Courses
Expert-led training in Design of Experiments and Bayesian Optimization
Introduction to Design of Experiments
1 day Beginner
Learn the fundamentals of experimental design and how to apply DoE principles to your research or industrial processes.
What You'll Learn:
- Understanding experimental design principles
- Planning efficient experiments
- Factorial designs and screening
- Analyzing and interpreting results
- Hands-on exercises with real data
Design of Experiments with Python
1 day Intermediate
Learn to design and analyze experiments using Python. Gain practical skills with modern tools and libraries for experimental design.
What You'll Learn:
- Python libraries for DoE (pyDOE, scikit-learn)
- Creating and analyzing factorial designs
- Response surface methodology in Python
- Data visualization and interpretation
- Optimization techniques
- Real-world case studies and coding exercises
Introduction to Bayesian Optimization
1 day Advanced
Discover the fundamentals of Bayesian optimization and learn how to efficiently optimize expensive experiments.
What You'll Learn:
- Fundamentals of Bayesian methods
- Introduction to Gaussian processes
- Understanding acquisition functions
- Sequential optimization basics
- Practical Python examples
Custom Training
Flexible All Levels
Tailored training programs designed for your team's specific needs and industry challenges.
What You'll Learn:
- Customized curriculum
- Industry-specific examples
- On-site or online delivery
- Consulting and support
- Hands-on project work
Ready to accelerate your research?
Contact us to discuss your training needs and schedule a course that fits your team's requirements.
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