About AI Charmers
We specialise in the design and delivery of technical AI and machine learning training for corporates, government organisations and research teams. Our course material is developed for each audience rather than taken off the shelf.
Our courses are written for the people who build these systems: engineers, data scientists, analysts and researchers who will be working in Python, training models, and answering for the results. Every course is hands-on, and you leave with code you have written yourself.
Our trainers have worked individually in AI and machine learning for more than 20 years, across research, industry and open source — through several shifts in what the field considered state of the art. Over the past 15 years we have delivered hundreds of courses, from foundational methods and model evaluation through to deep learning and large language models.
That depth is the point. Because we have spent careers applying these techniques, we can teach not just how a method works but when it is the wrong choice — and explain the reasoning in plain English.
Our Expertise
We specialise in machine learning, deep learning, and large language models. Our trainers have worked in these fields for over 20 years and still practise what they teach.
Our Approach
Technical courses in small groups, taught in Python. You write the code and train the models yourself, on real data, with a trainer beside you.
Our Mission
To help professionals and organisations apply AI and machine learning well — knowing both what these methods can do and where they fall short.
Our Clients
We've trained teams at leading organisations including Boeing, Cisco, Toyota, Optus, and many Australian government agencies and universities.
Our Training Philosophy
Practitioners, Not Presenters
Your trainer has built and shipped these systems, and can answer the questions that come up when yours does not behave.
You Write the Code
Every course is hands-on in Python. You train the models yourself and leave with working code you understand.
Judgement, Not Just Method
Knowing when a technique is the wrong choice matters as much as knowing how to run it. We teach both.
Ongoing Support
Post-course support and resources, so the work continues once you are back at your desk.
Our Team
Our team of specialists consists of experienced practitioners in machine learning, deep learning, data science, and technical training.
Dr Ed Schofield
Founder and Lead Trainer
Ed holds a PhD in machine learning from Imperial College London, and BA and MA (Hons) degrees in mathematics and computer science from Trinity College, University of Cambridge. He is the founder of Charmers Group in Australia and Singapore.
Ed has trained over 3000 people from dozens of organisations in data science and machine learning, including Atlassian, Barclays, Cisco, CSIRO, Dolby, Harvard University, IMC, Singtel Optus, Oracle, Shell, Telstra, Toyota, Verizon, and Westpac. He is a former release manager of SciPy, part of the scientific computing stack these methods are built on, and is sought-after as a speaker at conferences around the world.
Robert Layton
Senior Trainer
Robert is a contributor to scikit-learn, the open source machine learning library, and the author of "Data Mining with Python", published by Packt in 2016. He authored the website learningtensorflow.com and sold it to Databricks in 2017.
He provides analysis, consultancy, research and development work to businesses across the government, financial and security sectors. He was previously a Research Fellow at the Internet Commerce Security Laboratory, Federation University Australia, investigating cybercrime analytics and data-mining algorithms for attribution and profiling. He writes regularly on data mining and has presented at international conferences on data analytics and its applications.
Henry Walshaw
Senior Trainer & GIS Expert
Henry has 16 years of experience in GIS, spatial analysis and application development, particularly in the natural resource management field. Henry's core technical expertise relates to the development and analysis of large scale spatial datasets (primarily using Python), and communicating this understanding to people including subject matter experts and the general public.
Henry has worked in government at federal and state levels, at Geoscience Australia (GA), the Victorian Government Department of Sustainability and Environment (DSE), and the Environmental Protection Agency (EPA). He has also worked in the private sector as a consultant, manager and CTO at a startup. He is currently a senior developer at FloodMapp, an Australian company developing real-time flood alerting systems. He has trained over 1000 people with Python Charmers from organisations including AGL, the Bureau of Meteorology, CSIRO, ESRI, National Australia Bank, and Telstra. He holds a Bachelors in Computational Science.
Emeritus Trainers
We are grateful to these amazing past trainers for their service to our clients.
Dr Juan Nunez-Iglesias
Emeritus Trainer
Juan Nunez-Iglesias is co-author of the book Elegant SciPy, published by O'Reilly Media. Juan is a core developer of the scikit-image Python library, and has contributed to many others in the scientific Python ecosystem, including SciPy, NetworkX, and Matplotlib. He has taught and presented at the SciPy conference in Austin, EuroSciPy, PyCon Australia, the Advanced Scientific Programming in Python summer school, and Software Carpentry workshops.
Juan is a research fellow at Monash University, with interests in neuroscience and biological image analysis. He also has a particular interest in renewable energy and the environment.
Juan has a Bachelor's degree in Biomedical Science from the University of Melbourne and both an MSc in Statistics and PhD in Computational Biology and Bioinformatics from the University of Southern California.
Errol Lloyd
Emeritus Trainer
Errol's background is in computational neuroscience. He has been using Python for modelling neurological systems, digital signal processing, data analysis, and empirical research for 7 years.
Prior to joining Python Charmers in 2020, Errol trained fellow researchers from both the sciences and the humanities in a variety of software solutions to research problems, including data and natural language analysis in Python, data visualization, interactive dashboards with front-end JavaScript, and version control and collaboration with git and GitHub.
Errol is an advocate for open source software and reproducible research in science, and is passionate about empowering others to use code in enhancing their productivity. He completed doctoral studies on visual processing in the brain at the University of Melbourne.
Dr Clare Sloggett
Emeritus Trainer
Clare began life in computational physics before moving into genomics. She has research interests in data visualization and algorithms for genomic data. Her current focus is in machine learning for clinical and genomic data. She co-organized the Python in Science and Data Miniconf for PyCon AU from 2015-2017 and regularly gives talks at conferences and community events in genomics and data analytics with Python and other open source tools.
Clare holds a BSc and PhD in computational physics from the University of NSW.
Bianca Gibson
Emeritus Trainer
Bianca is a development team lead with Australian charity Infoxchange, where she uses Python to make a directory that connects people in need with housing, a meal, money help, family violence support, counselling and much more. She has been using Python for over a decade and has mostly worked in the government and not-for-profit sectors. She trained her colleagues at realestate.com.au and the Australian Bureau of Meteorology in Python and development tools. She has presented 3 times at PyCon AU and RubyConf AU on topics such as functional programming and an analysis of "imposter syndrome" and fostering healthy self-belief.
Bianca has an undergraduate degree in computer science from Monash University, Australia.
Dr Ned Letcher
Emeritus Trainer
Ned is a data scientist and software engineer who has helped a range of organizations in projects involving machine learning, natural language processing, information retrieval, and data visualization. Ned has been using Python for data analysis, visualization, machine learning, and web development for over 10 years. Ned is a contributor to the Plotly Dash library and an active member of the Dash community.
Ned has a PhD in computational linguistics from the Natural Language Processing group at the University of Melbourne. He also has a Bachelor of Arts (philosophy and linguistics) and a Bachelor of Science with Honours (computer science). Ned regularly presents at local meetups and organises the Melbourne Data Visualisation Meetup.
Testimonials
"I found it to be very inspiring."
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