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AI Curriculum | Major: Time Series Analysis

Develop the specific skills you need to enhance your job profile and become one of the sought-after experts to close the Tech & Data skills gap at Bertelsmann. Learn flexibly with the most in-demand tech learning providers.

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enen
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Coursera: please check our coursera website for details
Date

Various course or license starting dates according to your chosen learning partner (please see on peoplenet)

What you will learn

  • Learners will build  the knowledge and skills relevant to key Time-Series Analysis techniques, including: 

     

    • Linear, non-linear and multivariate time-series concepts such as trends, seasonal, stationary and co-integrated time-series, autocorrelations, autoregressions, moving averages, etc.
    • Expert-level knowledge of time-series modeling using, for example, sequence models such as Long-short Term Memory (LSTM), Recurrent Neural Networks (RNNs), 1D ConvNets and Hidden Markov Models and their use for specific forecasting and predictive analytics purposes

     

  • Acquire the competencies and skills necessary for working in the field of Time-series Analysis
  • Develop in your current role, or qualify for a new task
  • Benefit from a selected, well-structured and quality-checked digital learning curriculum
  • Learn from experts with high practical relevance
  • Exchange information on challenges and best practices in communities
  • Apply the learning content directly in your everyday professional life
  • Continue your education according to your individual knowledge, independent of time and place
  • Take the opportunity to develop further by completing a certificate or university degree

Who will benefit

  • In this specialization subject, you will learn how time-series models can be developed and used for decision support in various business scenarios
  • Time-series analysis and related topics like predictive analytics are valuable tools for companies for purposes, such as trend prediction, predictive maintenance, etc.
  • The creation of forecasts using modern data analysis is generally of crucial importance in the context of data-based business models
  • Requirements:
    • Sound knowledge of linear algebra and statistics, especially probability theory
    • Data analysis experience

What you can expect

  • Learning path with a course program specially designed for Time-series Analysis use cases
  • Modern online learning experience from selected learning providers with high quality standards
  • From short learning nuggets for solving current problems to Nanodegree and recognized university certificate
  • Self-directed learning according to individual abilities and needs - at one's own pace, independent of time and place
  • Interactive learning formats with learning controls to check your own learning progress