Training schedule

12 Dec - 16 Dec, 2022
Online, instructor-led / English
€1295

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!
Check out more

Data Science - Senior

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 our Python for Data Analysts course instead.) 
  • You have never built a model before with scikit-learn. (Check out our 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

Day 1
  • Timestamp features in Panda
  • Aggregations
  • Rolling averages and smoothing
Day 2
  • Error-trend-seasonality decomposition
  • Modeling time series with scikit-learn
  • Modeling time series with Prophet;

learning journey

Data Science Learning Journey

meet your trainer

Marysia Winkels

Data Scientist

Marysia is a data scientist who is proud to work on any AI application that can provide solutions to real-world problems. She is always eager to learn from, and be inspired by, her peers.

Flexible delivery

The Right Format For Your Preferred Learning Style

In-Classroom & In-Company Training
Online, Instructor-Led Training
Hybrid and Blended Learning
Self-Paced Training
Get in touch with the experts

Have any questions?

Contact Giovanni Lanzani, our Managing Director of Learning and Development, if you want to know more. He’ll be happy to help you!

Call me back

You can reach him out by phone as well at +31 6 51 20 6163

Course: Practical Time Series Analysis & Forecasting Training

Book now