探索性数据分析课程
探索性数据分析课程可以帮助您学习数据可视化技术、统计摘要和数据清洗方法。您可以掌握识别模式、检测异常和解释结果的技能，为决策提供依据。许多课程都会介绍 Python、R 和 Tableau 等工具，这些工具有助于分析和展示数据见解，让您能够有效地交流研究结果并支持数据驱动战略。
热门探索性数据分析课程与认证
状态：新Packt
您将获得的技能: NumPy, Time Series Analysis and Forecasting, Scikit Learn (Machine Learning Library), Pandas (Python Package), Matplotlib, Data Analysis, Predictive Analytics, Data Visualization, Database Management, Applied Machine Learning, Scientific Visualization, Data Manipulation, Data Science, Statistics, Python Programming, Statistical Analysis, Data Wrangling, Big Data, NoSQL, Data Preprocessing
状态：免费试用University of Illinois Urbana-Champaign
您将获得的技能: Jupyter, 数据可视化软件, 数据质量, 数据操作, 数据故事, 查询语言, Pandas（Python 软件包）, 探索性数据分析, 分析技能, 摘录, 数据处理, Python 编程, 数据清理, 商业分析, 数据驱动决策, 应用编程接口 (API), 商业智能
状态：新状态：免费试用您将获得的技能: Rmarkdown, Knitr, Model Evaluation, Data Wrangling, Tidyverse (R Package), Predictive Analytics, Data Analysis, Data Cleansing, Statistical Reporting, R Programming, Data Manipulation, Data Integration, Data Transformation, Statistical Modeling, Extract, Transform, Load, Data Pipelines, Performance Analysis, Performance Metric, Automation
状态：新您将获得的技能: Data Visualization, Data Structures
状态：免费试用University of Michigan
您将获得的技能: 散点图, 数据分析, 数据可视化软件, 数据可视化, 绘图（图形）, 数据展示, Ggplot2, 平面和视觉设计, 探索性数据分析, 柱状图, 趋势分析, 公共行政, R 程序设计, 政策分析, 统计可视化, Tidyverse（R 软件包）, R（软件）
状态：免费试用您将获得的技能: Exploratory Data Analysis, Predictive Modeling, Decision Tree Learning, Data Analysis, Regression Analysis, Classification Algorithms, Supervised Learning, Machine Learning Algorithms, Model Evaluation, Scikit Learn (Machine Learning Library), Data Preprocessing, Statistical Machine Learning, Feature Engineering
状态：新状态：预览SkillsBooster Academy
您将获得的技能: Microsoft Copilot, Data Visualization, Data Analysis, Exploratory Data Analysis, Data Storytelling, Data Visualization Software, Dashboard, Data Cleansing, Data-Driven Decision-Making, Business Intelligence, Microsoft Excel, AI Workflows, Microsoft PowerPoint, Artificial Intelligence and Machine Learning (AI/ML), AI Personalization, Excel Formulas, Data Architecture, Excel Macros, Generative AI, Microsoft Windows
状态：免费试用您将获得的技能: Exploratory Data Analysis, Data Visualization, Data Literacy, Data-Driven Decision-Making, Data Presentation, SAS (Software), Data Storytelling, Trend Analysis, Data Manipulation, Data Analysis, Data Quality, Data Preprocessing, Analysis, Analytics, Interactive Data Visualization, Technical Communication, Data Ethics, Data Visualization Software, Analytical Skills, Data Cleansing
状态：新状态：免费试用您将获得的技能: Data Modeling, Analytical Skills, Analysis, Data Management, Business Reporting, Data Manipulation, Security Awareness
状态：新状态：免费试用您将获得的技能: SPSS (Software), Correlation Analysis, Data Visualization, Descriptive Statistics, Advanced Analytics, Data Analysis, Regression Analysis, Statistical Analysis, Statistical Reporting, Data-Driven Decision-Making, Exploratory Data Analysis, Statistical Methods, Statistical Inference
状态：免费试用您将获得的技能: Generative AI, Matplotlib, Plotly, Prompt Engineering, Data Ethics, Power BI, Data Visualization, Microsoft Excel, Data Manipulation, Exploratory Data Analysis, Data Cleansing, Pandas (Python Package), Data Transformation, Excel Formulas, Pivot Tables And Charts, Data Visualization Software, Data Analysis, Microsoft Copilot, Data Presentation, Data Processing
状态：免费试用Duke University
您将获得的技能: 数据分析, 统计建模, 概率分布, 数据可视化, 回归分析, 统计资料, 探索性数据分析, 统计分析, 统计推理, 统计方法, 概率, R 程序设计, 统计假设检验, 数据分析软件, 贝叶斯统计, 抽样（统计）, 统计报告, 同行评审, 概率与统计, R（软件）
总之，以下是 10 最受欢迎的 exploratory data analysis 课程
- Python Data Analysis: Packt
- 商业探索性数据分析工具: University of Illinois Urbana-Champaign
- Transform, Analyze, and Report Data with R: Coursera
- Python for Data Analysis: Step-By-Step with Projects: Packt
- 利用 ggplot 对公共部门进行探索性数据分析: University of Michigan
- Exploratory Data Analysis & Core ML Algorithms: Packt
- AI-Powered Data Analysis with Microsoft Copilot: SkillsBooster Academy
- Data Literacy: Exploring and Visualizing Data: SAS
- Analyze Business Data Using Advanced Power BI Techniques: EDUCBA
- Analyze Advanced Data Projects Using SPSS: EDUCBA
