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Pro & University Programs

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Statistics for Data Science & Analytics
40 coding exercises 3 projects
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MIT IDSS

12 weeks  • Online

Learn from MIT Faculty

Free Statistics Courses

img icon BASICS
Statistics for Data Science
star   4.58 70.2K+ learners 7.5 hrs

Skills: Probability,Population, Samples,Statistical analysis,Hypothesis testing,Statistical distributions

img icon BASICS
Statistical Analysis
star   4.5 18.8K+ learners 1 hr

Skills: Statistical Analysis, EDA

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Statistical Methods for Decision Making
star   4.44 64.5K+ learners 2 hrs

Skills: Descriptive statistics, probability theory, hypothesis testing, regression analysis, decision making methods

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Importance of Statistics in Machine Learning
star   4.46 1.6K+ learners 1 hr

Skills: Big Data, Statistics and Measures of Central Tendency

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Statistics for Machine Learning
star   4.58 43.4K+ learners 2 hrs

Skills: Descriptive Statistics, Measures of Dispersion Range and IQR,,Central Tendency and 3 Ms,The Empirical Rule and Chebyshev Rule,Correlation Analysis

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Inferential Statistics
star   4.56 4.8K+ learners 1 hr

Skills: Data Collection, Statistical Analysis, Probability, Central Limit Theorem, Hypothesis Testing, Chi-Square Test, ANOVA

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Introduction to Descriptive Statistics
star   4.46 10.2K+ learners 1 hr

Skills: Central Tendency, Measures of Variability, Measure of Skewness, Kurtosis

img icon BASICS
Statistics for Data Science
star   4.58 70.2K+ learners 7.5 hrs

Skills: Probability,Population, Samples,Statistical analysis,Hypothesis testing,Statistical distributions

img icon BASICS
Statistical Analysis
star   4.5 18.8K+ learners 1 hr

Skills: Statistical Analysis, EDA

img icon BASICS
Statistical Methods for Decision Making
star   4.44 64.5K+ learners 2 hrs

Skills: Descriptive statistics, probability theory, hypothesis testing, regression analysis, decision making methods

img icon BASICS
Importance of Statistics in Machine Learning
star   4.46 1.6K+ learners 1 hr

Skills: Big Data, Statistics and Measures of Central Tendency

img icon BASICS
Statistics for Machine Learning
star   4.58 43.4K+ learners 2 hrs

Skills: Descriptive Statistics, Measures of Dispersion Range and IQR,,Central Tendency and 3 Ms,The Empirical Rule and Chebyshev Rule,Correlation Analysis

img icon BASICS
Inferential Statistics
star   4.56 4.8K+ learners 1 hr

Skills: Data Collection, Statistical Analysis, Probability, Central Limit Theorem, Hypothesis Testing, Chi-Square Test, ANOVA

img icon BASICS
Introduction to Descriptive Statistics
star   4.46 10.2K+ learners 1 hr

Skills: Central Tendency, Measures of Variability, Measure of Skewness, Kurtosis

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Learner reviews of the Free Statistics Courses

Our learners share their experiences of our courses

4.52
71%
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Reviewer Profile

4.0

Country Flag India
“Simple to Understand and Easy to Resume After a Break”
The course "Statistics for Data Science" is designed to be straightforward and accessible, ensuring that concepts are easy to grasp. The material is structured in a way that allows learners to pick up where they left off, even after taking a break, without losing continuity. The course is tailored for both beginners and those with some background in statistics, making complex topics understandable through clear explanations and practical examples. Whether you're stepping away for a short time or diving back in after a longer pause, you'll find the content intuitive and easy to re-engage with, enabling a smooth and effective learning experience.

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5.0

Country Flag India
“Insightful and Practical Learning Experience”
I appreciated the well-structured content, which covered each topic in a logical sequence. The quizzes and assignments were valuable in reinforcing what I learned, and the practical approach helped me build real-world skills. The support from instructors and the interactive modules made the learning experience engaging. Overall, the course was a perfect balance of theory and practice.

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Reviewer Profile

5.0

“Engaging and Informative Learning Experience: Great Course with Practical Insights and Excellent Curriculum and Instructors”
The course provided a well-structured curriculum with in-depth explanations. The quizzes and assignments were engaging and helped reinforce learning. The instructor explained concepts clearly, making the learning process smooth and enjoyable.

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Reviewer Profile

5.0

Country Flag India
“Great Learning Free Course for CM”
I've been exploring the free courses on the Great Learning app, and I must say, it's been an incredible experience! The platform offers a wide range of topics, all curated with high-quality content. The courses are easy to follow, engaging, and well-structured, making learning enjoyable and efficient. I particularly appreciate the flexibility of learning at my own pace and the ability to revisit any lesson whenever needed. The practical exercises and real-world examples help solidify concepts in a meaningful way.

