Exploratory Data Analysis

Exploratory Data Analysis (EDA) is a statistical approach that involves visualizing and understanding the patterns, trends, and relationships within data prior to formal modeling or hypothesis testing. Coursera's EDA catalogue helps you develop a comprehensive understanding of how to summarize, visualize, and interpret various types of data. You'll learn how to use graphical and quantitative methods to gain insights into data, uncover underlying structure, extract important variables, identify outliers and anomalies, and test underlying assumptions. You'll refine your analytical thinking skills and learn to effectively communicate results through informative visualizations, preparing you for roles in data science, statistics, and analytics.
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Explore the Exploratory Data Analysis Course Catalog

  • Status: New
    Status: Free Trial

    Skills you'll gain: Unsupervised Learning, Anomaly Detection, Supervised Learning, Python Programming, Exploratory Data Analysis

  • Skills you'll gain: Data Visualization, Matplotlib, Plot (Graphics), Exploratory Data Analysis, Text Mining, Applied Machine Learning, Data Cleansing, Scikit Learn (Machine Learning Library), Pandas (Python Package), Natural Language Processing, Predictive Modeling, Machine Learning, Data Processing, Unstructured Data, Data Analysis, Machine Learning Algorithms, Data Manipulation, Python Programming, Computer Science

  • Status: Preview

    Universidade de São Paulo

    Skills you'll gain: Network Analysis, Social Network Analysis, Data Visualization, Scientific Visualization, Graph Theory, Exploratory Data Analysis, Environmental Science, Data Analysis, R Programming, Data Science, Probability Distribution

  • Status: Free Trial

    Skills you'll gain: Data Analysis, Data Collection, Workflow Management, MLOps (Machine Learning Operations), Statistical Analysis, Artificial Intelligence and Machine Learning (AI/ML), Exploratory Data Analysis, Data Cleansing, Applied Machine Learning, Predictive Modeling, Machine Learning, Data Modeling, Machine Learning Algorithms, Process Management

  • Skills you'll gain: Datamaps, Interactive Data Visualization, Heat Maps, Data Visualization, Data Visualization Software, Statistical Visualization, Data Presentation, Data Storytelling, Data Wrangling, Data Access, Correlation Analysis, Scatter Plots, Exploratory Data Analysis, Data Science, Data Analysis, Python Programming

  • Skills you'll gain: Forecasting, Predictive Modeling, Data Manipulation, Anomaly Detection, Pandas (Python Package), Exploratory Data Analysis, Data Cleansing

  • Status: Free

    Skills you'll gain: SPSS, Statistical Modeling, Analysis, Statistical Analysis, SPSS (Software), SAS (Software), Regression Analysis, Correlation Analysis, Exploratory Data Analysis, Data Analysis Software, Statistical Methods, Data Modeling, Advanced Analytics

  • Status: New
    Status: Free Trial

    Skills you'll gain: Generative AI, Supervised Learning, Generative Model Architectures, Unsupervised Learning, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Data Collection, Machine Learning Algorithms, OpenAI, Feature Engineering, Data Ethics, Dimensionality Reduction, MLOps (Machine Learning Operations), Machine Learning, Multimodal Prompts, Data Processing, Network Architecture

  • Status: Free

    Skills you'll gain: AI Personalization, Data Analysis, Generative AI, Exploratory Data Analysis, OpenAI, Data Manipulation, Prototyping, Text Mining, Pandas (Python Package), Applied Machine Learning, Interactive Data Visualization, Scientific Visualization, Python Programming, Dimensionality Reduction, NumPy

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, Responsible AI, Tensorflow, Exploratory Data Analysis, Data Quality, Machine Learning, Applied Machine Learning, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Google Cloud Platform, MLOps (Machine Learning Operations), Supervised Learning, Machine Learning Algorithms, Data Strategy, Dataflow, Predictive Modeling, Artificial Neural Networks, Performance Tuning, Data Pipelines, Deep Learning

  • Status: Preview

    Johns Hopkins University

    Skills you'll gain: Rmarkdown, Data Science, R (Software), GitHub, Version Control, Data Analysis, Big Data, R Programming, Git (Version Control System), Statistical Programming, Exploratory Data Analysis, Data Management

  • Skills you'll gain: Anomaly Detection, Jupyter, Exploratory Data Analysis, Application Deployment, Unsupervised Learning, Data Visualization, Applied Machine Learning, Machine Learning Methods, Data Presentation, Machine Learning

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    Status: AI skills
  • Status: Free Trial
    Status: AI skills
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