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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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Digital only
Open
en
Coursera: please check our coursera website for details
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
