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    Results for "statistical inference"

    • DeepLearning.AI

      Нейронные сети и глубокое обучение

      Skills you'll gain: Deep Learning, Artificial Neural Networks, Supervised Learning, Artificial Intelligence, Machine Learning, Python Programming, Network Architecture, NumPy

      3.9
      Rating, 3.9 out of 5 stars
      ·
      13 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      University of Michigan

      Wearable Technologies and Sports Analytics

      Skills you'll gain: Kinesiology, Injury Prevention, Analytics, Data Analysis, Physical Therapy, Applied Machine Learning, Vital Signs, Health Technology, Machine Learning, Stress Management, Data Collection, Data Validation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      39 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial

      University of Michigan

      Data-Oriented Python Programming and Debugging

      Skills you'll gain: Debugging, NumPy, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Pandas (Python Package), Data Structures, Probability & Statistics, Statistical Methods, Probability, Statistics, Probability Distribution, Statistical Analysis, Data Analysis, Program Development, Large Language Modeling, Data Manipulation, Programming Principles, Computer Programming, Python Programming

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New

      University of Illinois Urbana-Champaign

      Advanced Topics in Artificial Intelligence

      Skills you'll gain: Automation, Artificial Intelligence, Data Ethics, Advanced Analytics, Business Process Automation, Artificial Intelligence and Machine Learning (AI/ML), Robotic Process Automation, Data Infrastructure, Cloud Computing Architecture, Predictive Analytics, Data-Driven Decision-Making, Machine Learning, Emerging Technologies, Cloud Computing, Internet Of Things, Computer Hardware

      Build toward a degree

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      Duke University

      Developing Explainable AI (XAI)

      Skills you'll gain: Data Ethics, Generative AI, Artificial Intelligence, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data-Driven Decision-Making, Information Privacy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      22 reviews

      Intermediate · Course · 1 - 4 Weeks

    • National Taiwan University

      用 Python 做商管程式設計(三)(Programming for Business Computing in Python (3))

      Skills you'll gain: Statistical Visualization, Matplotlib, Web Scraping, Business Logic, Machine Learning, Operational Analysis, Business Analytics, Python Programming, Programming Principles, Business Economics, User Interface (UI) Design, Computational Thinking, UI Components, Object Oriented Programming (OOP), Data Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      161 reviews

      Mixed · Course · 1 - 3 Months

    • Meta

      GenAI in Data Analytics

      Skills you'll gain: Generative AI, Business Analytics, Analytics, Data Quality, Business Analysis, Data Ethics, Prompt Engineering, Process Optimization, OpenAI, Artificial Intelligence, Data Analysis, ChatGPT, Machine Learning, Deep Learning, Natural Language Processing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      32 reviews

      Beginner · Course · 1 - 4 Weeks

    • Universidade de São Paulo

      Redes Ecológicas

      Skills you'll gain: Network Analysis, Data Visualization, Scientific Visualization, Analysis, Graph Theory, Exploratory Data Analysis, Environmental Science, R Programming, Data Analysis Software, Mathematical Modeling, Data Manipulation

      5
      Rating, 5 out of 5 stars
      ·
      35 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free

      École normale supérieure

      Cartographie thématique

      Skills you'll gain: Statistical Visualization, Geospatial Mapping, Data Mapping, Geographic Information Systems, Graphic and Visual Design, Data Presentation, Graphics Software, Quantitative Research, Color Theory

      4.6
      Rating, 4.6 out of 5 stars
      ·
      82 reviews

      Beginner · Course · 1 - 3 Months

    • Duke University

      GenAI Basics - How LLMs Work

      Skills you'll gain: Large Language Modeling, Generative AI, Natural Language Processing, Machine Learning, Artificial Intelligence, Data Processing, Data Science, Data Modeling

      3.9
      Rating, 3.9 out of 5 stars
      ·
      24 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial

      Yonsei University

      Financial Analysis for Startups

      Skills you'll gain: Financial Analysis, Financial Statements, Financial Modeling, Financial Forecasting, Income Statement, Balance Sheet, Financial Planning, Cash Flows, Business Valuation, Asset Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      112 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      University of Michigan

      Introduction to Machine Learning in Sports Analytics

      Skills you'll gain: Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Statistical Machine Learning, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Analytics, Machine Learning, Data Analysis, Random Forest Algorithm

      4.8
      Rating, 4.8 out of 5 stars
      ·
      24 reviews

      Intermediate · Course · 1 - 4 Weeks

    Searches related to statistical inference

    improving your statistical inferences
    data science foundations: statistical inference
    statistical inference for estimation in data science
    statistical inference and hypothesis testing in data science applications
    1…727374…151

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

    • Нейронные сети и глубокое обучение: DeepLearning.AI
    • Wearable Technologies and Sports Analytics: University of Michigan
    • Data-Oriented Python Programming and Debugging: University of Michigan
    • Advanced Topics in Artificial Intelligence: University of Illinois Urbana-Champaign
    • Developing Explainable AI (XAI): Duke University
    • 用 Python 做商管程式設計(三)(Programming for Business Computing in Python (3)): National Taiwan University
    • GenAI in Data Analytics: Meta
    • Redes Ecológicas: Universidade de São Paulo
    • Cartographie thématique: École normale supérieure
    • GenAI Basics - How LLMs Work: Duke University

    Skills you can learn in Probability And Statistics

    R Programming (19)
    Inference (16)
    Linear Regression (12)
    Statistical Analysis (12)
    Statistical Inference (11)
    Regression Analysis (10)
    Biostatistics (9)
    Bayesian (7)
    Logistic Regression (7)
    Probability Distribution (7)
    Bayesian Statistics (6)
    Medical Statistics (6)

    Frequently Asked Questions about Statistical Inference

    Statistical inference is the process whereby you can draw conclusions about a population based on random samples of that population and the statistics that you draw from those samples. When you rely on statistical inference, you take what you've observed about your samples of that population and apply them to the group as a whole. Applying statistical inference allows you to take what you know about the population as well as what's uncertain to make statements about the entire population based on your analysis.‎

    If you want to learn about a certain population—whether they're customers or fellow employees—you can use statistical inference to draw conclusions about that population based on your analysis of data about them. You can't always survey or test an entire population to gain insight, but you can sample the population and make educated assumptions based on the data. Understanding statistical inference allows you to take that data and use it to draw conclusions that make sense and prove true.‎

    Statistical inference has plenty of benefits for different business sectors. Statisticians and data analysts use this method often to draw conclusions based on samples of populations. If you're in sales or product development, you can use statistical inference to determine which brands or products are popular with your customers or clients. Scientists use statistical inference to test hypotheses and draw conclusions when it's impossible for them to test or sample an entire population. You can apply statistical inference to analyze the data from surveys of any population that you sample.‎

    Online courses on Coursera give you both a grasp of the concepts of statistical inference and practical applications. You'll learn from the best instructors in the academic world, and you can learn at a pace and schedule that best suits your schedule and lifestyle. When you finish our courses, you'll know how to use statistical inference in your career, which will give you an advantage whether you're trying to get better at your current job or whether you're looking to make a career change.‎

    Online Statistical Inference courses offer a convenient and flexible way to enhance your knowledge or learn new Statistical Inference skills. Choose from a wide range of Statistical Inference courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Statistical Inference, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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