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    Results for "advanced statistics"

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      IBM

      Generative AI for Data Scientists

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, Exploratory Data Analysis, Data Ethics, OpenAI, Feature Engineering, Predictive Modeling, Large Language Modeling, Artificial Intelligence, Data Storytelling, Program Development, Data Modeling, Data Presentation, Predictive Analytics, Data Synthesis, Data Analysis, Data Cleansing, Data Visualization Software, Image Analysis

      4.7
      Rating, 4.7 out of 5 stars
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      7K reviews

      Intermediate · Specialization · 1 - 3 Months

    • U

      University of Zurich

      An Intuitive Introduction to Probability

      Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Descriptive Statistics, Applied Mathematics, Statistical Methods, Risk Analysis, Finance

      4.8
      Rating, 4.8 out of 5 stars
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      1.9K reviews

      Beginner · Course · 1 - 3 Months

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      IBM

      IBM Business Intelligence (BI) Analyst

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Database Design, MySQL, Presentations, Descriptive Statistics, Extract, Transform, Load, Business Intelligence, IBM DB2, Tableau Software, Relational Databases, Star Schema, Data Visualization Software, Interactive Data Visualization, Regression Analysis, Data-Driven Decision-Making, Excel Formulas, Microsoft Excel

      4.7
      Rating, 4.7 out of 5 stars
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      14K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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      Free Trial
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      Johns Hopkins University

      Statistical Inference

      Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability & Statistics, Probability, Bayesian Statistics, Statistical Methods, Statistical Modeling, Statistical Analysis, Probability Distribution, Sampling (Statistics), Sample Size Determination, Data Analysis

      4.2
      Rating, 4.2 out of 5 stars
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      4.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • T

      The University of Sydney

      Introduction to Advanced Calculus

      Skills you'll gain: Advanced Mathematics, Integral Calculus, Calculus, Mathematical Theory & Analysis, Differential Equations, Applied Mathematics, Engineering Calculations, Mathematical Modeling, Linear Algebra, Physics, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
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      12 reviews

      Intermediate · Course · 1 - 4 Weeks

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      IBM

      Data Analysis and Visualization Foundations

      Skills you'll gain: Data Storytelling, Big Data, Data Visualization Software, Data Analysis, Dashboard, IBM Cognos Analytics, Statistical Analysis, Data Mining, Apache Hadoop, Tree Maps, Excel Formulas, Apache Hive, Microsoft Excel, Data Warehousing, Data Quality, Data Cleansing, Scatter Plots, Apache Spark, Pivot Tables And Charts, Data Import/Export

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      4.7
      Rating, 4.7 out of 5 stars
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      28K reviews

      Beginner · Specialization · 3 - 6 Months

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      Multiple educators

      Data Science Foundations

      Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Correlation Analysis, Web Scraping, NumPy, Python Programming, Probability & Statistics, Data Structures, Predictive Modeling, Big Data, Data Visualization Software, Data Collection, Data Science, Machine Learning Algorithms, Unsupervised Learning

      4.6
      Rating, 4.6 out of 5 stars
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      113K reviews

      Beginner · Specialization · 3 - 6 Months

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      IBM

      BI Foundations with SQL, ETL and Data Warehousing

      Skills you'll gain: Data Warehousing, Extract, Transform, Load, Apache Airflow, Linux Commands, SQL, IBM Cognos Analytics, Data Pipelines, Apache Kafka, Bash (Scripting Language), Shell Script, Dashboard, File Management, Star Schema, Unix Shell, IBM DB2, Business Intelligence, Interactive Data Visualization, Relational Databases, Stored Procedure, Databases

      4.6
      Rating, 4.6 out of 5 stars
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      24K reviews

      Beginner · Specialization · 3 - 6 Months

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      DeepLearning.AI

      Advanced Learning Algorithms

      Skills you'll gain: Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Performance Tuning

      4.9
      Rating, 4.9 out of 5 stars
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      7.9K reviews

      Beginner · Course · 1 - 4 Weeks

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      IBM

      Data Science Fundamentals with Python and SQL

      Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Statistical Hypothesis Testing, Web Scraping, Relational Databases, Stored Procedure, Python Programming, Data Structures, Databases, Data Science, GitHub

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      4.6
      Rating, 4.6 out of 5 stars
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      72K reviews

