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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

课程

在 Tableau 中分析数据

基础技能水平
4.8+
1,608 条评价
8小时
用高级分析和可视化提升你的 Tableau 技能。

学习路径

初级数据分析师 在 SQL 中

4.7+
172 条评价
39小时
掌握查询数据库、分析结果并成为精通 SQL 的数据分析师所需的 SQL 技能。 无需编程经验!

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课程

Power BI 中的数据转换

中级技能水平
4.7+
5,020 条评价
3小时
你将学习如何对表进行(取消)透视、转置、追加和连接。 用自定义列、M 语言和高级编辑器提升能力。

课程

R 统计学入门

中级技能水平
4.7+
2,022 条评价
4小时
提升统计技能,学习如何收集、分析数据并得出准确结论。

课程

Power BI 中的 DAX 函数

基础技能水平
4.8+
4,429 条评价
3小时
数据分析表达式 (DAX) 可通过编写自定义函数,将你的 Power BI 技能提升到新水平。

课程

R 中的回归入门

中级技能水平
4.8+
1,430 条评价
4小时
用 R 实现、分析并解读回归分析,预测房价和广告点击率。

课程

使用 dplyr 进行数据处理

基础技能水平
4.8+
693 条评价
4小时
通过学习如何使用 dplyr 转换和处理数据,提升 Tidyverse 技能。

课程

Power BI 中级 DAX

中级技能水平
4.8+
3,874 条评价
3小时
掌握丰富的 DAX 计算,并学习如何在 Microsoft Power BI 中使用它们。

课程

Power BI 中的探索性数据分析

基础技能水平
4.8+
3,609 条评价
3小时
学习如何使用 Power BI 的探索性数据分析(EDA)构建有影响力的报告,更快发现洞察并推动业务价值。

课程

Power BI 报表

中级技能水平
4.7+
2,853 条评价
3小时
用你已有的技能,让你的 Power BI 可视化更上一层楼。 学习替代数据讲故事技巧,而不只是构建仪表板。

课程

NumPy 入门

基础技能水平
4.8+
1,420 条评价
4小时
通过纽约市树木普查学习如何创建、排序、筛选和更新数组,精通 NumPy 技能。

课程

Excel 高级函数

中级技能水平
4.8+
1,135 条评价
2小时
通过实用练习,掌握高级引用、查找和数据库函数,提升你的 Excel 技能。

课程

Power BI 趋势分析

中级技能水平
4.8+
3,135 条评价
3小时
用时间序列、分解树和关键影响因素等趋势分析技术,提升你的报表。

课程

Introduction to Google Sheets

基础技能水平
4.8+
1,856 条评价
2小时
Bring your Google Sheets to life by mastering fundamental skills such as formulas, operations, and cell references.

课程

Power BI 中的数据连接

基础技能水平
4.8+
3,355 条评价
2小时
探索提升 Power BI 数据导入技能的多种方法。

课程

Power BI 报表设计

中级技能水平
4.7+
2,807 条评价
3小时
继续你的数据可视化之旅,学习在报表中融入 DAX 度量值和渐进式披露的实用技巧。

课程

在 Power BI 中部署与维护资产

中级技能水平
4.8+
3,026 条评价
2小时
学习如何在 Power BI 中部署和维护资产。 你将掌握 Power BI Service 界面及其关键元素,如工作区。

课程

Python 假设检验

中级技能水平
4.7+
3,399 条评价
4小时
了解如何以及何时在 Python 中使用常见假设检验,如 t 检验、比例检验和卡方检验。

课程

Dashboard 设计概念

基础技能水平
4.7+
1,025 条评价
2小时
学习创建有影响力仪表板所需的技能。 掌握仪表板设计基础、可视化分析组件和仪表板类型。

课程

Python 抽样

中级技能水平
4.7+
3,591 条评价
4小时
学会用 Python 和统计学从有限数据中得出结论。 本课程涵盖从随机抽样到分层抽样和整群抽样的所有内容。

课程

R 中的假设检验

中级技能水平
4.7+
942 条评价
4小时
了解如何以及何时在 R 中使用假设检验,包括 t 检验、比例检验和卡方检验。

课程

在 Tableau 中创建仪表板

基础技能水平
4.8+
1,390 条评价
3小时
在数据驱动的世界里,仪表板是必备工具。 用 Tableau 仪表板提升业务绩效影响力。

课程

R 数据导入入门

基础技能水平
4.7+
352 条评价
3小时
在本课程中,您将学习如何在 R 中使用 readxl 和 data.table 等工具读取 CSV、XLS 和文本文件。

课程

Web Scraping in Python

中级技能水平
4.7+
1,030 条评价
4小时
Learn to retrieve and parse information from the internet using the Python library scrapy.

课程

Introduction to Sigma

基础技能水平
4.8+
417 条评价
2小时
Get started with Sigma! Learn how to build and customize simple, interactive dashboards for real-time analytics.

课程

Power Pivot in Excel

基础技能水平
4.8+
1,395 条评价
3小时
Master Power Pivot in Excel to help import data, create relationships, and utilize DAX. Build dynamic dashboards to uncover actionable insights.

课程

Data Preparation in Alteryx

基础技能水平
4.8+
1,058 条评价
3小时
Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.

课程

Exploratory Data Analysis in R

中级技能水平
4.7+
1,197 条评价
4小时
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Data Analysis 相关资源

博客

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分钟

博客

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分钟

教程

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分钟


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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.

其他技术和主题

技术

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随时随地通过我们的移动课程和每日 5 分钟编程挑战提升技能。