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Data Analysis courses

Data analysis courses teach techniques for inspecting, cleaning, transforming, and modeling data to discover useful information, inform conclusions, and support decision-making. Build your analysis skills using technologies such as Python, R and SQL.

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Recommended for Data Analysis beginners

Build your Data Analysis skills with interactive courses, curated by real-world experts

コース

Tableauでデータを分析する

基礎スキルレベル
4.8+
3.2K
8 時間
高度な分析と可視化により、Tableauのスキルをさらに向上させましょう。

トラック

アソシエイトデータアナリスト in SQL

52.7K
39 時間
データベースをクエリし、結果を分析するために必要なSQLスキルを習得し、SQLに精通したデータアナリストとなるための知識を身につけましょう。プログラミングの経験は一切不要です!

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Data Analysis のコースとトラックを閲覧

コース

Rによる推測の基礎

中級スキルレベル
4.7+
505
4 時間
統計的推測と呼ばれる手法で、サンプルから母集団について結論を導く方法を学びます。

コース

Bayesian Data Analysis in Python

中級スキルレベル
4.7+
499
4 時間
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

コース

Case Study: Supply Chain Analytics in Power BI

中級スキルレベル
4.8+
492
4 時間
Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

コース

Introduction to Linear Modeling in Python

中級スキルレベル
4.7+
490
4 時間
Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

コース

RNA-Seq with Bioconductor in R

中級スキルレベル
4.7+
480
4 時間
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

コース

R の data.table によるデータ操作

基礎スキルレベル
4.7+
480
4 時間
data.tableでフィルタリングや選択、グループ統計の計算など、データ操作の基礎概念をマスターしましょう。

コース

Data Processing in Shell

中級スキルレベル
4.8+
471
4 時間
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

コース

Visualization Best Practices in R

基礎スキルレベル
4.8+
469
4 時間
Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

コース

Rで学ぶWebスクレイピング

中級スキルレベル
4.7+
462
4 時間
Rで任意のWebサイトからデータを効率よく収集し、ダウンロードする方法を学びます。

コース

Pythonで学ぶ Spark SQL 入門

上級スキルレベル
4.7+
460
4 時間
PythonのSQLを使用して、Sparkにおけるデータの操作方法と機械学習の特徴量セットの作成方法を学びましょう。

コース

Visualizations in Sigma

基礎スキルレベル
4.8+
458
2 時間
Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.

コース

Feature Engineering with PySpark

上級スキルレベル
4.8+
458
4 時間
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

コース

Dealing With Missing Data in R

基礎スキルレベル
4.7+
447
4 時間
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

コース

Rで学ぶ中級データインポート

中級スキルレベル
4.8+
438
3 時間
あらゆる形式のデータを解析。フラットファイル、統計ソフト、データベース、Web上のデータまで対応します。

コース

SQL Serverで学ぶ時系列分析

中級スキルレベル
4.8+
434
5 時間
SQL Serverで日時データの扱い方を学び、時系列分析に活用する方法を探る

コース

Rで学ぶ実験計画法

中級スキルレベル
4.7+
433
4 時間
このコースでは、データ分析に不可欠な基礎的な実験計画法を学びます。

コース

Communicating with Data in the Tidyverse

基礎スキルレベル
4.8+
432
4 時間
Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

コース

Pythonで学ぶ一般化線形モデル

上級スキルレベル
4.7+
423
5 時間
ロジスティック回帰とポアソン回帰を追加し、学習・解釈・検証と予測まで行えるようにします。

コース

Foundations of Probability in Python

中級スキルレベル
4.8+
407
5 時間
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

コース

Anomaly Detection in Python

中級スキルレベル
4.8+
390
4 時間
Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Data Analysis の関連リソース

ブログ

How to Become a Data Analyst in 2026: 5 Steps to Start Your Career

Learn how to become a data analyst and discover everything you need to know about launching your career, including the skills you need and how to learn them.
Elena Kosourova's photo

