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    • Applied Statistics

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    1046 results for "applied statistics"

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      University of Pennsylvania

      AI For Business

      Skills you'll gain: Machine Learning, Entrepreneurship, Leadership and Management, Strategy and Operations, Machine Learning Algorithms, Finance, Data Management, Theoretical Computer Science, Applied Machine Learning, Data Analysis, Business Analysis, Human Resources, Marketing, Artificial Neural Networks, Deep Learning, Computational Thinking, Computer Programming, Accounting, Algorithms, People Management, Regulations and Compliance, Sales, Big Data, Data Mining, Data Warehousing, Feature Engineering, Natural Language Processing, Reinforcement Learning, Audit, BlockChain, Business Transformation, Clinical Data Management, Customer Analysis, Customer Relationship Management, Customer Success, Database Administration, Databases, Decision Making, Financial Analysis, Innovation, Research and Design, Security Engineering, Software Security, Strategy

      4.6

      (122 reviews)

      Beginner · Specialization · 3-6 Months

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      University of Michigan

      Python 3 Programming

      Skills you'll gain: Computer Programming, Python Programming, Computer Science, Statistical Programming, Algorithms, Other Programming Languages, Algebra, Communication, Computer Programming Tools, Journalism, Mathematics, Programming Principles, Software Engineering, Theoretical Computer Science

      4.7

      (20.2k reviews)

      Beginner · Specialization · 3-6 Months

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      Macquarie University

      Influencing: Storytelling, Change Management and Governance

      Skills you'll gain: Leadership and Management, Communication, Marketing, Strategy and Operations, Entrepreneurship, Human Resources, Negotiation, Sales, Change Management, Business Psychology, Conflict Management, Influencing, Risk Management, Organizational Development, Business Communication, Business Process Management, Culture, Business Analysis, Critical Thinking, Data Analysis, Decision Making, Emotional Intelligence, Leadership Development, Probability & Statistics, Research and Design, Statistical Tests, Storytelling

      4.8

      (3.1k reviews)

      Beginner · Specialization · 3-6 Months

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      DeepLearning.AI

      Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

      Skills you'll gain: Machine Learning, Tensorflow, Computer Vision, Deep Learning, Artificial Neural Networks, Computer Programming, Python Programming, Statistical Programming, Applied Machine Learning, Programming Principles, Computer Graphic Techniques, Computer Graphics, Machine Learning Algorithms, Machine Learning Software

      4.7

      (18.2k reviews)

      Intermediate · Course · 1-4 Weeks

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      DeepLearning.AI

      Convolutional Neural Networks

      Skills you'll gain: Artificial Neural Networks, Computer Vision, Deep Learning, Machine Learning, Statistical Programming, Python Programming, Applied Machine Learning, Linear Algebra, Machine Learning Algorithms, Machine Learning Software, Statistical Machine Learning, Dimensionality Reduction, Feature Engineering, Computer Programming, Tensorflow, Computer Architecture, Computer Networking, Network Architecture, Computer Graphic Techniques, Computer Graphics, Data Visualization

      4.9

      (41.2k reviews)

      Intermediate · Course · 1-4 Weeks

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      Google Cloud

      Creating Business Value with Data and Looker

      Skills you'll gain: Business Analysis, Data Visualization, Data Visualization Software, Looker (Software), Cloud Computing, Data Management, Applied Machine Learning, Business Intelligence, Cloud Storage, Data Warehousing, Databases, Machine Learning, Application Development, Computer Programming, Computer Programming Tools, Data Analysis, Programming Principles, Software Engineering, Software Engineering Tools

      4.7

      (873 reviews)

      Intermediate · Specialization · 3-6 Months

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      DeepLearning.AI

      Structuring Machine Learning Projects

      Skills you'll gain: Applied Machine Learning, Business Psychology, Deep Learning, Entrepreneurship, Leadership and Management, Machine Learning, Marketing, Project Management, Sales, Strategy, Strategy and Operations, Computer Vision, Decision Making, Artificial Neural Networks, Machine Learning Algorithms

      4.8

      (48.9k reviews)

      Beginner · Course · 1-4 Weeks

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      Duke University

      Python, Bash and SQL Essentials for Data Engineering

      Skills you'll gain: Computer Programming, Statistical Programming, Python Programming, Data Management, Theoretical Computer Science, Cloud Computing, Databases, Software Engineering, Computer Programming Tools, Human Computer Interaction, Software Architecture, User Experience, Operating Systems, Amazon Web Services, Linux, Extract, Transform, Load, Data Structures, SQL, Cloud Platforms, Apache, Application Development, Big Data, Data Analysis, Data Engineering, DevOps, Programming Principles, Software Engineering Tools, Database Administration, Database Application, Applied Machine Learning, Cloud Applications, Cloud Engineering, Machine Learning, Machine Learning Algorithms, Systems Design, Data Mining

      4.5

      (155 reviews)

      Beginner · Specialization · 3-6 Months

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      Deep Teaching Solutions

      Uncommon Sense Teaching

      Skills you'll gain: Business Psychology, Entrepreneurship, Human Learning, Human Resources, Leadership and Management, People Development, Applied Machine Learning, Leadership Development, Machine Learning, Project Management, Strategy and Operations, Algebra, Creativity, Mathematics, Research and Design

      4.9

      (523 reviews)

      Beginner · Specialization · 1-3 Months

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      Free

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      Meta

      What is the Metaverse?

