Our Story
A Workshop for Engineers Who Want to Build, Not Just Learn.
Mindforge was put together in Kota Kinabalu by a small group of practitioners who kept noticing the same gap: people leaving online courses knowing a lot of theory and almost none of the practical side.
Back to HomepageThe Origin
How Mindforge Came Together
The studio started in 2022, when three engineers working in different corners of the Malaysian tech industry began running informal Saturday workshops out of a borrowed co-working space near the Kota Kinabalu waterfront. The sessions were intended for colleagues who had expressed curiosity about machine learning but kept hitting a wall: most available learning materials were either too shallow to be useful or too theoretical to translate into day-to-day engineering work.
After the first two cohorts, it became clear that the format — short framing lecture, then a live coding block, then a practice notebook to finish at home — was producing the kind of progress that self-paced online courses rarely did. Participants were building working models and asking better questions by week three. That format became the foundation of every Mindforge course.
The studio now operates from Suite 8-A on Jalan Tun Mustapha, with a small permanent team, a rotating group of senior mentor contributors, and a course catalogue that has grown to three structured programmes. The same practice-first philosophy that ran in that borrowed co-working space in 2022 runs through everything we put together today.
What We Stand For
Mission and Values
Our work sits in a specific niche: applied AI education for working adults who do not have the luxury of months off to study. We do not aim to produce researchers or to replicate academic curricula. We aim to close the gap between knowing and doing — between reading about machine learning and shipping something that works.
Practice over exposition
Every hour of lecture earns more hours of hands-on work. We write notebooks, not just slides.
Small enough to follow individual progress
Cohort sizes are kept deliberate. Instructors know who is ahead and who needs a different explanation.
Honest about what education can do
We do not promise careers or outcomes. We provide structured practice, feedback, and a cohort to work alongside.
Built for Sabah, useful beyond it
We run on Malaysian time, observe local holidays, and keep pricing relevant to the local market. Remote participants from across Malaysia are always welcome.
The People
Core Team
A small team with backgrounds in industry engineering and structured education. Everyone who teaches at Mindforge has built production systems before stepping in front of a cohort.
Ahmad Radzuan
Lead Instructor · Machine Learning
Eight years writing production data pipelines and classification systems before joining Mindforge full-time. Leads the Hands-On ML course and reviews Engineering Block projects.
Serena Lim
Senior Instructor · AI Engineering
Previously an MLOps engineer at a logistics technology company in Kuala Lumpur. Now teaches the Applied AI Engineering Block and mentors Capstone participants through deployment milestones.
James Ongkili
Programme Director · Capstone
Designed the Forge Capstone Programme structure and facilitates the closing cohort review each cycle. Background in software architecture and ten years of technical consulting across Sabah and the peninsula.
How We Work
Our Standards
A set of operating commitments that shape how we build courses, run cohorts, and handle participant information.
Practitioner-Instructed
Every instructor has worked in an engineering capacity before teaching. We do not hire presenters; we hire engineers who can explain what they have built.
Reviewed, Not Automated
Practice notebooks and final projects are read and responded to by a human reviewer. No automated scoring. Feedback is written, specific, and actionable.
Data Handled Carefully
Participant data is collected only for enrolment and communication purposes. We do not share details with third-party marketing services, and we retain only what is needed.
Content Updated Each Cycle
Course materials are reviewed after every cohort and updated where the field or tools have moved. Participants receive the current version, not a static archive.
Accessible Participation
Live sessions offer remote access. Recorded lectures are captioned. We work with participants who need schedule adjustments due to shift work or family commitments where possible.
Transparent Terms
Fees, refund terms, completion criteria, and intellectual property arrangements are stated plainly before enrolment. Nothing is buried in fine print.
Our Approach
AI Education Designed Around Engineering Practice
Mindforge operates in a corner of the educational market that is still relatively sparse: structured, practice-oriented AI programming education for working professionals who do not have a clear on-ramp from their current skills into applied machine learning. The three courses we offer — a ten-week machine learning entry course, a twelve-week engineering block, and a sixteen-week capstone programme — are built in sequence and designed to be taken in order, though participants with relevant experience can start at a later point.
The machine learning course emphasises doing over watching. Each week has a recorded lecture, a live coding session, and a practice notebook that participants complete between sessions. Topics move from classical supervised learning methods through evaluation approaches to an introduction to neural network architectures. The course is framed around working models, not abstract concepts, and participants who complete all notebooks receive a course completion record.
The engineering block moves from model training to the infrastructure that surrounds it — the pipelines that move data, the systems that deploy models, and the monitoring that keeps deployed models honest. This block suits participants who have some model-training experience and want to understand what happens before and after the training loop. An applied project at the end of the twelve weeks draws together the different elements of the block.
The capstone programme is the most intensive of the three. It pairs each participant with a senior mentor and structures sixteen weeks around their chosen project, with cohort check-ins, milestone reviews, and a closing session where the finished capstone is presented to the wider group. The programme belongs to the learner from beginning to end: the project, the code, and any resulting work are their own intellectual property.
Mindforge is headquartered in Kota Kinabalu, Sabah, and runs on Malaysian Standard Time. The team is small by design. We do not aim to scale to thousands of concurrent participants; we aim to run cohorts where instructors know participants by name and can adjust feedback accordingly.
Want to Learn More About the Courses?
Send an enquiry or browse the full curriculum outline. We'll answer questions about which course fits your background and when the next cohort opens.