# All Classes and Courses

## Find the resources you need to learn about computational fields and further your understanding of Wolfram technologies.

Click any button to browse all catalog resources in a particular area or use the filters to refine your search. The catalog includes free, self-paced, interactive courses, standalone video lessons, video courses and scheduled instructor-led courses as well as archived and special events. Learn about the different course types.

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8 results

##### Introduction to Elementary Algebra
###### Interactive Course | FREE

Certification Levels: CompletionLevel 1

Elementary algebra is a prerequisite for multiple mathematics and statistics courses, and a strong foundation in algebra can help you better understand more advanced math. This course introduces the basic concepts of algebra as well as common types of problems and how to solve them. Start with algebraic definitions and then move on to linear equations, linear inequalities, polynomials and quadratic equations. The instructor also discusses word problem examples in each section and walks through the steps to finding a solution.

###### Course Overview
• Section 179 minutes
• Section 289 minutes
• Section 379 minutes
• Section 466 minutes
• Section 565 minutes
• Section 679 minutes
• Section 715 minutes
##### Introduction to Probability
###### Interactive Course | FREE

Requirements: This course requires basic working knowledge of Mathematica or Wolfram Language. Prerequisites for probability include Algebra I (elementary algebra) and Algebra II (intermediate algebra).

Certification Levels: CompletionLevel 1

Probability is the branch of mathematics that deals with random phenomena. Using real-world examples, this comprehensive introduction to probability and statistics can help prepare you for coursework and research in natural science, engineering, finance, medicine, data science and other fields. The course starts with a discussion of basic probability concepts, followed by the study of random variables as well as common probability distributions and their applications. These topics are typically found in basic probability courses and serve as great preparation for statistics, data science and the professional examination Exam P from the Society of Actuaries.

###### Course Overview
• Section 151 minutes
• Section 239 minutes
• Section 332 minutes
• Section 434 minutes
• Section 527 minutes
• Section 626 minutes
##### Introduction to Statistics
###### Interactive Course | FREE

Requirements: This course requires basic working knowledge of Mathematica or Wolfram Language. Prerequisites for statistics include Algebra I (elementary algebra) and Algebra II (intermediate algebra).

Certification Levels: CompletionLevel 1

Statistics is the branch of mathematics concerned with collecting, describing, analyzing and interpreting data and trends in science, industry and society. This course introduces techniques for data visualization and descriptive statistics, methods for calculating confidence intervals and tools for hypothesis testing. Practical examples are used to demonstrate the application of statistical methods. The topics in this course are typically found in entry-level college statistics courses and serve as great preparation for the AP Statistics exam.

###### Course Overview
• Section 112 minutes
• Section 210 minutes
• Section 311 minutes
• Section 410 minutes
• Section 512 minutes
• Section 617 minutes
• Section 77 minutes
• Section 812 minutes
• Section 99 minutes
• Section 1012 minutes
• Section 1117 minutes
• Section 1215 minutes
• Section 1318 minutes
• Section 1410 minutes
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Hypothesis Testing

##### Hypothesis Testing
###### Video Lesson | FREE

The Wolfram Language includes a framework for hypothesis testing. This class explores parametric and nonparametric tests of location, variance or scale, as well as distributional goodness of fit. This class assumes basic familiarity with the Wolfram Language and statistics concepts.

Model Fitting and Analysis

##### Model Fitting and Analysis
###### Video Lesson | FREE

This class explores the built-in Wolfram Language framework for linear and nonlinear regression, logit, probit and generalized linear models, as well as optimization functions, linear algebra functions and a package for analysis of variance (ANOVA). The class assumes basic familiarity with the Wolfram Language and statistics concepts.

Modeling with Statistical Distributions

##### Modeling with Statistical Distributions
###### Video Lesson | FREE

The Wolfram Language has the largest collection of parametric and nonparametric distributions, supporting high-level functions for probability and statistics. This class demonstrates application of these functions for modeling and analysis in statistics. Presentation topics also include automated probability and statistics superfunctions, streamlined processes for parameter estimation and goodness-of-fit testing, working with built-in distributions or creating your own from data or other distributions, and statistical visualization functionality.

Statistical Analysis with Wolfram Language

##### Statistical Analysis with Wolfram Language
###### Video Course | FREE

Analyze your data using a framework of model fitting and statistical analysis built into the Wolfram Language. Whether it is basic descriptive and exploratory statistics or advanced modeling with statistical distributions, you can follow this video course to gain an understanding of the statistical functionality available in the Wolfram Language. Topics covered include descriptive measures, transformations, basic clustering, statistical distributions, parameter estimation and hypothesis testing. Advanced topics on using optimization functions, linear algebra functions, analysis of variance (ANOVA) and generalized logit and probit linear models will also be explored.

###### Course Overview
• Video 111 minutes
• Video 224 minutes
• Video 314 minutes
• Video 417 minutes
• Video 534 minutes

Statistical Distributions

##### Statistical Distributions
###### Video Lesson | FREE

The Wolfram Language includes extensive coverage for statistical distributions. This class explores the properties of derived distributions, probability distributions, mixture distributions and more. Other topics include random number generation and parameter estimation. This class assumes basic familiarity with the Wolfram Language and statistics concepts.

## Course Type

• Interactive Courses
• Video Lessons
• Video Courses
• Instructor-led Courses
• Archived and Special Events

### Interactive Courses

Also known as MOOCs (massive open online courses), these courses are hosted on the Wolfram Cloud and allow you to interactively explore concepts using Wolfram Language functionality.

• Self-paced with progress tracking

• Include video lessons, exercises and problems, quizzes, exams and a scratch notebook

• Sharable completion certificates available for all courses

• Wolfram Level 1 proficiency certifications available for select courses

### Video Lessons

Short recorded lessons that provide limited instruction on a computational topic or for using Wolfram tech.

• Quick-start videos

• Lessons from content experts

• A wide variety of beginner-level lessons

• Free to watch

### Video Courses

Video series that build on preceding lessons to provide comprehensive instruction.

• Each video course features a playlist of sequential lessons

• Recorded by Wolfram certified instructors

• Comprehensive coverage of a particular topic

• Free to watch

### Instructor-led Courses

Scheduled as online and in-person classes, these courses provide comprehensive instruction guided by a live instructor.

• Registration required to reserve your seat

• Taught by Wolfram certified instructors

• Opportunity to pose live questions to experts in the room

• Course completion certificates available

### Archived and Special Events

Presentations by Wolfram developers, content experts and instructors.

• Webinars on special topics and new release functionality

• Livecoding sessions

• Wolfram Daily Study Groups

• Free to watch