      Skills you'll gain: Computer Graphics, Human Computer Interaction, Virtual Reality, Finance, Interactive Design, BlockChain, Marketing, Accounting, Advertising, Big Data, Business Analysis, Business Psychology, Cloud Computing, Communication, Computer Architecture, Computer Vision, Culture, Data Analysis, Data Management, Decision Making, Digital Marketing, Entrepreneurship, FinTech, Financial Analysis, Hardware Design, Human Resources, Leadership and Management, Machine Learning, Operating Systems, Organizational Development, Regulations and Compliance, Security Engineering, Software Engineering, Software Engineering Tools, Software Security, System Security, User Experience, Benefits, E-Commerce, General Accounting, Sales

      4.6

      (445 reviews)

      Beginner · Course · 1-3 Months

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      Hebrew University of Jerusalem

      Build a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course)

      Skills you'll gain: Computer Architecture, Computer Programming, Hardware Design, Other Programming Languages, Algorithms, Applied Machine Learning, Computational Logic, Computer Vision, Machine Learning, Markov Model, Microarchitecture, Statistical Machine Learning, Theoretical Computer Science

      4.9

      (3.3k reviews)

      Mixed · Course · 1-3 Months

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      IBM Skills Network

      Introduction to Artificial Intelligence (AI)

      Skills you'll gain: Applied Machine Learning, Data Science, Computer Vision, Deep Learning, Machine Learning, Machine Learning Algorithms

      4.7

      (10.4k reviews)

      Beginner · Course · 1-4 Weeks

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

    • AI For Business: University of Pennsylvania
    • Python 3 Programming: University of Michigan
    • Influencing: Storytelling, Change Management and Governance: Macquarie University
    • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning: DeepLearning.AI
    • Convolutional Neural Networks: DeepLearning.AI
    • Creating Business Value with Data and Looker: Google Cloud
    • Structuring Machine Learning Projects: DeepLearning.AI
    • Python, Bash and SQL Essentials for Data Engineering: Duke University
    • Uncommon Sense Teaching: Deep Teaching Solutions
    • What is the Metaverse?: Meta

    Frequently Asked Questions about Applied Statistics

    • Applied statistics is the use of statistical techniques to solve real-world data analysis problems. In contrast to the pure study of mathematical statistics, applied statistics is typically used by and for non-mathematicians in fields ranging from social science to business. Indeed, in the big data era, applied statistics has become important for deriving insights and guiding decision-making in virtually every industry.

      The increased reliance on data and statistics to help understand our world has made the careful application of these techniques even more essential; too often, statistics can be used erroneously or even misleadingly when methods of analysis are not properly connected to research questions. Thus, a major aspect of applied statistics is the accurate communication of findings for a non-technical audience, including specifics about data sources, relevance to the problem at hand, and degrees of uncertainty.

      That said, the statistical approaches used in this field are the same as in the study of mathematical statistics. Rigorous use of statistical hypothesis testing, statistical inference, linear regression techniques, and analysis of variance (ANOVA) are core to the work of applied statistics. And, as in other areas of data science, Python programming and R programming are often used to analyze large datasets when Microsoft Excel is not sufficiently powerful.‎

    • Demand for data-driven insights is growing fast across all fields, making a background in applied statistics the gateway to a wide variety of careers. Financial institutions and companies of all kinds rely on business analytics to guide investments and operations; political candidates and advocacy groups need to conduct surveys and understand public polling data to understand popular opinion on today’s issues; and even sports teams are increasingly hiring experts in applied statistics to make decisions regarding personnel as well as in-game strategy.

      While many jobs in applied statistics may require only a bachelor’s degree in fields such as mathematics or computer science, high-level roles often expect a master’s degree in statistics. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160 as of May 2019, and these jobs are expected to grow much faster than average due to the need to analyze fast-growing volumes of electronic data.‎

    • Yes, with absolute certainty. Coursera offers courses and Specializations in applied statistics for business, social science, and other areas, as well as related topics such as data science and Python programming. These courses are offered by top-ranked universities and leading companies from around the world, including the University of Michigan, the University of Amsterdam, and the University of Virginia, and IBM. Regardless of whether you’re a student looking to learn more about this exciting field or a mid-career professional upgrading their skill set, the combination of a high-quality education and the flexibility of learning online makes Coursera a great choice.‎

    • It's very helpful to have strong math skills, analytical skills, and experience solving problems before starting to learn applied statistics. It's also good to have experience and a good comfort level with technology and computers. Previous experience in statistics is also helpful, although not required. You may also benefit from having prior experience using Excel spreadsheets as you begin to learn applied statistics.‎

    • People best suited for roles in applied statistics are analytical thinkers. They enjoy problem-solving by taking available data and analyzing it to arrive at solutions. They also have effective communication skills so that information can flow clearly to all stakeholders within an organization. Organization and multitasking come easily to people best suited for roles in applied statistics because these individuals need to deal with large amounts of information and manage their time and resources efficiently. People well suited for these roles also pay close attention to detail to make sure the outcomes they're tasked with delivering meet or exceed expectations.‎

    • While the use of applied statistics can be found in almost every industry, learning applied statistics may be especially interesting to you if you're seeking a career in the insurance, web analytics, or energy sectors. These are some of the top industries that currently utilize applied statistics. However, a person in any position in which data is gathered and analyzed to create solutions, innovations, or improvements would benefit from learning applied statistics, from coaches and hospital administrators to bloggers, data scientists, and bankers. If you would like to know how to ensure you're collecting the right data, how to analyze data correctly, and how to effectively report your findings so they can be applied in real-world situations, learning applied statistics may be 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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