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    Results for "advanced statistics"

    • S

      Siemens

      Siemens NX Mastery: Advanced Design & Applications

      Skills you'll gain: Assembly Drawing, Finite Element Methods, Mechanical Design, Drafting and Engineering Design, 3D Modeling, Computer-Aided Design, Technical Design, Engineering Software, Simulations

      4.6
      Rating, 4.6 out of 5 stars
      ·
      22 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of California, Davis

      GIS Applications Across Industries

      Skills you'll gain: ArcGIS, Geographic Information Systems, Public Health, Land Management, Geospatial Mapping, Spatial Analysis, Community Health, Emergency Response, Environmental Science, Natural Resource Management, Business Development, Market Analysis, Risk Mitigation, Supply Chain

      4.6
      Rating, 4.6 out of 5 stars
      ·
      72 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      SQL for Data Science with R

      Skills you'll gain: Relational Databases, Database Design, SQL, Database Management, Databases, Query Languages, Data Analysis, Exploratory Data Analysis, R Programming, Data Manipulation, Data Modeling, Data Access

      4.3
      Rating, 4.3 out of 5 stars
      ·
      175 reviews

      Beginner · Course · 1 - 3 Months

    • T

      The Hong Kong University of Science and Technology

      Understanding Modern Physics II: Quantum Mechanics and Atoms

      Skills you'll gain: Physics, Laboratory Experience, Experimentation, Advanced Mathematics, Physical Science, Mathematical Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      54 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Tools for Exploratory Data Analysis in Business

      Skills you'll gain: Extract, Transform, Load, Alteryx, Data Presentation, Interactive Data Visualization, Business Analytics, Statistical Visualization, Data Visualization Software, Power BI, Exploratory Data Analysis, Analytical Skills, Business Intelligence, Ggplot2, Data Processing, Data Analysis, Data Transformation, R Programming, Data Manipulation

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      50 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Logistic Regression with NumPy and Python

      Skills you'll gain: Matplotlib, Data Visualization, Seaborn, Exploratory Data Analysis, NumPy, Data Analysis, Jupyter, Machine Learning, Python Programming, Supervised Learning, Regression Analysis, Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      393 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      U

      Universitat Autònoma de Barcelona

      Pre-Calculus

      Skills you'll gain: Trigonometry, Integral Calculus, Calculus, Arithmetic, Advanced Mathematics, Algebra, Geometry, Applied Mathematics, Graphing, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      568 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Michigan

      Digital Twins

      Skills you'll gain: Manufacturing Operations, Production Planning, Digital Transformation, Technology Strategies, Business Modeling, Technology Roadmaps, Business Transformation, Product Lifecycle Management, Internet Of Things, Simulation and Simulation Software, Emerging Technologies, Real Time Data, Trend Analysis, Risk Analysis, Systems Integration

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92 reviews

      Beginner · Course · 1 - 4 Weeks

    • T

      Tufts University

      Hypothesis Testing with Python and Excel

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Microsoft Excel, Quantitative Research, Probability & Statistics, Statistical Analysis, Analytical Skills, Business Analytics, Python Programming

      4.2
      Rating, 4.2 out of 5 stars
      ·
      23 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Llama for Python Programmers

      Skills you'll gain: Large Language Modeling, Prompt Engineering, Application Development, Generative AI, Python Programming, Natural Language Processing, Open Source Technology

      4.7
      Rating, 4.7 out of 5 stars
      ·
      15 reviews

      Intermediate · Course · 1 - 4 Weeks

    • T

      Talend

      Talend Data Integration Certification Preparation training

      Skills you'll gain: Metadata Management, Data Manipulation, Data Integration, Extract, Transform, Load, Database Management Systems, Data Transformation, Data Warehousing, Data Pipelines, Data Validation, Version Control

      4.6
      Rating, 4.6 out of 5 stars
      ·
      67 reviews

      Intermediate · Course · 1 - 4 Weeks

    • P

      Packt

      AutoCAD 2023 Masterclass - Produce Amazing Site Plans

      Skills you'll gain: AutoCAD, Architectural Drawing, Technical Drawing, Computer-Aided Design, Drafting and Engineering Design, Engineering Drawings, Architectural Design, Data Import/Export

      4.4
      Rating, 4.4 out of 5 stars
      ·
      36 reviews

      Beginner · Course · 3 - 6 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
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    In summary, here are 10 of our most popular advanced statistics courses

    • Siemens NX Mastery: Advanced Design & Applications: Siemens
    • GIS Applications Across Industries: University of California, Davis
    • SQL for Data Science with R: IBM
    • Understanding Modern Physics II: Quantum Mechanics and Atoms: The Hong Kong University of Science and Technology
    • Tools for Exploratory Data Analysis in Business: University of Illinois Urbana-Champaign
    • Logistic Regression with NumPy and Python: Coursera Project Network
    • Pre-Calculus: Universitat Autònoma de Barcelona
    • Digital Twins: University of Michigan
    • Hypothesis Testing with Python and Excel: Tufts University
    • Llama for Python Programmers: University of Michigan

    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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