Time Series Analysis & Forecasting
4 March, 2024 – Virtual
From financial data to resource planning, website visitors to measurement monitoring, time-series data surrounds 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.
09:00 – 13:00
What will you learn?
After the training, you will be able to:
Extract insights from time series data, including trends and patterns.
Interpret and model seasonality in time series data.
Build forecasting models to make predictions about the future.
Forecast at scale with Prophet.
This program focuses on time series analysis using Pandas in Python. It covers key topics including timestamp features, aggregations, rolling averages, decomposition, and modeling with scikit-learn and Prophet.
- 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
- Decompose time series data into trends, seasonality, non-cyclical components, and residuals
- Extrapolate current dynamics into the future with a scikit-learn forecasting model
- Explicitly model trends, seasonalities, outliers and holiday effects with Prophet
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.
Why should I do this training
Learn how to extract insights from your time-series data.
Learn how to create state-of-the-art forecasting models for business data.
And gain a strong understanding of how they work.
What does it look like?
should I know?
After registering for this training, you will receive a confirmation email with practical information. A week before the training we will ask you about any dietary requirements and share literature if there’s a need to prepare. See you soon!
The training requires a laptop. The hands-on labs are run in an online environment, eliminating the need to install software.
After registering for this course, you will receive a confirmation email with practical information.
Literature and a nice lunch are included in the price.
Travel & accommodation expenses are not included
Meet the trainer
Meet James Hayward, a data science trainer at Xebia Academy. Get to know him here.
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