Training that builds lasting capability.

Our goal for training is care: care for our trainees, our courses and the link to applications, so that learning outcomes translate into real-world results.

Programs

Three training tracks

Professional & corporate

Courses for analysts, clinicians, researchers and managers.

  • Biostatistics and experimental design
  • Statistical analysis plans and clinical-trial methods
  • Real-world evidence and observational data
  • SAS, R, SQL and Python for data analysis
  • Decision analysis and simulation
  • Lean Six Sigma foundations

Mathematics, statistics & AI foundations

For high-school, college and adult learners at every level.

  • Algebra, geometry, pre-calculus and calculus
  • Probability and statistics
  • Linear algebra and engineering mathematics
  • Excel for data and decision analysis
  • Introductory machine learning and responsible AI for non-technical learners

Program development & accreditation

For universities and training providers.

  • Course and curriculum design
  • Assessment and evaluation methods
  • Academic program accreditation support
  • Program planning for public-health and computer-science schools
  • Workshops for regional medical doctors
How we teach

Our training approach

  • Convey a positive vision of education and science
  • Continually improve course syllabi and outcomes
  • Stabilize class management and enhance course delivery
  • Enhance curriculum assessment and development
  • Support trainees’ understanding and creativity
  • Work for trainees’ satisfaction

Real-world examples, decision-tree guides, templates, hands-on software labs and applied projects are woven into every course.

A group of trainees with their instructor after a class
Outcomes

Results we measure

Trainee evaluations consistently show strong results and steady improvement over time.

3.5+average trainee evaluation on a 4-point scale, across eight master’s-level courses (2009–2013)
+0.11 to +0.28annual gain across all ten evaluation items, with a significant positive trend
4.6 / 5average student rating in university engineering-mathematics and statistics courses
8graduate students trained in data mining and large-dataset integration in a university data-mining lab
“Your enthusiasm for the content was contagious and absolutely helped me learn not only the science of it but the art as well. Statistics became an interesting subject for me, and that is not something I was even open to at the start of the course.”Student with a non-statistics background, experimental design course
“I appreciate your teaching style, your demeanor, and the fact that you are just very knowledgeable in the class content and very approachable with questions.”Full-time nurse and non-traditional student

Looking for training for your team or your student?

Tell us the level, the topic and the format you have in mind (in person or online).