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    Results for "advanced statistics"

    • D

      DeepLearning.AI

      Custom Models, Layers, and Loss Functions with TensorFlow

      Skills you'll gain: Tensorflow, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Network Model, Network Architecture, API Design, Object Oriented Programming (OOP)

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.1K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Spacecraft Dynamics and Control

      Skills you'll gain: Control Systems, Vibrations, Mechanics, Torque (Physics), Linear Algebra, Numerical Analysis, Engineering Calculations, Simulations, Engineering Analysis, Physics, Mathematical Modeling, Visualization (Computer Graphics), Differential Equations, Simulation and Simulation Software, Applied Mathematics, Engineering, Verification And Validation, Advanced Mathematics, Estimation, Matlab

      4.8
      Rating, 4.8 out of 5 stars
      ·
      427 reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: Free
      Free
      S

      Stanford University

      Game Theory II: Advanced Applications

      Skills you'll gain: Game Theory, Bidding, Social Sciences, Resource Allocation, Political Sciences, Economics, Behavioral Economics, Negotiation, Mathematical Theory & Analysis, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      641 reviews

      Advanced · Course · 1 - 3 Months

    • S

      SAS

      SAS Visual Business Analytics

      Skills you'll gain: SAS (Software), Network Analysis, Trend Analysis, Data Manipulation, Data Analysis, Forecasting, Data Quality, Text Mining, Exploratory Data Analysis, Ad Hoc Reporting, Spatial Data Analysis, Data Visualization Software, Spatial Analysis, Dashboard, Time Series Analysis and Forecasting, Business Analytics, Interactive Data Visualization, Data-Driven Decision-Making, Predictive Analytics, Data Visualization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.1K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • C

      Coursera Project Network

      COVID19 Data Analysis Using Python

      Skills you'll gain: Correlation Analysis, Seaborn, Data Cleansing, Data Visualization, Statistical Analysis, Data Manipulation, Data Analysis, Exploratory Data Analysis, Pandas (Python Package), Data Integration, Infectious Diseases

      4.5
      Rating, 4.5 out of 5 stars
      ·
      2K reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      P

      Peking University

      Advanced Neurobiology I

      Skills you'll gain: Neurology, Anatomy, Molecular Biology, Biochemistry, Biology, Basic Electrical Systems, Scientific Methods, Research

      4.1
      Rating, 4.1 out of 5 stars
      ·
      621 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Probability Theory: Foundation for Data Science

      Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Statistics, Bayesian Statistics, Data Science, Statistical Analysis, Statistical Inference

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      253 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      Unilever

      Unilever Digital Marketing Analyst

      Skills you'll gain: Data Storytelling, Marketing Automation, Web Analytics, Marketing Effectiveness, Marketing Analytics, Customer Insights, Digital Marketing, Social Media Campaigns, Market Analysis, Google Analytics, Social Media Marketing, Customer Analysis, Search Engine Marketing, Marketing Strategies, Social Media Strategy, Customer experience strategy (CX), Performance Reporting, Search Engine Optimization, Predictive Analytics, MarTech

      4.7
      Rating, 4.7 out of 5 stars
      ·
      232 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      Institute for the Future

      Ready, Set, Future! Introduction to Futures Thinking

      Skills you'll gain: Forecasting, Innovation, Proactivity, Strategic Thinking, Creative Thinking, Optimism, Systems Thinking, Cognitive flexibility, Trend Analysis, Professional Development, Adaptability, Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.3K reviews

      Beginner · Course · 1 - 4 Weeks

    • F

      Fractal Analytics

      Fractal Data Science

      Skills you'll gain: Data Storytelling, Decision Making, Critical Thinking, Database Design, Data Manipulation, Data Presentation, Power BI, Data Visualization, Exploratory Data Analysis, Feature Engineering, Interactive Data Visualization, Data Analysis Expressions (DAX), Human Centered Design, Storyboarding, SQL, Applied Machine Learning, Problem Solving, Data Modeling, Machine Learning, Machine Learning Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      337 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      Universidad Austral

      Pilares de Marketing Digital

      Skills you'll gain: Digital Marketing, Customer Relationship Management, Social Media, Digital Media Strategy, Social Media Strategy, Marketing Analytics, Marketing Strategies, Online Advertising, Web Analytics, Marketing, Sales Process, Business Analytics, Search Engine Marketing, Email Marketing, Search Engine Optimization, Content Performance Analysis, Target Audience

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      Imperial College London

      Epidemiology for Public Health

      Skills you'll gain: Epidemiology, Clinical Trials, Research Design, Clinical Research, Public Health, Preventative Care, Data Collection, Biostatistics, Research Methodologies, Program Evaluation, Research, General Medical Tests and Procedures, Probability & Statistics, Risk Analysis, Quantitative Research, Health Policy, Correlation Analysis, Science and Research, Statistical Methods, Statistical Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    advanced linear models for data science 2: statistical linear models
    1…313233…262

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

    • Custom Models, Layers, and Loss Functions with TensorFlow: DeepLearning.AI
    • Spacecraft Dynamics and Control: University of Colorado Boulder
    • Game Theory II: Advanced Applications: Stanford University
    • SAS Visual Business Analytics: SAS
    • COVID19 Data Analysis Using Python: Coursera Project Network
    • Advanced Neurobiology I: Peking University
    • Probability Theory: Foundation for Data Science: University of Colorado Boulder
    • Unilever Digital Marketing Analyst: Unilever
    • Ready, Set, Future! Introduction to Futures Thinking: Institute for the Future
    • Fractal Data Science: Fractal Analytics

    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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