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  • Statistical Analysis

Statistical Analysis Courses

Statistical analysis courses can help you learn data collection methods, hypothesis testing, regression analysis, and data visualization techniques. You can build skills in interpreting results, making predictions, and drawing conclusions from data sets. Many courses introduce tools such as R, Python, and Excel, that support performing statistical computations and creating visual representations of data.


Popular Statistical Analysis Courses and Certifications


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

    Meta

    Meta Data Analyst

    Skills you'll gain: Data Storytelling, Data Presentation, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Visualization, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Analysis, Data Visualization Software, Spreadsheet Software, Exploratory Data Analysis, SQL, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    1.8K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Pennsylvania

    Fundamentals of Quantitative Modeling

    Skills you'll gain: Business Modeling, Mathematical Modeling, Regression Analysis, Statistical Modeling, Risk Analysis, Forecasting, Predictive Analytics, Business Analytics, Simulation and Simulation Software, Probability, Logistic Regression, Vocabulary

    4.6
    Rating, 4.6 out of 5 stars
    ·
    9.4K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of London

    Applied Mathematical Methods for Computing

    Skills you'll gain: Combinatorics, Probability & Statistics, Data Analysis, Advanced Mathematics, Linear Algebra, Mathematics and Mathematical Modeling, Mathematical Theory & Analysis, Applied Mathematics, Statistics, Analysis, Statistical Analysis, Probability, Algorithms, Algebra

    Beginner · Course · 1 - 4 Weeks

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

    Meta

    Meta Marketing Analytics

    Skills you'll gain: Data Storytelling, Data Presentation, Business Metrics, Key Performance Indicators (KPIs), Marketing Analytics, Bayesian Statistics, Data Visualization, Descriptive Statistics, Marketing Effectiveness, Statistical Hypothesis Testing, Target Audience, Marketing Strategies, Data Cleansing, Pandas (Python Package), Data Analysis, Data Visualization Software, A/B Testing, Data Collection, Marketing, Interviewing Skills

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    4.3K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Generative AI for Software Developers

    Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, Data Ethics, Software Design, Software Architecture, Continuous Integration, Software Design Patterns, Software Development, LLM Application, Artificial Intelligence and Machine Learning (AI/ML), AI Workflows, Application Security, Software Engineering, Deep Learning, Debugging, Augmented and Virtual Reality (AR/VR), DevSecOps, Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    12K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Agile Project Management

    Skills you'll gain: Agile Project Management, Backlogs, Agile Methodology, User Story, Sprint Planning, Agile Product Development, Product Roadmaps, Sprint Retrospectives, Kanban Principles, Coaching, Team Management, Organizational Change, Prioritization, Problem Solving, Influencing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    15K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Structuring Machine Learning Projects

    Skills you'll gain: Transfer Learning, Deep Learning, Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Debugging, AI Product Strategy, Model Evaluation, Data-Driven Decision-Making, Performance Tuning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    50K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Predictive Modeling, Supervised Learning, Bayesian Statistics, Logistic Regression, Statistical Modeling, Artificial Intelligence, Data Preprocessing, Deep Learning, Data Mining, Decision Tree Learning, Computer Vision, Statistical Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    16K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Introduction to Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Classification Algorithms, Regression Analysis, Dimensionality Reduction, Statistical Methods, Data Preprocessing, Applied Machine Learning, Model Evaluation, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Access, Anomaly Detection, Logistic Regression, Scikit Learn (Machine Learning Library), Machine Learning, Machine Learning Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.4K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives

    4.6
    Rating, 4.6 out of 5 stars
    ·
    15K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Virginia

    Leading the Modern Day Business

    Skills you'll gain: Design Thinking, Digital Transformation, Creative Problem-Solving, New Product Development, Ideation, Business Transformation, Product Management, Technology Strategies, Innovation, Creativity, Product Lifecycle Management, Strategic Thinking, Product Improvement, Case Studies, Information Technology, Business Strategy, Business Analysis, Leadership and Management, Marketing, Storytelling

    4.7
    Rating, 4.7 out of 5 stars
    ·
    21K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    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
    ·
    22K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

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

  • Meta Data Analyst: Meta
  • Fundamentals of Quantitative Modeling: University of Pennsylvania
  • Applied Mathematical Methods for Computing: University of London
  • Meta Marketing Analytics: Meta
  • Generative AI for Software Developers: IBM
  • Agile Project Management: Google
  • Structuring Machine Learning Projects: DeepLearning.AI
  • Machine Learning: University of Washington
  • IBM Introduction to Machine Learning: IBM
  • Mathematics for Machine Learning: Imperial College London

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