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Reviewer Profile

5.0

“I Had a Very Nice Experience with This Course”
Very nice course. The instructor is awesome and explains the topics very well.

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Reviewer Profile

5.0

Country Flag India
“Course Name: Statistics for Data Science”
What I like most about Statistics for Data Science is its practicality and power to turn raw data into actionable insights. Whether it's testing hypotheses, making predictions, or understanding relationships, statistics lays the groundwork for nearly every decision and model in data science.

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Reviewer Profile

5.0

Country Flag India
“A Nicely Structured Course for Statistics for Data Science”
I like the project assignment as well as the extensive quiz.

LinkedIn Profile

Reviewer Profile

5.0

Country Flag India
“Flow of Learning Was Really Good, and I Liked the Way of the Faculty Teaching in a Hybrid Model”
Everything was better than expected. I'm looking forward to doing more courses as well.

LinkedIn Profile

Reviewer Profile

5.0

Country Flag India
“An Engaging and Informative Course Experience”
I thoroughly enjoyed this course and found it to be highly informative and engaging. The curriculum was well-structured, covering a wide range of topics in depth. The instructors were knowledgeable and presented the material in a clear and concise manner. The quizzes and assignments were challenging yet fair, helping to reinforce the concepts learned. Overall, this course provided a comprehensive learning experience that was both enjoyable and educational.

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Reviewer Profile

5.0

“I learned about making boxplots using Seaborn and about discrete and continuous data. I am glad to know about prediction concepts for future thoughts.”
I am glad to be a part of this course. This increased my statistical concepts as much as I expected. I am very satisfied with this course.

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Learn Statistics For Free & Get Completion Certificates

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. It covers all data components, such as planning and data collecting, in terms of survey and experiment design.

 

Statistics can infer relationships between variables, test hypotheses, and make predictions. It is widely used in many fields, such as business, economics, finance, and medicine. 

 

The basic statistics concepts include probability and random variables, which define and measure the uncertainty associated with a given dataset. Probability theory describes the likelihood of specific outcomes and calculates the chances of future events. Random variables are used to describe the behavior of a system or process. 

 

Statistical methods are used to analyze data and draw conclusions from it. Several types of statistical analysis can be used, such as descriptive statistics, inferential statistics, and multivariate statistics. Descriptive statistics summarize and describe data, while inferential statistics are used to make conclusions about a data population based on a sample. Multivariate statistics are used to analyze several variables at once. 

 

Statistics also includes the use of software to analyze data. Commonly used statistical software packages, including SPSS, SAS, and R. These packages are used to analyze data and to create graphical representations of the data. They are also used to create predictive models and to perform hypothesis testing. It is an essential tool that can be used to help make decisions and to understand various aspects. It is used in a wide variety of fields to help make informed decisions.

 

Statistics for Machine Learning is an essential concept for individuals who want to gain a better understanding of the data that is being collected and used in modern machine learning algorithms. Statistics are a key component of machine learning and enable the development of more accurate and reliable models. Understanding the underlying concepts of statistics will help individuals better understand the data being used and the results being produced. 

 

The most important aspect of statistics for machine learning is the ability to identify meaningful patterns and relationships in the data. By understanding the principles of correlation and regression, individuals can look for significant relationships between the variables that are being studied. This is essential to understanding the data and the relationships between them, and it is also helpful in identifying potential areas of improvement in the data. 

 

Another important concept in statistics for machine learning is probability. Probability is an essential concept in understanding how the data is used and how it can be used to make predictions. By understanding the concept of probability, individuals can better understand the data and make better predictions. 

 

In addition to the concepts of correlation, regression, and probability, individuals should also be familiar with the concept of sampling. Sampling is an essential concept in understanding the accuracy of data. By sampling the data, individuals can better determine the accuracy of the data and make more informed decisions about the data.

 

There are several types of statistical methods used in Data Science. These include descriptive statistics, inferential statistics, predictive analytics, and machine learning. 

 

  • Descriptive statistics summarize and describe the data, such as the mean, median, and mode. These techniques can be used to identify patterns and trends in the data. 
  • Inferential statistics are used to make predictions/assumptions based on the data. This can include using the data to make assumptions about the population or to draw conclusions about the data.
  • Predictive analytics is used to create models that predict the outcomes of future events. This can include identifying factors that may influence an outcome, such as customer behavior or market trends. 

 

Some typical applications of statistics in Data Science include predictive analytics, market segmentation, forecasting, and optimization. Statistics can also identify potential risks and opportunities and make decisions based on the data.

 

This subject page will provide you with a comprehensive list of free online statistics courses available for you to explore. Statistics courses are a great way to learn more about the subject, from basic concepts to advanced topics. Whether you're a beginner or an experienced statistician, these free online courses can help you gain a better understanding of the subject.