Elena Kosourova

15 分

ブログ

30 Data Analytics Projects for All Levels in 2026

Explore our list of data analytics projects for beginners, final-year students, and professionals. The list consists of guided/unguided projects and tutorials with source code.
Abid Ali Awan's photo

Abid Ali Awan

13 分

チュートリアル

Alteryx Tutorial: A Comprehensive Hands-On Guide for Data Analytics

Dive into our detailed Alteryx tutorial and learn how this powerful data analytics tool can transform your data handling experience. This guide covers everything from installation to advanced workflow automation in Alteryx, making it the perfect resource for beginners and seasoned data professionals alike.
Kurtis Pykes 's photo

Kurtis Pykes

11 分


Ready to apply your skills?

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Frequently asked questions

Is data analysis easy to learn?

It’s different for everyone. Some people pick up data analysis very quickly, while others need a bit more time. The underlying theory and concepts are not hard to understand (or highly technical), but you’ll need to learn a few popular data analysis tools. 

This includes SQL and databases, a programming language such as Python or R, spreadsheets and Excel, and software such as Power BI or Tableau. 

It might sound like a lot, but each technology is easy to learn individually, especially when you choose data analysis courses from a dedicated online training provider like DataCamp.

Has AI changed the role or need for data analysts?

AI is indeed transforming the data analyst's role. Rather than replacing them, it has automated repetitive tasks, freeing analysts to focus on complex issues, interpret AI results, and strategize. Although AI aids in data analysis, human supervision for training and adjusting AI models remains crucial. Thus, AI is changing the analyst role but increased its importance.

Which data analysis course is the best?

We only release courses that meet our high quality standards, which is why DataCamp is known as a leading platform for learning data analysis! That being said, our Data Analyst with Python Career Track is one of our most popular, comprehensive course programs for acquiring the skills to become a data analyst from scratch.

How can I become a data analyst quickly?

To become a data analyst quickly, a structured learning path like DataCamp's Career Tracks is beneficial. For example, programs such as our Data Analyst with Python and Data Analyst with Power BI Tracks are designed to gradually upskill you in the various concepts, technologies and processes required to be a data analyst.

And importantly, becoming a data analyst requires dedication and consistency in learning, while embracing a positive attitude towards problem-solving. Applying your knowledge to real-world projects helps solidify concepts, and creating a data portfolio to showcase these projects can demonstrate your proficiency to potential employers.

See our 'How to become a data analyst' article for further guidance.

How can online courses help you learn data analytics?

DataCamp's courses provide a flexible and convenient way to learn data analytics at your own pace. Our data analytics courses, taught by industry experts, offer interactive exercises and practical projects that help you apply theoretical concepts to real-world scenarios.

Do I need a background in programming to start learning data analytics?

No, you don't need a programming background to start learning data analytics. Our beginner courses, such as Introduction to SQL and Analyzing Data in Tableau, are designed to accommodate beginners and gradually introduce programming concepts, if needed.

What jobs can you get with data analysis skills?

With data analysis skills in your technical tool kit, you have plenty of job options:

  • Data analyst
  • Database administrator
  • Systems analyst
  • Business intelligence
  • Digital marketer
  • Data scientist
  • Financial analyst
  • And many more!

Because the modern business world is data-driven, people with data analysis skills find it easy to get work in an eclectic mix of industries and sectors.

Are data analysis skills in demand?

Yes, data analysts are some of the most in-demand professionals worldwide. Data from the US Bureau of Labor Statistics suggest the number of jobs for analysts is expected to grow by 23% between 2021 and 2031.

How can I prove my data analysis skills to employers?

To prove your data analysis skills to employers, you can complete our industry recognized Data Analyst Certification. This certification showcases your data analysis knowledge using SQL and either Python or R.

What tools and software are commonly used in data analytics?

Common tools in data analytics include Excel, SQL, Python, R, Tableau, and Power BI. These tools help in data manipulation, analysis, and visualization.

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