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.
Looking to upskill your team(s) or organization?
Nico will gladly help you further with custom training solutions.
Nico de Jonge
Data and AI Training Advisor
Duration
4 days
Time
09:00 – 13:00
Language
English
Lunch
Excluded
Certification
No
Level
Professional
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.
Forecast at scale with Prophet.
Key takeaways
Time Series Analysis
- Effectively deal with timestamps and formatting with Pandas
- Master fundamental time series analysis techniques with aggregations
- Quickly 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, seasonality, and holiday effects with Prophet
Program
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.
- Timestamp features in Pandas
- Aggregations
- Rolling averages & smoothing
- Error-trend-seasonality decomposition
- Modeling time series with scikit-learn
- Modeling time series with Prophet
Who is it for?
This course is ideal for Data Scientists with experience with data wrangling, Pandas, and Machine Learning who want to expand their skillset by moving from static to dynamic time-dependent data sets. Want to become more productive and empowered in analyzing and forecasting using time-series data? Then this course is for you!
Requirements
To ensure maximum benefit from this course, participants should have at least a year of work experience with Pandas, Scikit-learn, and Prophet.
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?
What else
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!
Requirements
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
James Hayward
Meet James Hayward, a data science trainer at Xebia Academy. Get to know him here.
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