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Data Science: Foundations using R専門講座ジョンズ・ホプキンズ大学（Johns Hopkins University）学習内容
Use R to clean, analyze, and visualize data.
Learn how to ask the right questions, obtain data, and perform reproducible research.
Use GitHub to manage data science projects.
Set up R, R-Studio, Github and other useful tools
習得するスキル
この専門講座について
110,649 最近の表示
Ask the right questions, manipulate data sets, and create visualizations to communicate results.
This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. Learners who complete this specialization will be prepared to take the Data Science: Statistics and Machine Learning specialization, in which they build a data product using real-world data.
The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization. This specialization is presented for learners who want to start and complete the foundational part of the curriculum first, before moving onto the more advanced topics in Data Science: Statistics and Machine Learning.
応用学習プロジェクト
In taking the Data Science: Foundations using R Specialization, learners will complete a project at the ending of each course in this specialization. Projects include, installing tools, programming in R, cleaning data, performing analyses, as well as peer review assignments.
受講生の就業成果
38%
この専門講座終了後に新しいキャリアをスタートしました
15%
昇給や昇進につながった
共有できる証明書
修了時に証明書を取得
100%オンラインコース
自分のスケジュールですぐに学習を始めてください。
フレキシブルなスケジュール
柔軟性のある期限の設定および維持
初級レベル
経験は不要です。
約5か月で修了
推奨8時間/週
英語
字幕：英語, アラビア語, フランス語, ポルトガル語（ヨーロッパ）, 中国語（簡体）, イタリア語, ベトナム語, 韓国語, ドイツ語, ロシア語, トルコ語, スペイン語, ポルトガル語（ブラジル）, 日本語
受講生の就業成果
38%
この専門講座終了後に新しいキャリアをスタートしました
15%
昇給や昇進につながった
共有できる証明書
修了時に証明書を取得
100%オンラインコース
自分のスケジュールですぐに学習を始めてください。
フレキシブルなスケジュール
柔軟性のある期限の設定および維持
初級レベル
経験は不要です。
約5か月で修了
推奨8時間/週
英語
字幕：英語, アラビア語, フランス語, ポルトガル語（ヨーロッパ）, 中国語（簡体）, イタリア語, ベトナム語, 韓国語, ドイツ語, ロシア語, トルコ語, スペイン語, ポルトガル語（ブラジル）, 日本語
この専門講座には5コースあります。
The Data Scientist’s Toolbox
30,624件の評価
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
Rプログラミング
20,275件の評価
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
Getting and Cleaning Data
7,668件の評価
Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.
探索的データ解析
5,797件の評価
This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.
提供：
ジョンズ・ホプキンズ大学（Johns Hopkins University）
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
よくある質問
専門講座を修了することで大学の単位は付与されますか？
Can I just enroll in a single course?
1つのコースだけに登録することは可能ですか？
Can I take the course for free?
無料でコースを受講できますか？
このコースは100%オンラインで提供されますか？実際に出席する必要のあるクラスはありますか？
専門講座を修了するのにどのくらいの期間かかりますか？
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
専門講座を修了することで大学の単位は付与されますか？
Can I sign up for the course without paying or applying for financial aid?
さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。
