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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

      Introduction to Data Analytics

      Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Data Wrangling, Apache Hive, Data Collection, Data Mart, Data Warehousing, Analytics, Apache Spark, Data Cleansing, Data Lakes, Extract, Transform, Load, Data Visualization Software

      4.8
      Rating, 4.8 out of 5 stars
      ·
      19K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Automation, Web Scraping, Python Programming, Data Manipulation, Data Import/Export, Scripting, Data Structures, Data Processing, Data Collection, Application Programming Interface (API), Pandas (Python Package), Programming Principles, NumPy, Object Oriented Programming (OOP), Computer Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      41K reviews

      Beginner · Course · 1 - 3 Months

    • Status: AI skills
      AI skills
      M

      Microsoft

      Microsoft Power BI Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Excel Formulas, Extract, Transform, Load, Power BI, Data Analysis Expressions (DAX), Microsoft Excel, Microsoft Copilot, Data Modeling, Data-Driven Decision-Making, Star Schema, Data Analysis, Data Presentation, Data Visualization Software, Spreadsheet Software, Data Validation, Interactive Data Visualization, Data Transformation, Data Cleansing, Data Storage

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Databases and SQL for Data Science with Python

      Skills you'll gain: SQL, Relational Databases, Stored Procedure, Databases, Query Languages, Jupyter, Data Manipulation, Data Analysis, Pandas (Python Package), Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      22K reviews

      Beginner · Course · 1 - 3 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Data Literacy, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      143K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google Data Analytics

      Skills you'll gain: Data Storytelling, Data Literacy, Data Visualization, Data Presentation, Data Ethics, Rmarkdown, Interactive Data Visualization, Interviewing Skills, Data Cleansing, Data Validation, Professional Networking, Ggplot2, Tableau Software, Presentations, Spreadsheet Software, Data Analysis, Data Visualization Software, Stakeholder Communications, Dashboard, Sampling (Statistics)

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      168K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Business Analyst

      Skills you'll gain: Data Storytelling, Requirements Elicitation, Risk Mitigation, Business Analysis, Business Process Modeling, Risk Analysis, Process Mapping, Process Optimization, Requirements Management, Risk Management, Business Requirements, Stakeholder Management, Work Breakdown Structure, Scope Management, Process Analysis, Stakeholder Engagement, Data Visualization Software, Excel Formulas, Microsoft Excel, Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Toronto

      GIS, Mapping, and Spatial Analysis

      Skills you'll gain: ArcGIS, Spatial Data Analysis, Spatial Analysis, Geographic Information Systems, Geospatial Mapping, GIS Software, Data Mapping, Data Visualization, Metadata Management, Query Languages, Global Positioning Systems, Quantitative Research, Data Compilation, Data Modeling, Typography, Data Manipulation, Data Processing, Data Storytelling, Design Elements And Principles, Image Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Generative AI Engineering

      Skills you'll gain: Prompt Engineering, Data Wrangling, Large Language Modeling, Unit Testing, Supervised Learning, Feature Engineering, Generative AI, Keras (Neural Network Library), Deep Learning, Artificial Intelligence, ChatGPT, Natural Language Processing, Data Cleansing, Jupyter, Data Analysis, Unsupervised Learning, Data Manipulation, PyTorch (Machine Learning Library), Data Import/Export, Exploratory Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      86K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • R

      Rice University

      Business Statistics and Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Methods, Sample Size Determination, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      13K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Data Management

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Data Governance, Data Security, Data Migration, Database Design, Data Literacy, Descriptive Statistics, Extract, Transform, Load, Data Mining, Cloud Storage, Data Visualization Software, Data Store, IBM DB2, Data Management, Relational Databases, MySQL, Excel Formulas

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    Time Series Analysis learners also search

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

    • Introduction to Data Analytics: IBM
    • Python for Data Science, AI & Development: IBM
    • Microsoft Power BI Data Analyst: Microsoft
    • Databases and SQL for Data Science with Python: IBM
    • IBM Data Science: IBM
    • Google Data Analytics: Google
    • IBM Business Analyst: IBM
    • GIS, Mapping, and Spatial Analysis: University of Toronto
    • Data Analysis with R: Duke University
    • IBM Generative AI Engineering: IBM

    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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