statistics IV: Confidence Intervals and Hypothesis tests program, the candidates will probability distributions, design tests, interpret the hypothesis, and calculate confidence intervals for different probability parameters. An official certificate signed by the instructor with the institute’s logo will be issued after completion of the course. Applicants can add this certificate to their CV and submit it directly on platforms like LinkedIn, Upwork, and Fiver, for job applications. The learners can enrol in the programme either by paying the fee (verified) or free cost. In the free mode, the learners can access the programme for a limited period whereas in the paid mode, the learners will have unlimited access and a certificate of completion. 

The Introduction to Probability and Statistics online course is essentially an introductory or prerequisite course in probability and statistics. It is also an NPTEL online course comprising around 8-10 hours of content for learning, covered over four weeks of video lectures.

As such, the Introduction to Probability and Statistics certification course will prepare you to take on a more advanced study of probability and statistics. The course will begin by defining data and then slowly presenting the various ways of classifying data. Aspects of numerical and categorical data will be of primary focus.

Thus, around 10-12 core topics of both probability and statistics will be broadly covered in the Introduction to Probability and Statistics certification syllabus by the course instructor, Prof. G. Srinivasan of IIT Madras. He will instruct the course modules through live lectures.

Lastly, you will learn in detail about data and measuring associations. If you are a student or manager/executive, the Introduction to Probability and Statistics course by Swayam is an ideal fit for you.

In Non-Parametric Statistical Inference, as opposed to Parametric Statistical Inference, we do not know the underlying distribution. Parametric Inference also uses samples from the population to estimate the distribution parameters. However, the assumptions of Parametric Inference, such as normality, independence, and homoscedasticity may not always be accurate. 

In this case, non-parametric information is used. The Course in Non-Parametric Statistical Inference by Swayam will help the candidates to fill in the gaps of parametric statistics as non-parametric methods can be used for different inferencing purposes. The simple non-parametric techniques can help you to establish a hypothesis.  

The Non-Parametric Statistical Inference online programme has several practical applications in real life. This is an ongoing, undergraduate-level course that spans four weeks. The course will be taught by a faculty member from the esteemed Mathematics Department of IIT, Delhi. Moreover, this course is entirely free of cost, and the paid certificate is optional. 

The Statistics and R Online Course is centered around the basic principles of R programming language in connection with statistical concepts. The course will enable students to understand different statistical and visualization techniques. It will also help them understand the usage of the R programming language for analysing data and conducting research.

The Statistics and R Certification Syllabus are prepared under the guidance of genius minds including biologists from Harvard and from around the world who are dealing with genomic technology and scientific hypotheses. The course is instructed by Rafael Irizarry and Michael Love, Harvard University. The course would help students in achieving certification in data science with R programming.

The Statistics and R Training Course offered on the edX portal is a self-paced course taught over 4 weeks. The course will be delivered through online course materials and assessed through graded assignments and exams. After the successful completion of the course, learners will be rewarded with a shareable certificate if they have opted for the verified track. They can also join the programme free of cost and access the course materials for a limited duration. 

The Statistical Inference and Modeling for High-throughput Experiments Training Course is an open online course conducted in collaboration with the edX platform and Harvard University. The course deals with different techniques of statistical inference and their applications with regard to the handling of high-throughput data.

The Statistical Inference and Modeling for High-throughput Experiments Certification Course is taught over 4 weeks with the help of online study materials. The course is instructed by Rafael Irizarry and Michael Love, renowned professors at Harvard University. The online course is assessed through graded assignments and exams.

The Statistical Inference and Modeling for High-throughput Experiments Online Course is an intermediate-level course taught in a self-paced manner. The students who enrol in the course are required to have basic knowledge of programming, statistics and linear algebra. The students will receive professional certification after successful course completion if they join the course in the verified mode. For free, they can audit it for a limited duration. 

The Advanced Linear Models for Data Science 1: Least Squares course helps you develop a strong foundation of linear and regression modelling. Johns Hopkins University offers the programme, and your instructors will be subject-matter experts. It is the third part of the Advanced Statistics Specialisation by Coursera.  

