What is 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.

Why learn statistics for data science?

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.

What are typical careers that use statistics for data science?

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.

How can online courses help me learn statistics for data science?

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.

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.

What Statistics for Data Science courses are best for training and upskilling employees or the workforce?

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 .

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

Explore the Statistics for Data Science Course Catalog

DeepLearning.AI
Linear Algebra for Machine Learning and Data Science
Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Machine Learning Methods, Jupyter, Data Manipulation, Data Science, Applied Mathematics, Python Programming, Image Analysis, Artificial Intelligence
4.6
Rating, 4.6 out of 5 stars
2K reviews
Intermediate · Course · 1 - 4 Weeks
Google
Foundations: Data, Data, Everywhere
Skills you'll gain: Data Ethics, Data Analysis, Data-Driven Decision-Making, Google Sheets, Spreadsheet Software, Analytical Skills, Data Sharing, Data Cleansing, Data Processing, Data Visualization Software, SQL, Data Management
4.8
Rating, 4.8 out of 5 stars
114K reviews
Beginner · Course · 1 - 4 Weeks
University of Michigan
Introduction to Data Science in Python
Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles
4.5
Rating, 4.5 out of 5 stars
27K reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free
Coursera Instructor Network
Data Science for Professionals
Skills you'll gain: Predictive Modeling, Statistical Analysis, Data Manipulation, Data Analysis, Data Science, Pandas (Python Package), Data Visualization Software, Statistics, Data Cleansing, Data Processing, Data-Driven Decision-Making, Business Analytics, Exploratory Data Analysis, Machine Learning
4.5
Rating, 4.5 out of 5 stars
14 reviews
Beginner · Course · 1 - 4 Weeks
Macquarie University
Excel Fundamentals for Data Analysis
Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Manipulation, Spreadsheet Software, Data Transformation, Data Validation, Data Analysis, Pivot Tables And Charts, Automation
4.8
Rating, 4.8 out of 5 stars
4.1K reviews
Intermediate · Course · 1 - 3 Months
DeepLearning.AI
Calculus for Machine Learning and Data Science
Skills you'll gain: Applied Mathematics, Calculus, Numerical Analysis, Mathematical Modeling, Machine Learning, Python Programming, Regression Analysis, Artificial Neural Networks, Deep Learning, Derivatives
4.8
Rating, 4.8 out of 5 stars
840 reviews
Intermediate · Course · 1 - 4 Weeks
University of California, Davis
Data Visualization with Tableau
Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization Software, Key Performance Indicators (KPIs), Data Visualization, Dashboard, Interactive Data Visualization, Data Mapping, Tableau Software, Proposal Development, Graphing, Histogram, Scatter Plots, Tree Maps, Exploratory Data Analysis, Statistical Visualization, Storytelling, Performance Metric, Geospatial Mapping, Heat Maps
4.5
Rating, 4.5 out of 5 stars
8.2K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free
University of Cape Town
Understanding Clinical Research: Behind the Statistics
Skills you'll gain: Biostatistics, Statistical Hypothesis Testing, Statistical Methods, Probability & Statistics, Clinical Research, Statistical Analysis, Quantitative Research, Descriptive Statistics, Statistical Inference, Data Collection, Probability
4.8
Rating, 4.8 out of 5 stars
3.6K reviews
Beginner · Course · 1 - 3 Months
IBM
Exploratory Data Analysis for Machine Learning
Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Data Science, Probability & Statistics, Jupyter, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Artificial Intelligence
4.6
Rating, 4.6 out of 5 stars
2.2K reviews
Intermediate · Course · 1 - 3 Months
Macquarie University
Excel Skills for Business
Skills you'll gain: Microsoft Excel, Dashboard, Excel Formulas, Spreadsheet Software, Data Visualization, Excel Macros, Data Validation, Data Analysis Expressions (DAX), Data Cleansing, Data Modeling, Financial Forecasting, Predictive Modeling, Financial Modeling, Workflow Management, Finance, Data Management, Business Intelligence Software, Consolidation, Data Integrity, Data Entry
4.9
Rating, 4.9 out of 5 stars
62K reviews
Beginner · Specialization · 3 - 6 Months
IBM
Data Analysis and Visualization Foundations
Skills you'll gain: Data Storytelling, Big Data, Data Visualization Software, Data Analysis, Dashboard, IBM Cognos Analytics, Statistical Analysis, Data Mining, Apache Hadoop, Tree Maps, Excel Formulas, Data Wrangling, Apache Hive, Data Collection, Data Mart, Microsoft Excel, Data Warehousing, Data Quality, Data Cleansing, Data Import/Export
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
27K reviews
Beginner · Specialization · 3 - 6 Months
Johns Hopkins University
Python for Genomic Data Science
Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Scripting Languages, Scripting, Data Processing, Computer Programming, Data Manipulation, File Management
4.3
Rating, 4.3 out of 5 stars
1.8K reviews
Mixed · Course · 1 - 4 Weeks