Excel/Googleスプレッドシートで学ぶデータサイエンスの基礎 近代科学社Digital
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Excel/Googleスプレッドシートで学ぶデータサイエンスの基礎 近代科学社Digital
Learn the basics of data science using Excel and Google spreadsheets, designed specifically for beginners and first-year university students.
Excel/Googleスプレッドシートで学ぶデータサイエンスの基礎 近代科学社Digital
товар №: 135103302

Excel/Googleスプレッドシートで学ぶデータサイエンスの基礎 近代科学社Digital

86% of respondents would recommend this to a friend

товар №: 135103302

AMD 9198

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What Stands Out

Accessible Learning
Designed for beginners, this book simplifies data science concepts using Excel and Google Sheets, making them comprehensible for non-technical users aiming to enhance their analytical skills.
Hands-On Approach
Includes practical exercises and real-world examples, allowing readers to apply their knowledge immediately and build confidence in using data science tools effectively.
Comprehensive Coverage
Covers a wide range of topics from data visualization to statistical analysis, ensuring readers gain a well-rounded understanding of data science essential for various industries.

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Shop Excel/Googleスプレッドシートで学ぶデータサイエンスの基礎 近代科学社Digital online at a best price in Armenia. 4764907364
  • 　本書は、数理・データサイエンス教育強化拠点コンソーシアムが公表している「数理・データサイエンス・AI（リテラシーレベル）モデルカリキュラム～データ思考の涵養」の「基礎（2.データリテラシー）」で示されている「データを適切に読み解く力」「データを適切に説明する力」「データを扱うための力」を養うことを目的としています。主に大学１年生を対象に、初学者にも扱いやすいスプレッドシート（Microsoft ExcelやGoogleスプレッドシート）を用いてデータサイエンスの基礎を学習します。序盤では、スプレッドシートの使い方やオープンデータの利用方法を通して、データの扱い方を学習します。中盤では、高等学校までの情報教育との接続としてデータの可視化や基本統計量についてより理解を深めていき、終盤では、代表的な確率分布を取り上げ、統計学への理解を深める構成としています。
Publisher 近代科学社
Publication date February 25, 2025
Language Japanese
Print length 122 pages
ISBN-10 4764907364
ISBN-13 978-4764907362
Item Weight 270 g
Dimensions 7.17 x 0.31 x 10.12 inches (18.2 x 0.8 x 25.7 cm)

Who Should Buy?

Suitable For
  • Beginners in Data

    Ideal for individuals starting to learn data science concepts using user-friendly tools like Excel and Google Sheets.

  • Students and Academics

    Beneficial for students seeking practical applications of data science in academic projects using spreadsheets for analysis.

  • Small Business Owners

    Useful for entrepreneurs wanting to leverage data insights for decision-making without needing advanced software or skills.

Not Suitable For
  • Advanced Users

    Experienced data scientists may find the content too simplistic and lacking in advanced analytical techniques or tools.

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Вопросы и ответы клиентов

  • вопрос: Who is this book intended for?

    отвечать: This book is primarily aimed at first-year university students or beginners in data science.
  • вопрос: What tools will I learn with this book?

    отвечать: You will learn to use Microsoft Excel and Google spreadsheets for data science.
  • вопрос: What topics are covered in this book?

    отвечать: The book covers data handling, visualization, basic statistics, and probability distributions.

徳野 淳子 , 田中 武之 Spreadsheets Editorial Review

Excel/Googleスプレッドシートで学ぶデータサイエンスの基礎 offers a comprehensive introduction to data science using accessible tools like Excel and Google Sheets. Published by 近代科学社, this 122-page guide is designed to make data analysis approachable for Japanese readers. The combination of spreadsheet familiarity and data science principles makes it an excellent resource. The publication, set to release on February 25, 2025, emphasizes practical applications in data science, catering to beginners and intermediate learners alike. Readers may appreciate the clear language and structured approach, making it easier to digest complex concepts efficiently.

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Плюсы

  • Easy to understand for beginners
  • Focus on practical applications
  • Utilizes widely used tools
  • Well-structured content for learning
  • Available in Japanese language

Минусы

  • Limited to just 122 pages for depth

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Особенности и преимущества

  • Designed for beginners in data science.
  • Utilizes familiar tools: Excel and Google spreadsheets.
  • Caters primarily to first-year university students.
  • Focused on data handling, visualization, and basic statistics.
  • Develops essential data literacy skills.
  • Structured learning from basic to advanced data concepts.

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