Moreover, the course completion certificate that you will receive is shareable, after finishing the Advanced Linear Models for Data Science 1: Least Squares programme by Coursera. It will allow you to establish your relevant expertise in the field. Learn and develop fluency in the basics related to least squares and regression modelling, at your own pace.

In addition, the Advanced Linear Models for Data Science 1: Least Squares course features immersive content, developed around a self-paced model to align perfectly with your schedule. The training also provides adjustable deadlines. Furthermore, the online course allows you to quickly and efficiently start studying. You have to devote nearly 8 hours of learning time to the programme.

This certification course in Bayesian Statistics: Mixture Models by Coursera is a one stop place to learn the Bayesian Statistics and its Mixture Models along with its applications in the practical world. The course introduces one of the useful classes of statistics. This course is structured in a way to teach the most practical uses of Bayesian Statistics and its tools. It encourages candidates taking this course to practice and learn as the course progresses by not simply watching the videos but also constantly solving the Bayesian Statistics problems.

The course also utilises the industry software R in some places for solving the course problems. R is an easily available free statistical software that is used in m multiple industries of development, design and manufacturing, etc. The course lays out a basic tutorial to learn the software and teach the uses of it in Bayesian Statistics. Candidates are also encouraged to learn further about R for better advantages in their career.

The course is an intermediate level certificate course in Bayesian Statistics: Mixture Models taught by some of the expert faculty of the University of California Santa Cruz. For candidates who wish to take this course, it should be noted that prior knowledge of principles of estimation in maximum likelihood, Calculus based probability, and the Bayesian estimation is required. The course is a great way to take a step further in the statistics learning field and can provide you with the required edge in your career and the industry.

The Statistics for Data Science online course offers essential instruction on fundamental statistical concepts and techniques for effective data analysis. Participants will gain proficiency in data collection, summarization, visualisation, and interpretation utilising Python libraries. In addition, the Statistics for Data Science certification by PWskills covers a wide range of statistical tests and models to derive insights and make predictions from data.

This Statistics for Data Science certification course is thoughtfully designed to cater to beginners seeking to develop their skills in data science and statistical analysis. The course extends over 1 week. Offered through PW Skills, an esteemed online learning platform, the course is just one of the many valuable courses and certifications available across various domains, including data science, machine learning, artificial intelligence, cloud computing, and more.

Also read:

• Statistics Certification Courses
• Data Science With R And Python Certification Courses

The Statistics for Researchers Online Course available on the Edu Plus Now platform aims to educate learners about one of the most important aspects of research in academia and the role of statistical skills. The course attempts to impart knowledge to learners on the usage of statistics to perform domain research and resolution of arguments.

The Statistics for Researchers Training Course will be beneficial for learners who are participating in research activities. The course is delivered by experts at the Indian Statistical Institute, Pune, and aims to provide a clear idea of the relevance and role of statistics in research.

The Statistics for Researchers Certification Course is delivered via live interactive online sessions mediated by industry specialists and domain experts. With the help of extensive training sessions and simulated projects learners will be able to develop in-depth knowledge in various aspects of data science and build their careers.

The Fundamentals of Data Science and Statistics course will help you develop a foundation in the fundamentals of data science and statistics. The program will take you through multiple core concepts through a hands-on approach. The faculty for this training boasts over 20 years of teaching experience and has ample skills in the relevant field. 

Furthermore, the Fundamentals of Data Science and Statistics program takes you through probability concepts, hypothesis testing, and linear regression essentials. Additionally, the curriculum of the training emphasizes advanced linear regression. You will get to know about multiple regression, ANOVA table, serial correlation, and other related concepts.

This Fundamentals of Data Science and Statistics online course by E & ICT Academy (IIT Kanpur) houses assignments and a course-end assessment to help you acquire a course certificate. You will have the opportunity of attending live sessions with the course instructor. Moreover, there will be a total of five lectures only.

The Probabilistic Graphical Models 1: Representation course by Coursera is a part of the Probabilistic Graphical Models Specialization on the Coursera platform. Stanford University offers a certification course in association with Coursera.

