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    • Time Series Analysis

    Time Series Analysis Courses Online

    Study time series analysis for forecasting. Learn techniques for analyzing temporal data and building predictive models.

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    Explore the Time Series Analysis Course Catalog

    • I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Data Science, Probability & Statistics, Jupyter, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      S

      Stanford University

      Introduction to Statistics

      Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Data Collection, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.1K reviews

      Beginner · Course · 1 - 3 Months

    • W

      Workday

      Workday in Action Series

      Skills you'll gain: Workday (Software), Benefits Administration, Payroll Processing, Accounts Payable and Receivable, Human Capital, General Accounting, Business Process, Compensation Management, Payroll Administration, Human Resource Management, Workforce Management, Applicant Tracking Systems, Compensation and Benefits, Recruitment

      4.8
      Rating, 4.8 out of 5 stars
      ·
      81 reviews

      Beginner · Course · 1 - 3 Months

    • V

      Vanderbilt University

      ChatGPT Advanced Data Analysis

      Skills you'll gain: Prompt Engineering, Data Presentation, ChatGPT, Document Management, Artificial Intelligence, Microsoft Excel, Problem Solving, Data Analysis, Generative AI, Information Management, File Management, Creativity, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      778 reviews

      Beginner · Course · 1 - 3 Months

    • P

      PwC

      Data Analysis and Presentation Skills: the PwC Approach

      Skills you'll gain: Analytics, Business Analytics, Data Analysis, Microsoft PowerPoint, Data Presentation, Presentations, Excel Formulas, Data-Driven Decision-Making, Dashboard, Data Storytelling, Business Intelligence, Microsoft Excel, Customer Analysis, Data Visualization, Data Visualization Software, Data Literacy, Big Data, Verbal Communication Skills, Data Cleansing, Spreadsheet Software

      4.6
      Rating, 4.6 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google Digital Marketing & E-commerce

      Skills you'll gain: Media Planning, Search Engine Marketing, Email Marketing, Data Storytelling, Social Media Strategy, Search Engine Optimization, Social Media Marketing, Content Creation, Order Fulfillment, Google Ads, Professional Networking, Online Advertising, A/B Testing, Social Media Campaigns, Digital Advertising, E-Commerce, Customer Retention, Customer Relationship Management, Campaign Management, Interviewing Skills

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      39K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of California, Davis

      Learn SQL Basics for Data Science

      Skills you'll gain: Data Governance, Presentations, SQL, Apache Spark, Distributed Computing, Data Quality, Descriptive Statistics, Data Lakes, A/B Testing, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Data Pipelines, Databricks, JSON, Statistical Analysis, Database Design, Query Languages, Complex Problem Solving

      4.6
      Rating, 4.6 out of 5 stars
      ·
      17K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      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, Data Architecture, Jupyter, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Manipulation, Stored Procedure, Databases, Automation, Python Programming

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

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California, Davis

      Data Visualization with Tableau

      Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization Software, Key Performance Indicators (KPIs), Data Visualization, Dashboard, Interactive Data Visualization, Data Mapping, Tableau Software, Proposal Development, Graphing, Histogram, Scatter Plots, Tree Maps, Exploratory Data Analysis, Statistical Visualization, Storytelling, Performance Metric, Geospatial Mapping, Heat Maps

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • S

      Starweaver

      Certified Business Analysis Professional™ (CBAP®)

      Skills you'll gain: Process Analysis, Requirements Elicitation, Business Analysis, Risk Analysis, Backlogs, Requirements Management, Stakeholder Engagement, Business Process, User Requirements Documents, User Story, Business Requirements, Requirements Analysis, Business Modeling, Business Process Improvement, Business Intelligence, Business Risk Management, Business Strategies, Financial Analysis, Performance Measurement, Business Planning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      250 reviews

      Intermediate · Specialization · 3 - 6 Months

    • W

      Workday

      Workday Basics Series

      Skills you'll gain: Workday (Software), Business Process, Workflow Management, Business Reporting, System Configuration, Role-Based Access Control (RBAC), Enterprise Security, Organizational Structure, Data Access, Multi-Tenant Cloud Environments

      4.8
      Rating, 4.8 out of 5 stars
      ·
      276 reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google

      Foundations of Cybersecurity

      Skills you'll gain: Cybersecurity, Security Controls, Cyber Attacks, Security Management, Cyber Security Strategy, Incident Response, Cyber Risk, Security Information and Event Management (SIEM), Information Assurance, Data Ethics, Network Analysis, Ethical Standards And Conduct

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      34K reviews

      Beginner · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular time series analysis courses

