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HU Credits:
3
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Soil and Water Sciences
Semester:
1st Semester
Teaching Languages:
English
Campus:
Rehovot
Course/Module Coordinator:
Yair Mau
Coordinator Office Hours:
By appointment
Teaching Staff:
Dr. Yair Mau,
Mr. Erez Feuer
Course/Module description:
Data analysis of time series, with practical examples from environmental sciences.
Course/Module aims:
This course aims at giving the students a broad overview of the main steps involved in the analysis of time series: data management, data wrangling, visualization, analysis, and forecast. The course will provide a hands-on approach, where students will actively engage with real-life datasets from the field of environmental science.
Learning outcomes - On successful completion of this module, students should be able to:
- Explore a time-series dataset, while formulating interesting questions.
- Choose the appropriate tools to attack the problem and answer the questions.
- Communicate their findings and the methods they used to achieve them, using graphs, statistics, text, and a well-documented code.
Attendance requirements(%):
100
Teaching arrangement and method of instruction:
Frontal lectures in a computer classroom
Course/Module Content:
Data wrangling: organization, cleaning, merging, filling gaps, excluding outliers, smoothing, resampling.
Visualization: best practices for graph making using leading python libraries.
Analysis: stationarity, seasonality, (auto)correlations, lags, derivatives, spectral analysis.
Forecast: ARIMA
Data management: how to plan ahead and best organize large quantities of data. If there is enough time, we will build a simple time-series database.
Required Reading:
course website
https://yairmau.com/time-series/
Additional Reading Material:
None
Grading Scheme :
Essay / Project / Final Assignment / Home Exam / Referat 50 %
Submission assignments during the semester: Exercises / Essays / Audits / Reports / Forum / Simulation / others 50 %
Additional information:
None
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