The Probabilistic Graphical Models 1: Representation online course has a curriculum spread out over five weeks. The certification course will help you develop a deep understanding of the PGM framework by communicating perplex material with skill. Moreover, the online course primarily covers the fundamentals of Bayesian networks and Markov networks. 

Furthermore, the Probabilistic Graphical Models 1: Representation certification course promotes interaction and improvement with a comprehensive curriculum, intermittent assignments, and discussion boards. Candidates can self-assess using these mediums and grasp the course contents at their own pace. 

Finally, Coursera provides a certificate upon successful completion of the  Probabilistic Graphical Models 1: Representation course. The certificate can be added to the resume or shared on LinkedIn and other professional websites. Learners can also take a print out of the certificate.

Probabilistic Graphical Models (PGMs) is considered to be a strong foundation for encrypting probability arrangement over composite domains. Hence, Probabilistic Graphical Models 2: Inference is drafted to address the questions related to probabilistic inference. This course depends upon the concepts from graph algorithms, probability theory, and machine learning. These concepts are the base for the advanced methods used in various applications like speech recognition, medical diagnosis, natural language processing, etc. These advanced methods are also essential tools in composing various machine learning problems.

In an order of three, Probabilistic Graphical Models 2: Inference is the second one. While the first course, focused on description, this course would address the question occurs in probabilistic inference or in other words use of PGM in answering the questions. PGM is described as a very high dimensional diffusion but its framework is drafted in such a way that it can answer the questions efficiently. The course introduces both approximate and accurate algorithms for the variety of inference tasks, and also talks over the application of each algorithm.

Statistics and its various procedures form the backend of Data Science. It allows data science to understand, analyse, and predict real-time phenomena. If you’re fascinated by these and want to become fluent in statistical techniques, the Statistics Essentials for Analytics course by Edureka is an ideal training programme. It covers the basics of these techniques and explains how each one is used for a real-world data set to analyse and retrieve insights.

The Statistics Essentials for Analytics certification syllabus covers core topics like data clustering, data testing, probability, etc. It also includes real-life case studies and practical assignments for thorough evaluations. These will also help you acquire industry-relevant skills to become a fluent statistics professional. 

The Statistics Essentials for Analytics programme is completely online and self-paced. Moreover, you’ll receive lifetime access to the learning videos, the discussion forum, and the course's LMS (Learning Management System). Thus, you can revisit the topics anytime you want. Edureka also provides a valuable certificate and a resume builder tool to create a compelling CV to boost your portfolio.

The Advanced Predictive Modelling in R certification course has been curated to help you make better business decisions with the help of helpful data insights. It teaches the widely used techniques of predictive modelling as well as its core principles. Business organisations use these techniques throughout functional areas such as finance, human resource management, accounting, operations, and strategic planning. 

The Advanced Predictive Modelling in R course curriculum dives into logistic regression models, advanced regression, dimensionality reduction and more. You will also get to learn about the basics of Statistics that include Correlation and Linear Regression Analysis. Moreover, R programming offers a free and open-source environment perfect for learning and deploying predictive modelling solutions. 

Since the Advanced Predictive Modelling in R training will take place through online self-paced classes, you will learn through video lectures, PPTs, assignments and projects. Upon successful completion of the programme, you can earn Edureka’s certification to improve your professional prospects.

The Master Statistics with Python programme on Codecademy is a skill path curriculum. The course covers vital concepts about one of the most in-demand programming languages, Python. As such, you’ll develop a specialised skill in using Python for running hypothesis tests and summarising data. 

Besides, hand-picked content is provided in this training to help you fast-track your learning and complete the course in a few months. Codecademy offers a vast Master Statistics with Python certification syllabus. 

You will gain comprehensive knowledge on quantitative data stats, probability, visualising categorical data, and other related topics. Moreover, these skills will make you fluent in communicating data, testing your theories, and establishing a firm Python expertise. 

With Codecademy’s Pro plan, you can get extra benefits for the Master Statistics with Python course. You’ll become a part of the Pro members’ community, get unlimited programme access, work on real-world projects, and receive a step-by-step training roadmap. The Pro subscription also includes additional lessons on experimental design, SciPy, matplotlib, NumPy, and more.