    • Exploratory Data Analysis for Machine Learning: IBM
    • Introduction to Statistics: Stanford University
    • Workday in Action Series: Workday
    • ChatGPT Advanced Data Analysis: Vanderbilt University
    • Data Analysis and Presentation Skills: the PwC Approach: PwC
    • Google Digital Marketing & E-commerce: Google
    • Learn SQL Basics for Data Science: University of California, Davis
    • Data Engineering Foundations: IBM
    • Data Visualization with Tableau: University of California, Davis
    • Certified Business Analysis Professional™ (CBAP®): Starweaver

    Skills you can learn in Probability And Statistics

    R Programming (19)
    Inference (16)
    Linear Regression (12)
    Statistical Analysis (12)
    Statistical Inference (11)
    Regression Analysis (10)
    Biostatistics (9)
    Bayesian (7)
    Logistic Regression (7)
    Probability Distribution (7)
    Bayesian Statistics (6)
    Medical Statistics (6)

    Frequently Asked Questions about Time Series Analysis

    Time series analysis uses statistical techniques to determine how a sequence of numerical data points varies during a specific period of time. For example, time series analysis is used in the financial sector to track the prices of securities, commodities, and other assets to discover how they may vary seasonally. These techniques are important in business, science, public opinion polling, or any other field which seeks to understand how things change over time.

    The insights from time series analysis are often used for time series forecasting, which seeks predictions in the future changes in the value of a variable based on its movement in the past. Financial modeling and other applications of these techniques may also use linear regression to establish relationships between the variable of interest and other variables, such as overall economic factors like the unemployment rate or weather patterns.

    Even more powerful prediction engines can be developed using machine learning and deep learning approaches. The use of TensorFlow, R, and Python programming for increasingly sophisticated applications of time series analysis is making it possible to uncover complex patterns in vast datasets that would have been impossible - or, at least, very difficult and time-consuming - in the not-too-distant past.‎

    Time series analysis skills are important for a wide range of careers in business, science, journalism, and many other fields. Whether you’re a biologist seeking to understand seasonal growth of an invasive species population or a political scientist analyzing trends in support for a candidate over the course of a campaign, time series analysis is a fundamental tool for describing change.

    The combination of time series analysis and time series forecasting is particularly useful in the world of finance, where quantitative analysts or “quants” that discover hidden correlations in the movements of stocks can generate incredible value for clients. According to the Bureau of Labor Statistics, analysts in securities, commodities, and other financial investments make a median annual salary of $98,690 per year and typically only have a bachelor’s degree, making this a high-paying job to begin your career in the business world.‎

    Yes, absolutely! Coursera offers a breadth of learning opportunities across business as well as data science topics, including courses and Specializations that teach time series analysis skills. Wherever you live, you can learn about time series analysis remotely from top-ranked schools from around the world like the University of Pennsylvania, the State University of New York, Erasmus University Rotterdam, and The Hong Kong University of Science and Technology. You can also build skills in time series analysis by completing step-by-step tutorials alongside experienced instructors with Coursera’s Guided Projects.

    Regardless of what you choose, learning on Coursera gives you the flexibility to view and complete course materials on your own schedule, making this ideal for students as well as mid-career professionals looking to add new skills to their resume.‎

    Skills you typically need when starting to learn time series analysis include technical skills and math skills. The technology is used for collecting and organizing data sets into usable information. In the area of math, you generally need to have some experience in statistics. It may also help if you have experience reading graphs and charts to interpret information. You might also have to use your technical skills to download software programs, such as R, that are needed for time series analysis learning. Python, machine learning, AI, statistics, and linear algebra are some other skills you may need to possess along with an interest in data analysis.‎

    People who are curious and who have a passion for learning are typically best suited for time series analysis. People who are highly analytical may enjoy this field of work. Time series analysis can also be well suited to people who enjoy exploring advanced mathematical models and using highly technical computer programs. These people can come from many other technical fields, such as engineering or science. Additionally, people who are involved with AI-powered algorithms can be well suited for roles in time series analysis.‎

    Time series analysis could be right for you if you enjoy learning about topics like statistical hypothesis testing and if you have an appreciation for complex mathematical models using statistics. If you find solving complex puzzles interesting, time series analysis could be right for you. Time series analysis could also be right for you if you’re working in a field that delivers large amounts of data and there is no good way to process that data. Learning time series analysis could potentially help you close that data processing gap.‎

    Some career paths for someone in time series analysis include science, business, and engineering. Data analysts, financial analysts, and business analysts are also common career paths in this field. It can also typically be applied by people who specialize in machine learning and AI. Research is another common career path in this field. Time series analysis can be used by researchers to create models which can then be used to solve real-world problems.‎

    Online Time Series Analysis courses offer a convenient and flexible way to enhance your knowledge or learn new Time Series Analysis skills. Choose from a wide range of Time Series Analysis courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Time Series Analysis, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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