What are the benefits of taking an online Statistics for Data Science course?

Online Statistics for Data Science courses offer a convenient and flexible way to enhance your knowledge or learn new Statistics for Data Science skills. Choose from a wide range of Statistics for Data Science courses offered by top universities and industry leaders tailored to various skill levels.

Top Statistics For Data Science Courses - Learn Statistics For Data Science Online

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Statistics For Data Science

Results for "statistics for data science"

Status: Free Trial
IBM
Statistics for Data Science with Python
Skills you'll gain: Descriptive Statistics, Statistical Analysis, Data Analysis, Probability Distribution, Statistics, Data Visualization, Statistical Methods, Statistical Hypothesis Testing, Regression Analysis, Probability & Statistics, Scientific Visualization, Data Science, Matplotlib, Exploratory Data Analysis, Probability, Correlation Analysis, Pandas (Python Package), Jupyter
4.5
Rating, 4.5 out of 5 stars
450 reviews
Mixed · Course · 1 - 3 Months
Status: Preview
Stanford University
Introduction to Statistics
Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution
4.6
Rating, 4.6 out of 5 stars
4.2K reviews
Beginner · Course · 1 - 3 Months
Status: New
Status: Preview
O.P. Jindal Global University
Statistical Methods and Data Analysis
Skills you'll gain: Sampling (Statistics), Statistical Analysis, Probability Distribution, Statistical Hypothesis Testing, Descriptive Statistics, Statistical Methods, Correlation Analysis, Regression Analysis, R (Software), R Programming, Statistical Modeling, Statistical Inference, Probability, Big Data, Decision Tree Learning
Build toward a degree
Mixed · Course · 1 - 3 Months
Status: Free Trial
DeepLearning.AI
Probability & Statistics for Machine Learning & Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization
4.6
Rating, 4.6 out of 5 stars
644 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
University of Michigan
Statistics with Python
Skills you'll gain: Sampling (Statistics), Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Data Visualization, Descriptive Statistics, Bayesian Statistics, Data Visualization Software, Jupyter, Histogram, Statistical Software, Probability & Statistics, Matplotlib, Statistical Analysis, Statistics, Data Analysis, Box Plots, Statistical Programming, Python Programming
4.6
Rating, 4.6 out of 5 stars
3.3K reviews
Beginner · Specialization · 1 - 3 Months
Status: Free Trial
Johns Hopkins University
Advanced Statistics for Data Science
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Science, Statistics, Probability Distribution, Mathematical Modeling, Data Analysis, Applied Mathematics, Predictive Modeling
4.4
Rating, 4.4 out of 5 stars
781 reviews
Advanced · Specialization · 3 - 6 Months

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Status: Free Trial
Google
The Power of Statistics
Skills you'll gain: Sampling (Statistics), Descriptive Statistics, Statistical Hypothesis Testing, Data Analysis, Probability Distribution, Statistics, Data Science, Statistical Analysis, A/B Testing, Statistical Methods, Probability, Statistical Inference, Statistical Programming, Python Programming, Technical Communication
4.8
Rating, 4.8 out of 5 stars
853 reviews
Advanced · Course · 1 - 3 Months
Coursera
Statistics For Data Science
Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistics, Statistical Analysis, Data Analysis, Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference
4.1
Rating, 4.1 out of 5 stars
38 reviews
Beginner · Guided Project · Less Than 2 Hours
Status: Free Trial
Johns Hopkins University
Data Science: Statistics and Machine Learning
Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Machine Learning Algorithms, Plotly, Interactive Data Visualization, Probability & Statistics, Data Presentation, Data Visualization, Feature Engineering, Statistical Analysis, Statistical Modeling, R Programming, Data Science, Machine Learning, GitHub
4.4
Rating, 4.4 out of 5 stars
7.2K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
IBM
Python for Data Science, AI & Development
Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis
4.6
Rating, 4.6 out of 5 stars
43K reviews
Beginner · Course · 1 - 3 Months
Status: New
Status: Free Trial
University of Colorado Boulder
Foundations of Probability and Statistics
Skills you'll gain: Probability, Probability & Statistics, Estimation, Probability Distribution, Markov Model, Bayesian Statistics, Statistical Methods, Statistical Inference, Sampling (Statistics), Statistical Analysis, Statistics, Artificial Intelligence, Generative AI, Data Analysis, Data Science, Descriptive Statistics, Machine Learning Algorithms, Mathematical Theory & Analysis
Build toward a degree
4.4
Rating, 4.4 out of 5 stars
320 reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
Status: AI skills
IBM
IBM Data Science
Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Dashboard, Data Visualization Software, Data Visualization, SQL, Unsupervised Learning, Plotly, Interactive Data Visualization, Peer Review, Supervised Learning, Data Transformation, Feature Engineering, Jupyter, Data Analysis, Data Cleansing, Data Literacy, Generative AI, Professional Networking, Data Import/Export
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
148K reviews
Beginner · Professional Certificate · 3 - 6 Months

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In summary, here are 10 of our most popular statistics for data science courses

Statistics for Data Science with Python: IBM
Introduction to Statistics: Stanford University
Statistical Methods and Data Analysis : O.P. Jindal Global University
Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
Statistics with Python: University of Michigan
Advanced Statistics for Data Science: Johns Hopkins University
The Power of Statistics: Google
Statistics For Data Science: Coursera
Data Science: Statistics and Machine Learning: Johns Hopkins University
Python for Data Science, AI & Development: IBM

Frequently Asked Questions about Statistics For Data Science

Statistics for data science refers to the mathematical analysis used to sort, analyze, interpret, and present data. It includes concepts like probability distribution, regression, and over or under-sampling. Descriptive statistics organizes data based on characteristics of the data set, such as normal distribution, central tendency, variability, and standard deviation. Inferential statistics incorporates the use of probability theory to infer characteristics of the data set.‎

Learning statistics for data science can lead to career opportunities in data science and related fields. As organizations increasingly rely on data to make decisions, they tend to seek out analysts who understand how to work with data and present it to stakeholders. Learning statistics for data science can also provide a good salary. As of 2020, the median pay for computer and information research scientists in the US is $122,840 and the job market remains positive, according to the Bureau of Labor Statistics. Mathematicians and statisticians have a similar job outlook and a median salary of $92,030 per year.‎

Data analysis, data architects, data scientists, and information officers typically use statistics for data science in their regular work. Data science is a broad field, and statistics can be useful in other roles that require analyzing and presenting data. This includes data warehouse analysts, data visualization developers, database managers, and machine learning engineers. Additional related fields include financial analysts, teachers, and researchers working for universities and corporate settings.‎

Through online courses, you can learn the fundamentals of statistics for data science, including the theories and techniques statisticians use in their work. Some courses explore fundamental concepts like Bayes’ Theorem and probability theory. Others present methods for calculating and evaluating data sets. You can brush up on your knowledge of programs statisticians use, like Excel and Python, or examine the application of statistics specific fields.‎

When looking to enhance your workforce's skills in Statistics for Data Science, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.