Build skills and confidence

Programming is an experiential skill - the more you do, the better you get.

We will kick-start your learning journey by giving you the knowledge and tasks to build you skills and, most importantly, your ability to continue learning independently.

Take control of your data

Learn how to investigate your datasets - no matter how large or impenetrable.

We give you the experience and tools to  examine, QC, and output tables and graphs from your own data - whatever the format!

Intermediate and advanced courses available

Write better code and use more advanced tools to utilise your data more.

Once you have mastered the basics, then we can help you learn more advanced techniques, analyses, and tools to truly mine the information in your data.

What attendees are saying

I found the pace, structure, and content incredibly well thought out. It gave me a strong, practical foundation in Python—from working with different file types to confidently creating data visualisations.
    Sam Nicholls - Laboratory Operations Supervisor

I'd absolutely recommend this course to any scientist looking to get to grips with Python.
    Sean Monks - Senior Production Process and Improvement Scientist

This course was absolutely brilliant – exactly the springboard I needed to finally start coding with confidence. I’ve been meaning to learn Python for ages, and Introduction to Python for Scientists exceeded all expectations.
    Tom Edmondson - Technical Lead

Read more testimonials

Mortar board

30+ years programming professionally, mentoring individuals and teams,
former university lecturer

Why learn with us?

Learning to program is a tough assignment - if you were the type of person who could learn from dry, online courses then you would probably have done it by now!

Our in-person courses are paced to the attendees, relaxed, and engaging.

We help scientists with every level of coding ability - from complete beginners onward - to gain the knowledge, skills, and confidence to program independently and control their own continued learning.

The courses mix lecture-style with many practical tasks, one-to-one time, and group conversations - led by the attendees to answer their questions, no matter how tangential to the course materials!

The notes and tasks dovetail together to keep attendees interested and layering increasing knowledge at each stage, supporting the learning of all attendees whatever their pace of learning.

  • Mark lecturing
    Mark lecturing
  • One-to-one feedback
    One-to-one feedback
  • Ad hoc group conversation
    Ad hoc group conversation

Overcome inertia by learning to program in an engaging and supportive atmosphere

Introduction to Programming for Scientists

Three day, in-person courses in R or Python

Learning outcomes:

Familiarity and confidence with programming

Understanding context and history of computer science

Use the IPO model to read in Excel data, examine it, and produce plots

Learn about multiple formats: Excel, JSON, image files

Further courses:

Intermediate

Learning outcomes:

Programming with VS Code and git

Advanced program flow

Curating, aggregating, and transforming complex datasets

Basic statistical analyses

Complex graphical outputs

Advanced

Learning outcomes:

Working collaboratively in teams

Deploying code and libraries

Logging, debugging, and writing efficient code

Object oriented code

Using advanced statistics and AI/ML