Advanced Data Science with Python
26 June, 2025 – Virtual
Go beyond the basics with this Advanced Data Science with Python training. Packed with best practices, models, code, algorithms, and a framework to improve your projects, you will rapidly advance your skills by immersing yourself in two days of nothing but data science, machine learning, and Python.
🔆Summer School special – 30% discount! Find out how to sign up here.🔆
Looking to upskill your team(s) or organization?
Rozaliia will gladly help you further with custom training solutions.
Rozaliia Khafizova
Data and AI Training Advisor
Duration
2 days
Time
09:00 – 17:00 (GMT +2:00)
Language
English
Lunch
Included
Certification
No
Level
Professional
What will you learn?
After the training, you will be able to:
Build reproducible machine learning pipelines using scikit-learn
Apply best practices for machine learning with imbalanced datasets
Design custom transformers and estimators tailored to your use-cases
Analyze the effects of feature engineering and selection on the performance of your machine learning models using cross-validation
Program
- Scikit-learn refresher
- Organizing machine learning workflows with scikit-learn pipelines
- Feature Engineering and selection
- Dealing with imbalanced data
This training is for you if:
You are excited to learn how to build reproducible ML pipelines
You want personalized, instructor-led training to learn best practices right from the start.
You wish to build custom estimators and transformers tailored to your use-cases
You already have some experience with data science and are interested in learning advanced modelling skills.
This training is not for you if:
You want to get started with Python for data analysis (check out our Python for Data Analysis training instead).
You have never built a machine learning model with scikit-learn before (check out our Certified Data Science with Python training instead).
You want to learn more about packaging your Python code and making your data science projects production-ready (check out our Production Ready Python for Machine Learning course instead).
Why should I
follow this training?
Create your own custom scikit-learn objects that are composable with scikit-learn pipelines.
Get best practices for working with Python, Pandas, and scikit-learn.
Improve your model performance.
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.
See you soon!
Course information
All literature and course materials are included in the price.
After registering for this course, you will receive a confirmation email with practical information.
Meet the trainers
Lucy Sheppard
Meet Lucy Sheppard, trainer at Xebia Data. Lucy is a data science trainer and teaches many Python courses as well as dbt Learn.
Lysanne van Beek
Lysanne is a Data Science Educator at Xebia Data and loves making courses as accessible as possible. With over 1,000 hours of training experience and over 750 students taught, she’ll make sure you get the most out of your training.
Enrico Erler
Meet Enrico, a data science trainer at Xebia Academy with a passion for Deep Learning and Statistics. Get to know him here.
