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Data Analysis Courses for Beginners

Beginner data analysis courses can help you learn data collection techniques, basic statistical concepts, data visualization, and interpretation of results. You can build skills in using spreadsheets for data manipulation, creating charts for visual representation, and applying descriptive statistics to summarize findings. Many courses introduce tools like Excel, Google Sheets, and data visualization software such as Tableau, showing you how to effectively analyze and present data to support decision-making.


Popular Beginner Data Analysis Courses and Certifications


  • Status: Free Trial
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    DeepLearning.AI

    Neural Networks and Deep Learning

    Skills you'll gain: Deep Learning, Artificial Neural Networks, Convolutional Neural Networks, Applied Machine Learning, Supervised Learning, Recurrent Neural Networks (RNNs), Python Programming, Linear Algebra, Calculus

    4.9
    Rating, 4.9 out of 5 stars
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    124K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, PyTorch (Machine Learning Library), Large Language Modeling, Retrieval-Augmented Generation, Transfer Learning, Model Evaluation, Computer Vision, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Vision Transformer (ViT), Keras (Neural Network Library), Supervised Learning, Generative AI Agents, Deep Learning, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    22K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: New
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    Coursera

    Product Analytics Unlocked: Metrics to Meaningful Insight

    Skills you'll gain: Data Storytelling, Dashboard, Data Pipelines, Web Analytics, Strategic Prioritization, Customer Retention, Process Analysis, Customer Analysis, Product Strategy, SQL, Data Analysis, Business Intelligence, Data Warehousing, Pandas (Python Package), Performance Metric, Statistical Analysis, Scikit Learn (Machine Learning Library), Decision Making, Resource Allocation, Python Programming

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
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    IBM

    IBM Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Autoencoders, Feature Engineering, Unsupervised Learning, Supervised Learning, Classification Algorithms, Regression Analysis, Dimensionality Reduction, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Deep Learning, Statistical Methods, Data Preprocessing, Applied Machine Learning, Data Science, Machine Learning, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    3.6K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
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    University of Michigan

    Applied Machine Learning in Python

    Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
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    8.8K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Geospatial Foundations & Python Tooling

    Skills you'll gain: Geographic Information Systems, GIS Software, Geospatial Information and Technology, Spatial Data Analysis, Spatial Analysis, Metadata Management, Query Languages, Technical Documentation, SQL, Data Validation, Global Positioning Systems, Geospatial Mapping, Data Quality, PostgreSQL, Data Management, File Management, Data Mapping, Data Analysis, Data Structures, Python Programming

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
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    IBM

    Machine Learning with Python

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Classification Algorithms, Feature Engineering

    4.7
    Rating, 4.7 out of 5 stars
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    18K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
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    D

    Duke University

    Introduction to Machine Learning

    Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Transfer Learning, Reinforcement Learning, Convolutional Neural Networks, Deep Learning, Image Analysis, Applied Machine Learning, Natural Language Processing, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Neural Networks, Supervised Learning, Unsupervised Learning, Python Programming, Computer Vision, Medical Imaging

    4.7
    Rating, 4.7 out of 5 stars
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    3.8K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    Imperial College London

    Mathematics for Machine Learning: Linear Algebra

    Skills you'll gain: Linear Algebra, NumPy, Applied Mathematics, Machine Learning Algorithms, Jupyter, Algorithms, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
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    13K reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
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    KodeKloud

    Hands-On MLOps Fundamentals for ML Engineers

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Apache Airflow, Data Pipelines, Apache Kafka, DevOps, CI/CD, Apache Spark, Pandas (Python Package), Deep Learning, Applied Machine Learning, Machine Learning, Data Governance, Supervised Learning, Flask (Web Framework), Grafana, Python Programming, Automation, Unsupervised Learning, Continuous Monitoring

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
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    University of Washington

    Machine Learning: Regression

    Skills you'll gain: Regression Analysis, Model Evaluation, Predictive Modeling, Supervised Learning, Statistical Modeling, Feature Engineering, Machine Learning, Data Preprocessing, Python Programming, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
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    5.6K reviews

    Mixed · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
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    Coursera

    Building Reliable LLM Systems

    Skills you'll gain: LLM Application, Model Evaluation, Large Language Modeling, Retrieval-Augmented Generation, Vector Databases, MLOps (Machine Learning Operations), Performance Tuning, Debugging, Performance Testing, Query Languages, SQL, Statistical Hypothesis Testing, Statistical Analysis, Artificial Intelligence and Machine Learning (AI/ML), Data-Driven Decision-Making, Python Programming, Pandas (Python Package)

    Intermediate · Course · 1 - 3 Months

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In summary, here are 10 of our most popular data analysis courses

  • Neural Networks and Deep Learning: DeepLearning.AI
  • IBM AI Engineering: IBM
  • Product Analytics Unlocked: Metrics to Meaningful Insight: Coursera
  • IBM Machine Learning: IBM
  • Applied Machine Learning in Python: University of Michigan
  • Geospatial Foundations & Python Tooling: Coursera
  • Machine Learning with Python: IBM
  • Introduction to Machine Learning: Duke University
  • Mathematics for Machine Learning: Linear Algebra: Imperial College London
  • Hands-On MLOps Fundamentals for ML Engineers: KodeKloud

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