      Beginner · Specialization · 3 - 6 Months

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      DeepLearning.AI

      DeepLearning.AI TensorFlow Developer

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Time Series Analysis and Forecasting, Deep Learning, Artificial Neural Networks, Generative AI, Applied Machine Learning, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Text Mining, Forecasting, Data Processing, Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
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      25K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

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      IBM

      Data Engineering Foundations

      Skills you'll gain: Web Scraping, Database Design, SQL, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Jupyter, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Manipulation, Stored Procedure, Python Programming, Data Structures, Databases

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    1…789…270

    In summary, here are 10 of our most popular advanced statistics courses

    • Generative AI for Data Scientists: IBM
    • An Intuitive Introduction to Probability: University of Zurich
    • IBM Business Intelligence (BI) Analyst: IBM
    • Statistical Inference: Johns Hopkins University
    • Introduction to Advanced Calculus: The University of Sydney
    • Data Analysis and Visualization Foundations: IBM
    • Data Science Foundations: IBM
    • BI Foundations with SQL, ETL and Data Warehousing: IBM
    • Advanced Learning Algorithms: DeepLearning.AI
    • Data Science Fundamentals with Python and SQL: IBM

    Frequently Asked Questions about Advanced Statistics

    Advanced statistics are the mathematical tools used to discover and explore complex relationships between different variables in large datasets. In contrast to basic statistics such as average and analysis of variance (ANOVA) that simply describe the characteristics of a dataset, advanced statistical approaches often seek to make predictions about the world. This requires the use of more sophisticated statistical inference tools, such as generalized linear models for regression analysis capable of establishing how multiple interrelated factors may impact projected outcomes.

    These advanced statistical methods are increasingly important in the field of data science, which is tasked with uncovering important business insights and developing predictive models from diverse big data-scale datasets. These techniques are also especially important for the proper training and use of machine learning algorithms. As in data science and machine learning more generally, R programming and Python programming skills are typically relied upon to conduct these advanced statistical analyses.‎

    Advanced statistics skills are essential for work in data science, machine learning, and artificial intelligence (AI), as statistical approaches are at the heart of the learning algorithms that make these applications possible. An understanding of statistics is likewise important for professionals in finance, healthcare, and other industries that are increasingly making use of machine learning and AI, as they increasingly need to work closely with data scientists to ensure that these powerful techniques are developed to solve the right business problems.

    Those wishing to delve deeper into advanced statistical methods and help develop new mathematical approaches in the field may pursue a master’s or even a PhD in statistics. These experts work in academia, government, or at private sector companies involved in scientific or engineering research. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160, and this specialized career path is expected to be in high demand due to expanding opportunities to use statistics to navigate our data-rich world.‎

    Certainly. Coursera offers a variety of courses in advanced statistics as well as their applications in the context of fields like data science and machine learning. In fact, coursework in statistics is often a prerequisite for data science classes. Regardless of your level of expertise and needs in these areas, Coursera enables you to learn remotely from top-ranked schools like the University of Michigan, Johns Hopkins University, and Duke University. And, since you can view course materials and complete coursework on a flexible schedule, there’s an exceedingly high probability that you can fit online learning about advanced statistics into your existing school or work life.‎

    You need to have strong math skills, especially in basic calculus, linear algebra, and statistics before starting to learn advanced statistics. It's important that you have strong technical skills and are very comfortable on the computer, strong analytical skills, and the ability to carefully examine and question data that is presented to you so that you can organize and draw conclusions from it. For learning some concepts in advanced statistics, you'll need to have experience using the R statistical software package and understand Bayesian estimation, principles of maximum-likelihood estimation, and calculus-based probability.‎

    People who enjoy mathematics are best suited for roles in advanced statistics, especially those who enjoy concepts like probability, linear models, and statistics and how they relate to data science. They can quickly grasp and apply complex technical concepts as well. Those who enjoy testing hypotheses and figuring out uncertain outcomes based on probability are also well suited for roles in advanced statistics. Also, people who have wide-ranging computer skills, the ability to communicate their statistical findings in plain language, problem-solving and analytical skills, and teamwork and collaborative skills are best suited for roles involving advanced statistics.‎

    If you're aspiring to be a biostatistician or data scientist, learning advanced statistics is probably right for you. If you're interested in machine learning and the development of data products, you may also find learning advanced statistics is right for you. People who want to have a career as a statistician, statistical epidemiologist, sports analyst, actuary, market researcher, or investment analyst may also find learning advanced statistics to be the right choice. And if you need to understand how to transform complex sets of data into practical applications, learning advanced statistics is right for you.‎

    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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