Statistics & Probability Courses and Certifications

Statistics for Data Analysis Using Python

1536 ratings at Udemy

Learn Python from Basics • Descriptive, Inferential Statistics • Plots for Data Visualization • Data Science

• Udemy
• 15 hours 58 minutes
• Self-Paced
• Paid Course

American Psychological Association

Statistics in Psychological Research

66 ratings at Coursera

This is primarily aimed at first- and second-year undergraduates interested in psychology, statistics, data analysis, and research methods along with high school students and professionals with similar interests.

• Coursera
• 11 hours 47 minutes
• Self-Paced
• Paid Course

Applied Statistics for Data Analytics

63 ratings at Coursera

Gain insights into foundational statistics, from descriptive analysis to hypothesis testing, while mastering practical techniques for extracting meaningful insights from data through hands-on examples.

• Coursera
• 1 day 10 hours 46 minutes
• Self-Paced
• Paid Course

EDUCBA

Regression & Forecasting for Data Scientists using Python

43 ratings at Coursera

Master Python-based regression and forecasting techniques for data-driven decision-making across industries. Covers time-series analysis, ARIMA models, data preprocessing, and linear regression model creation.

• Coursera
• 13 hours 5 minutes
• Self-Paced
• Paid Course

Coursera

Statistics For Data Science

42 ratings at Coursera

This is a hands-on project to give you an overview of how to use statistics in data science.

• Coursera
• 1 hour 52 minutes
• Self-Paced
• Paid Course

Coursera

Basic Statistics in Python (Correlations and T-tests)

35 ratings at Coursera

Learn Python for basic statistics: data handling, exploratory analysis, correlations, t-tests. Analyze World Bank Science and Technology data using boxplots, scatter plots, and statistical methods.

• Coursera
• 2 hours 5 minutes
• Self-Paced
• Paid Course

IBM;  University of London

Statistics and Clustering in Python

22 ratings at Coursera

Master statistical analysis and data clustering using Python, from basic statistics to K-means algorithm implementation. Work with Pandas for data manipulation and complete hands-on clustering projects.

• Coursera
• 17 hours 51 minutes
• Self-Paced
• Paid Course

Multilevel Modeling

21 ratings at Coursera

Introduction to multilevel modeling theory and practice using R, focusing on two-level models with continuous response variables for analyzing hierarchical data in social sciences.

• Coursera
• 7 hours 56 minutes
• Self-Paced
• Paid Course

Statistics & Data Analytics For Data Science And Business

1101 ratings at Udemy

A Beginner's Guide To Statistics & Data Analytics For Data Science and Business Decisions (+Ebook & Templates)

• Udemy
• 2 hours 33 minutes
• Self-Paced
• Paid Course

JMP Training for Statistics & Data Visualization

1051 ratings at Udemy

Learn Statistics, Analytics & Data Visualization with JMP Statistical Software

• Udemy
• 3 hours 22 minutes
• Self-Paced
• Paid Course

Model Diagnostics and Remedial Measures

11 ratings at Coursera

Learn to diagnose and fix issues in regression models, including assumption violations, heteroscedasticity, autocorrelation, and multicollinearity. Gain skills in variable selection and model validation for data-driven industries.

• Coursera
• 19 hours 55 minutes
• Self-Paced
• Paid Course

Packt

Statistics & Mathematics for Data Science & Data Analytics

11 ratings at Coursera

Master essential statistical and mathematical concepts for data science, from descriptive statistics and probability theory to regression analysis and hypothesis testing, with practical applications for real-world data problems.

• Coursera
• 15 hours 7 minutes
• Self-Paced
• Paid Course

Statistics and Calculus Methods for Data Analysis

Master essential mathematical foundations for data science through statistics, calculus, and Python applications in expected values, derivatives, and integrals.

• Coursera
• 16 hours 5 minutes
• Self-Paced
• Paid Course

Statistics 101: Principles of Statistics

Learn fundamental statistical concepts, from data summarization to hypothesis testing, with expert-led lessons and interactive quizzes. Gain transferable skills applicable to various fields.

• Study.com
• 21 hours 44 minutes
• Self-Paced
• Paid Course

Ball State University

Statistical Methods for Data Science

Master statistical methods and probability theory for data science through hands-on applications in R, covering distributions, inference, multivariate analysis, and real-world problem-solving techniques.

• Coursera
• 1 day 15 hours 59 minutes
• Self-Paced
• Paid Course