Training schedule
IN-COMPANY TRAINING PROGRAMS
Contact Giovanni Lanzani, if you want to know more about custom data & AI training for your teams. He’ll be happy to help you!
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What will the future hold?
From financial data to resource planning, website visitors to measurement monitoring, time-series data is all around us. But how can you know what the future holds? This two-day course empowers you to go beyond “spotting trends” to making data-driven business forecasts.
Please keep in mind, the December edition will have 4 half days, see the schedule below.
Dates: 12, 13, 15, and 16 December, from 09.00 till 13.00 CEST.
This training is for you if…
- You work with time series data or are likely to in the future.
- You have (some) experience with data wrangling with Pandas and machine learning with scikit-learn.
- You want to extract insights from your time series data more easily.
- You want to build forecasting models you can trust.
This training is not for you if…
- You have no data wrangling & analysis experience with Pandas. (Check out the Python for Data Analysts course instead.)
- You have never built a model before with scikit-learn. (Check out the Certified Data Science with Python course instead.)
Clients we've helped
What you'll learn
Time Series Analysis
- Effectively deal with timestamps and formatting with Pandas
- Master fundamental time series analysis techniques with aggregations
- Easily identify trends in the data with rolling averages and various smoothing techniques
Forecasting & Modeling
- Decompose time series data into trends, seasonality, non-cyclical components, and residuals
- Extrapolate current dynamics into the future with various time series models such as ARIMA and LSTMs
- Explicitly model trends, seasonalities, and holiday effects with Prophet
The schedule
- Timestamp features in Panda
- Aggregations
- Rolling averages and smoothing
- Error-trend-seasonality decomposition
- Modeling time series with scikit-learn
- Modeling time series with Prophet;