Short Lessons on Wolfram Language - Programming, Data Processing, Graphics, Machine Learning, and Quantum Computing with Mathematica

Aug 4, 2026

Upload by Asher

A practical, concise learning guide to Wolfram Language through Mathematica, covering core programming constructs, variable and function behavior, loops, scoping, and pattern-based rules. It explains essential data structures including lists, matrices, and tensors, along with number and string handling and regular expressions. The book also teaches visualization via 2D/3D graphics, graph construction and layouts, algebraic and differential equation solving, and importing/exporting external data for analysis. Advanced chapters introduce machine learning workflows and quantum computing concepts using QI.

LanguageEnglish

CategoryTechnology

FormatPDF

Pages147

Reading Time6 h 10 min

AccessFree to download

Quick introduction

Where to use?

Getting help

Interacting with the system

Mathics – open source implementation

Variables, functions, loops

Introduction

Assignments

Caching calculation results

Rules and patterns

Pure anonymous functions

Loops and repetitions

Conditional execution

Scoping

Lists of functions

Lists, matrices, and tensors

Introduction

Inputting matrices

Matrix multiplication

Displaying matrices

Special matrices

Constructing matrices

Matrices of random numbers

Changing the shape

Symbolic matrices

Associations

Numbers and strings

Strings and other atoms

String operations

Converting numbers

Numbers from strings

Matching text and regular expressions

Graphics and visualization

Tutorial of plot functionality

Plotting tabular data

3D graphics

Saving graphics

Graphs

Constructing graphs

Common graphs

Graph layouts

Weighted graphs

Random graphs

Using graphs

Solving and simplifying

Algebraic equations

Systems of equations

Differential equations

Recurrence equations

Simplifying expressions

Assumptions

Using external data

Export formats

Import and cloud storage

Data frames

External data

Machine learning

Introduction

Harness built-in AI

Linear regression

Regression

Classification

Artificial neural networks

Using large language models

Quantum computing

Package QI

Pure states and quantum gates

Density matrices

Quantum gates

Examples

Packages, scripting, external evaluation

Batch execution

Parallel processing

Packages

Integration with external systems

Internet resources

Bibliography

Short Lessons on Wolfram Language Jarosław Miszczak Programming, Data Processing, Graphics, Machine Learning, and Quantum Computing with Mathematica Short Lessons on Wolfram Language Programming, Data Processing, Graphics, Machine Learning, and Quantum Computing with Mathematica Jaroslaw Adam Miszczak This book is freely available from [https://miszczak.eu/wl-lessons](https://miszczak.eu/wl-lessons) Short Lessons on Wolfram Language Programming, Data Processing, Graphics, Machine Learning, and Quantum Computing with Mathematica © 2024 by Jaroslaw Adam Miszczak, [https://miszczak.eu/wl-lessons](https://miszczak.eu/wl-lessons)[ ](https://miszczak.eu/wl-lessons)ISBN: 978-83-66950-01-6 (paperback) Publisher: Quoqa Pubs First edition. April 2024 Technical editing: J&M This document can be distributed under CC BY-SA 4 .0. Full information about the license: [http://creativecommons.org/licenses/by](http://creativecommons.org/licenses/by)sa/4.0/ Wolfram Language and Mathematica are register trademarks of Wolfram Research Inc. Wolfram Research, Inc., Wolfram Language, Version 14.0.0, Champaign, IL (2023). [https://www.wolfram.com/language](https://www.wolfram.com/language). This book is freely available from [https://miszczak.eu/wl-lessons](https://miszczak.eu/wl-lessons) Contents Preface 6 0 Quick introduction 9 0.1 Where to use? ............................ 9 0.2 Getting help ............................. 9 0.3 Interacting with the system .................... 11 0.4 Mathics – open source implementation .............. 14 1 Variables, functions, loops 17 1.1 Introduction ............................. 17 1.2 Assignments ............................. 20 1.3 Caching calculation results .................... 21 1.4 Rules and patterns ......................... 22 1.5 Pure anonymous functions ..................... 24 1.6 Loops and repetitions ....................... 26 1.7 Conditional execution ....................... 30 1.8 Scoping ............................... 31 1.9 Lists of functions .......................... 32 2 Lists, matrices, and tensors 35 2.1 Introduction ............................. 35 2.2 Inputting matrices ......................... 35 2.3 Matrix multiplication ........................ 36 2.4 Displaying matrices ......................... 37 2.5 Special matrices .......................... 39 2.6 Constructing matrices ....................... 39 2.7 Matrices of random numbers ................... 41 2.8 Changing the shape ........................ 41 2.9 Symbolic matrices ......................... 44 2.10 Associations ............................. 45 3 Numbers and strings 47 3.1 Strings and other atoms ...................... 47 3.2 String operations .......................... 48 3.3 Converting numbers ........................ 49 3 This book is freely available from [https://miszczak.eu/wl-lessons](https://miszczak.eu/wl-lessons) Contents 3.4 Numbers from strings ....................... 50 3.5 Matching text and regular expressions .............. 51 4 Graphics and visualization 53 4.1 Tutorial of plot functionality ................... 54 4.2 Plotting tabular data ........................ 62 4.3 3D graphics ............................. 67 4.4 Saving graphics ........................... 68 5 Graphs 69 5.1 Constructing graphs ........................ 69 5.2 Common graphs .......................... 72 5.3 Graph layouts ............................ 73 5.4 Weighted graphs .......................... 74 5.5 Random graphs ........................... 76 5.6 Using graphs ............................ 79 6 Solving and simplifying 83 6.1 Algebraic equations ......................... 83 6.2 Systems of equations ........................ 87 6.3 Differential equations ........................ 88 6.4 Recurrence equations ........................ 88 6.5 Simplifying expressions ....................... 90 6.6 As

FAQs

What programming fundamentals does the book cover for Wolfram Language?

It introduces variables, functions, assignments, caching, rules and patterns, pure anonymous functions, loops and repetitions, conditional execution, and scoping. It also covers lists of functions and how to interact with the system effectively.

How does the book teach working with structured data?

It focuses on lists, matrices, and tensors, including inputting and displaying matrices, matrix multiplication, constructing special and random-number matrices, changing shapes, and using symbolic matrices and associations.

Which advanced topics are included beyond basic programming?

The later chapters cover graphics and visualization, graph construction, solving and simplifying math problems, using external data, machine learning (including built-in AI and large language models), and quantum computing with the QI package.

Aug 4, 2026

Upload by Asher