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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

Google Sheets のピボットテーブル

基礎スキルレベル
4.8+
823
2 時間
数回のクリックでピボットテーブルを作成し、数千のデータポイントをすばやく整理する方法を学びます。

コース

Pythonで学ぶA/Bテスト

中級スキルレベル
4.7+
786
4 時間
PythonでA/Bテストの実務を学び、実験の実行と分析を習得。p値、サニティチェック、分析で意思決定を支援。

コース

Calculations in Tableau

上級スキルレベル
4.7+
780
6 時間
In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

コース

Data Transformation in Alteryx

基礎スキルレベル
4.8+
774
2 時間
Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.

コース

Pythonで学ぶデータベース入門

中級スキルレベル
4.7+
743
4 時間
このコースでは、リレーショナルデータベースの基礎と、その操作方法を学びます。

コース

Alteryxでのデータ操作

基礎スキルレベル
4.8+
718
3 時間
Alteryxでユニオン、ジョイン、パースを用いてデータを統合し、パフォーマンス最適化を行います。

コース

tidyverse で学ぶモデリング

中級スキルレベル
4.8+
710
4 時間
予測を含むデータモデリングの種類を学び、Tidyverseでの線形回帰とモデル評価指標の実施方法を習得します。

コース

中級 Google Sheets

基礎スキルレベル
4.8+
691
4 時間
Google Sheetsの語彙を強化。数値、論理、欠損などのデータ型を深く学び、理解を広げましょう。

コース

Data Visualization in Databricks

基礎スキルレベル
4.7+
666
3 時間
Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

コース

Rで学ぶ確率の基礎

基礎スキルレベル
4.8+
665
4 時間
このコースでは、確率変数、分布、条件付けの概念を学びます。

コース

Rで始めるテキスト分析

中級スキルレベル
4.8+
645
4 時間
tidy フレームワークを用いて、R でテキストデータを分析する。

コース

Intermediate SQL Querying with AI

基礎スキルレベル
4.9+
627
3 時間
Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.

コース

Oracle SQL 入門

基礎スキルレベル
4.8+
627
4 時間
Oracle SQLで、基礎、集計、結合、データのカスタマイズを学び、スキルを磨きましょう。

コース

Data Types and Functions in Snowflake

中級スキルレベル
4.8+
619
3 時間
Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.

コース

Window Functions in Snowflake

中級スキルレベル
4.8+
612
3 時間
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.

コース

Polars入門

基礎スキルレベル
4.8+
598
3 時間
高速なデータ操作が可能なPythonライブラリPolarsで、データの変換、クレンジング、分析を効率的に行う方法を学びます。

コース

Case Study: Analyzing Job Market Data in Power BI

基礎スキルレベル
4.8+
571
4 時間
Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

コース

Introduction to Bioconductor in R

中級スキルレベル
4.8+
552
4 時間
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

コース

Statistical Techniques in Tableau

中級スキルレベル
4.8+
515
4 時間
Take your reporting skills to the next level with Tableau’s built-in statistical functions.

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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