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手を動かしながらやさしく学べる はじめてのAIデータサイエンスリテラシー (AI Data Science Literacy)
手を動かしながらやさしく学べる はじめてのAIデータサイエンスリテラシー (AI Data Science Literacy)
by M. Kitamura, Akiko Kanamitsu, Erika Drago, Yoko Ono, Tomoko Yoshida
  • Publisher: 技術評論社
  • Year: 2025
  • ISBN: 9784297151072
  • 208 pp
Description

The data that surrounds us in our daily lives helps us construct new stories by targeting all things expressed in various forms, such as images and text in the world of digital data. With the magic wand called data science, we can incorporate all facts as data into our "horizon of thought," visualize them and from there weave new stories—that is, the future.

However, data science truly becomes a magic wand only when we understand its essence and can handle it skillfully. Some people may have given up on data science because it contains abundant mathematics and programming. Good news for such people!

This book is overflowing with materials that allow you to learn the essence of data science and AI through enjoyable experiences while working hands on, learning with excitement. The Wolfram Language covered in this book has many functions prepared in advance for learning the world of data science and AI. By using these functions, you can enter this world with excitement.

Without being bothered by mathematical calculations or programming syntax, this book allows you to take on creative challenges. Please try entering the world of AI and data science.

Recommended for:

  • Those who want to learn AI and data science by actually running programs themselves
  • Middle- and high-school students and teachers who want to learn the basics of AI and data science and apply them to academic learning and inquiry activities
  • University students and teachers interested in practical applications of data analysis and AI programming using Wolfram Language
  • Those who want to enjoy learning programming with Wolfram Language
Contents
Chapter 1: Experience the World of Wolfram Language
  • Experience with Online Content
  • Learn Basic Rules and Actually Use Them!
  • Make Use of Online Documentation
Chapter 2: Programming Fundamentals
  • How Computers Work
  • History of Programming Languages and Types of Languages
  • Algorithms and Data Structures
  • Three Basic Processes of Programs
Chapter 3: The World Visible from Image Data
  • What Is Image Data
  • Various Image Processing Techniques
Chapter 4: The World Visible from Sound and Audio Data
  • What Is Sound and Audio Data
  • Various Audio Processing Techniques
Chapter 5: How AI Works
  • An AI's Brain Is a Program
  • The Mechanism for Training an AI's Brain: Machine Learning
  • What Is Supervised Machine Learning
  • Exercise: Try Classifying Candy with Supervised Machine Learning
  • What Is Unsupervised Machine Learning
  • Exercise: Try Grouping Animals with Unsupervised Machine Learning
Chapter 6: The World Visible from Text Data
  • What Is Text Data
  • Natural Language Processing
  • What Is a Word Cloud
  • Exercise: Create a Word Cloud of "Run, Melos!"
Chapter 7: Fundamentals of Statistics
  • The Relationship between Statistics and AI/Data Science
  • Data Collection and Types
  • Histograms and Basic Statistics
  • Exercise: Try Creating Histograms and Basic Statistics
  • Relationship between Two Datasets
  • Data Visualization
Chapter 8: Utilization of AI and Data in Society
  • Data-Driven Society
  • AI and Data Utilization Case Studies
  • Personal Information and Information Security Guidelines
  • Guidelines for Handling AI and Data
Chapter 9: Generative AI
  • History of AI
  • Neural Networks
  • Try Using the Knowledge-Based Wolfram|Alpha
  • How Generative AI Works
  • The Future of Generative AI
  • Wolfram Language Tutorial
Appendix: Data Science for Understanding the Real World
  • Exploratory Activities and Statistical Problem Solving (PPDAC Cycle)
  • Let's Practice Data Science Exploration: Bias in Problem Setting and Formalization of Tacit Knowledge
  • Step 1: Problem—How to Use Dollar Street
  • Step 2: Plan and Data Collection—How to Use UNICEF Data
  • About the Human Development Index (HDI) Representing Human Well-Being
  • Step 3: Data Collection and Analysis—Geographic Data Analysis for Achieving SDGs
  • Step 4: Data Collection and Analysis—How to Use Wolfram Language and Wolfram|Alpha in Exploratory Activities
  • Data Collection and Analysis Using Wolfram|Alpha
  • Data Analysis and Exploratory Activities with Wolfram Language
  • Practical Examples of Wolfram Language for SDGs Problem Exploration
  • Step 5: Conclusion (Solutions and Presentation)—Present Problem Solutions Backed by Data
Related Topics
Computer Science, Courseware, Programming, Tutorial and Reference
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