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    Results for "advanced statistics"

    • U

      University of London

      Introduction to Computer Security

      Skills you'll gain: Linux, Computer Systems, Command-Line Interface, Cybersecurity, Computer Architecture, Network Security, Vulnerability Assessments, Hardware Architecture, Application Security, Threat Detection, Authorization (Computing), Network Protocols, Virtual Private Networks (VPN), Operating Systems, Authentications, Network Monitoring, Network Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      31 reviews

      Beginner · Course · 1 - 4 Weeks

    • S

      SkillUp EdTech

      ASQ-Certified Six Sigma Yellow Belt Exam Prep Specialization

      Skills you'll gain: Process Mapping, Root Cause Analysis, Lean Six Sigma, Lean Methodologies, Correlation Analysis, Process Improvement, Quality Improvement, Lean Manufacturing, Six Sigma Methodology, Regression Analysis, Statistical Methods, Statistics, Continuous Improvement Process, Data Collection, Descriptive Statistics, Statistical Hypothesis Testing, Probability & Statistics, Process Optimization, Process Management, Risk Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      15 reviews

      Beginner · Specialization · 3 - 6 Months

    • A

      Alberta Machine Intelligence Institute

      Data for Machine Learning

      Skills you'll gain: Feature Engineering, Data Quality, Data Processing, Supervised Learning, Data Validation, Data Cleansing, Data Transformation, Verification And Validation, Applied Machine Learning, Machine Learning, Unsupervised Learning, Machine Learning Algorithms, Exploratory Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      98 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Cervical Cancer Risk Prediction Using Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Data Analysis, Statistical Analysis, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Predictive Modeling, Matplotlib, Data Import/Export, Pandas (Python Package), Applied Machine Learning, Data Visualization Software, NumPy, Data Manipulation, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      38 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      L

      Ludwig-Maximilians-Universität München (LMU)

      Research kitchen

      Skills you'll gain: Innovation, Organizational Structure, Competitive Analysis, Business Strategy, Organizational Strategy, Research, Strategic Thinking, Business Research, Strategic Decision-Making, Market Dynamics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      151 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Create an A/B web page marketing test with Google Optimize

      Skills you'll gain: A/B Testing, Google Analytics, Web Analytics, User Experience, Web Content, Target Audience, Marketing Effectiveness, Goal Setting, Content Development and Management

      4.4
      Rating, 4.4 out of 5 stars
      ·
      107 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • E

      Emory University

      Managing Uncertainty in Marketing Analytics

      Skills you'll gain: Probability Distribution, Marketing Analytics, Probability, Microsoft Excel, Statistics, Statistical Modeling, Forecasting, Decision Making, Simulation and Simulation Software, Insurance and Warranty Claims Processing, Risk Analysis

      4.3
      Rating, 4.3 out of 5 stars
      ·
      68 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Codio

      Advanced Django: Introduction to Django Rest Framework

      Skills you'll gain: Django (Web Framework), Postman API Platform, Restful API, Data Validation, Authentications, Authorization (Computing), Application Programming Interface (API), API Design, JSON, Object-Relational Mapping, Model View Controller

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49 reviews

      Advanced · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Machine Learning with PySpark: Customer Churn Analysis

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Analysis, PySpark, Data Processing, Data Cleansing, Data Transformation, Apache Spark, Data-Driven Decision-Making, Decision Tree Learning, Predictive Modeling, Predictive Analytics, Applied Machine Learning, Application Deployment, Machine Learning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • A

      Arizona State University

      Random Models, Nested and Split-plot Designs

      Skills you'll gain: Statistical Analysis, Regression Analysis, Statistical Modeling, Data Analysis, Statistical Methods, Data Transformation, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      34 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Advanced Deep Learning Methods for Healthcare

      Skills you'll gain: Deep Learning, Generative AI, Applied Machine Learning, Machine Learning Methods, Image Analysis, Graph Theory, Network Analysis, Artificial Neural Networks, Health Informatics, Machine Learning Software, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Predictive Modeling, Natural Language Processing, Data Synthesis, Python Programming

      3.4
      Rating, 3.4 out of 5 stars
      ·
      13 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: New
      New
      J

      Johns Hopkins University

      Advanced Network Security and Analysis

      Skills you'll gain: Email Security, Mobile Security, Network Security, Open Web Application Security Project (OWASP), Intrusion Detection and Prevention, Threat Detection, TCP/IP, Network Analysis, Network Protocols, Cybersecurity, Application Security, Wireless Networks, Splunk, Information Privacy

      Intermediate · Course · 1 - 3 Months

    Searches related to advanced statistics

    advanced statistics for data science
    advanced quantitative statistics with excel
    advanced statistical analysis and tools
    advanced statistical techniques for data science
    seaborn: visualizing basics to advanced statistical plots
    advanced probability and statistical methods
    statistical analysis and advanced techniques
    advanced linear models for data science 2: statistical linear models
    1…106107108…265

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

    • Introduction to Computer Security: University of London
    • ASQ-Certified Six Sigma Yellow Belt Exam Prep Specialization: SkillUp EdTech
    • Data for Machine Learning: Alberta Machine Intelligence Institute
    • Cervical Cancer Risk Prediction Using Machine Learning: Coursera Project Network
    • Research kitchen: Ludwig-Maximilians-Universität München (LMU)
    • Create an A/B web page marketing test with Google Optimize: Coursera Project Network
    • Managing Uncertainty in Marketing Analytics: Emory University
    • Advanced Django: Introduction to Django Rest Framework: Codio
    • Machine Learning with PySpark: Customer Churn Analysis: Coursera Project Network
    • Random Models, Nested and Split-plot Designs: Arizona State University

    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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