 

You can further enhance your Data Science and Business Analytics skills through the Data Science certificate courses

Meet your faculty

Meet industry experts who will teach you relevant skills in artificial intelligence

instructor img

Dr. P K Viswanathan

Professor, Analytics & Operations
Dr. P K Viswanathan, currently serves as a professor of analytics at Great Lakes Institute of Management. He teaches subjects such as business statistics, operations research, business analytics, predictive analytics, ML analytics, spreadsheet modeling and others. In the industrial tenure spanning over 15 years, he has held senior management positions in Ballarpur Industries (BILT) of the Thapar Group and the JK Industries of the JK Organisation. Apart from executing corporate consultancy assignments, Dr. PK Viswanathan has also designed and conducted training programs for many leading organizations in India. He has degrees in MSc (Madras), MBA (FMS, Delhi), MS (Manitoba, Canada), PHD (Madras).   Noteworthy achievements: Ranked 12th in the "20 Most Prominent Analytics & Data Science Academicians In India: 2018". Current Academic Position: Professor of Analytics, Great Lakes Institute of Management. Prominent Credentials: He has authored a total of four books, three of which are on Business Statistics and one on Marketing Research published by the British Open University Business School, UK. Research Interest: Analytics, ML, AI. Patents: He has original research publications exclusively on analytics where he has developed modeling and demonstrated their decision support capabilities. These are: Modelling Credit Default in Microfinance — An Indian Case Study, PK Viswanathan, SK Shanthi, Modelling Asset Allocation and Liability Composition for Indian Banks. Teaching Experience: He has been teaching analytics for more than two decades but has been into active and intense teaching since analytics started witnessing a meteoric growth with the advent of R and Python. Ph.D. in the application of Operations Research from Madras University.
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Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning
  • 30+ years of experience in data science, ML, and analytics.
  • Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.

Frequently Asked Questions

What are the prerequisites required to learn these Statistics courses?

These courses include beginner-level Statistics introduction to give you foundational knowledge on required concepts. So, you need not do any homework before learning from these free courses. 
 

How long does it take to complete these Statistics courses?

These courses include 2-8 hours of video lectures. These courses are, however, self-paced, and you can complete them at your convenience. 
 

What knowledge and skills will I gain upon completing these free Statistics courses?

You will gain a foundational understanding of Statistics. You will be skillful in working with Data Science and Machine Learning tasks, including implementing statistical methods and deriving data-driven managerial decisions. You will realize the importance of statistics in various sectors and learn to apply it in the FinTech industry. 
 

Will I have lifetime access to these free Statistics courses with certificates?

Yes. You will have lifetime access to these courses after enrolling in them and access to certificates after completing the course.
 

Will I get a certificate after completing these free Statistics courses?

Yes. After completing them successfully, you will receive a certificate of completion for each course. 
 

How much do these Statistics courses cost?

These are free courses, and you can enroll in them and learn for free online. 

What are my next learning options after these Statistics courses?

These free Statistics courses give you a competitive edge in your professional life. You can register for the Applied Data Science course to escalate your learning in Data Science and Business Analytics domains. 

 

Is it worth learning Statistics?

Mastering statistics enables you to select the best techniques for data collection, apply the right analysis, and effectively communicate the findings. Making judgments based on data, making predictions, and making scientific discoveries depend on statistics. 

 

The important reasons to study statistics are to improve your ability to conduct research, read and analyze journal papers, behave as an informed consumer, and recognize when to employ outside statistical assistance.
 

Why is Statistics so popular?

Statistics provide you the ability to assess assertions supported by numerical data and assist you in differentiating between credible and doubtful findings. This feature is especially important now because individuals with various hidden motives offer so many data sources and interpretations.
 

What jobs demand you learn Statistics?

Jobs that are directly related to Statistics include,

  • Actuarial Analyst
  • Actuary
  • Civil Service Fast Streamer
  • Data Analyst
  • Data Scientist
  • Financial Risk Analyst
  • Investment Analyst
  • Market Researcher
  • Operational Researcher
  • Statistician
     

Why take Statistics courses from Great Learning Academy?

Great Learning Academy offers a wide range of high-quality, completely free Statistics courses. From beginner to advanced level, these free courses are designed to help you improve your Data Science and Business analytics skills and achieve your goals. All these courses come with a certificate of completion, so you can demonstrate your new skills to the world. Start learning today and discover the benefits of free Statistics courses!

Who are eligible to take these free Statistics courses?

These courses have no prerequisites. Anybody can learn from these courses for free online. 

What are the steps to enroll in these free Statistics courses?

To learn Statistics from these courses, you need to,

  1. Go to the course page
  2. Click on the "Enroll for Free" button
  3. Start learning the Statistics course for free online.