Training

Practical Time Series Analysis & Forecasting

Two-Day Training

What will the future hold?

From inventory to website visitors, resource planning to financial data, 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” and make data-driven business forecasts.

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This course is perfect for

Data Scientists who know Machine Learning and want to expand their skillset by moving from static data sets to dynamic time-dependent data sets.

We invite anyone who is familiar with Python and statistics and wants to become more productive and empowered in analyzing and forecasting using time-series data to join us. To ensure you get the most out of these two days, we recommend you have at least one year of work experience with pandas, scikit-learn, and Matplotlib.

What will you learn during Practical Time Series Analysis & Forecasting?

You will learn to confidently work with time-series data: cleaning it, removing outliers, and handling missing data. You will also learn how to create forecasts with your data sets and validate your models when using time-series data.

Program

The program consists of nine blocks. Each block consists of a theory component and a hands-on lab.

Day 1:

  • Time features encoding and formatting;
  • Pandas time series features (smoothing, resampling, re-weighting);
  • Sessionization and holiday
  • Feature Engineering for time
  • Additive vs Multiplicative
  • Error-Trend-Seasonality Decomposition;

Day 2:

  • Seasonality estimation;
  • Forecast evaluation and model selection;
  • Forecasting with Prophet;
  • Switch-point Detection;
  • Outlier Detection.

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Course details

You will learn:

  • How to effectively handle time-series data
  • Python utilities that make working with time-series a breeze
  • Why model validation with time-series data cannot follow the traditional machine learning methodology
  • How to determine which loss functions to use when training models
  • Why feature engineering is fundamental to the success of your modeling
  • How to incorporate seasonality into your models

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Availability

Training Formats

This training is available in the following formats:

In-Company Classroom

In-Company training is perfect for groups of 6 or more. The training takes place online, at your office, or at one of our modern training facilities.

Online Virtual Classroom

Virtual Classrooms provide you with an interactive environment to effectively develop your skills, right from the comfort of your own home or office.

Data Science Learning Journey

This data science learning journey is available for any data professional. Our extensive training programs are designed to develop your skills from junior to senior.

Our curriculum teaches you new skills and empowers you to stay ahead professionally. We offer solid fundamentals that apply to practical Python courses, whether you are a beginner or an advanced user. We also offer courses on Spark, R, and Deep Learning.

We’ve experienced first hand what works and what doesn’t through our consulting business, and we pass that knowledge on to you through our education business. You learn all the ins and outs of the data science models most seen in the field, in a fast-paced classroom training that ups your game.

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Any questions? Please get in touch!

Contact Gert-Jan Steltenpool, our Sales Director, if you want to know more. He’ll be happy to help you!