Explain the principle.
Concept notes, worked examples and knowledge checks.
LAUNCHPOINT BY MINDFORGEAILearn the science.
Learn the science.
Build the skill.
Build what comes next.
A learning + training programme for the engineer you want to become. Technical depth. Supervised practice. A body of work that speaks for you.
16-WEEK CORE4-WEEK SPECIALIST OPTIONPROPOSED JANUARY 2027
Illustrative campaign image · Created with Canva AI
FROM FIRST PRINCIPLESTo working systems.Learn → Practise → Build → Defend
12common-core courses
30specialist course plans
6focused pathways
1substantial capstone
A PROGRAMME WITH BOTH HALVES.
Understanding matters.
So does doing.
A course tells you what a model is. Training asks you to make it work, diagnose its failures and explain your decisions.
Launchpoint connects both: guided concepts, worked examples, supervised labs, technical reviews and an individual engineering contribution. The full catalogue is visible; the programme has a defined common core and a focused specialist choice.
See exactly what is included ↗YOUR ENGINEERING TOOLCHAIN
From the first commit
to an intelligent system.
Software foundations, mathematical reasoning, machine learning, neural systems, generative AI and the disciplines of delivering them responsibly.
01
Engineering foundations
1 coded course plans
↗02Mathematics & data
5 coded course plans
↗03Machine learning
8 coded course plans
↗04Deep learning & perception
5 coded course plans
↗05Language & generative AI
6 coded course plans
↗06MLOps & cloud
6 coded course plans
↗07Research & professional practice
6 coded course plans
↗08RL & robotics
5 coded course plans
↗PRACTICAL DISCIPLINE, BUILT IN
A visible trail
of your work.
Demonstrate the skill.
Code, data investigation, experiments and supervised lab tasks.
Integrate the system.
A reproducible capstone with tests, reviews and a recovery story.
Own the contribution.
A technical demonstration and an individual explanation of decisions.
OUR PEOPLE. OUR FIRST CHAPTER.Learning is
Learning is
a shared pursuit.
Meet the earlier cohort, see the actual studio and watch an original student presentation. Real history alongside a new programme direction.
Inside the learning community ↗Actual photograph · earlier programme archiveCHOOSE A DIRECTION, THEN GO DEEPER
One foundation.
Several futures.
PATHWAY 01
Applied ML Engineer
A reproducible decision service with feature contracts and documented errors.
ML210 + ML220 ↗PATHWAY 02Generative AI & Agent Engineer
A source-grounded assistant with evaluated retrieval, bounded tools and approval gates.
AI340 + AI350 ↗PATHWAY 03Deep Learning & Vision Engineer
A visual-inspection prototype with held-out scene evaluation and a profiled model.
CV320 + DL310 ↗PATHWAY 04Robotics & Autonomous Systems
A simulated ROS 2 perception/localisation workflow with replay and transform evidence.
ROB301 + ROB310 ↗PATHWAY 05MLOps & AI Platform Engineer
A versioned model service with release controls, monitoring and a recovery drill.
MLO420 + MLO430 ↗PATHWAY 06Scientific AI & Research
A reduced-order twin and reproducible research package with carefully bounded claims.
RES430 + RES440 ↗BEGIN WITH A CLEAR PICTURE
See the curriculum.
Know the commitment.
Review the course plans, timetable, proposed fees and project expectations. Then explore your readiness and prepare an application draft.
Paid professional training. Proposed cohort; admissions not open. Curriculum plans are not a claim that all course lessons are already authored.
EXPLORE THE WIDER CONTEXT
A learning journey.
A connected ecosystem.
THE ENGINEERING RECORD
Thirteen original projects.
Follow the earlier cohort’s work in its original context.
↗ACADEMIC CONTEXTInstitutions and proposals.
A historical SSWP interaction and the proposed Orchid pathway.
↗DISTINCT IDENTITIESOur wider platforms.
Learning, research, publishing and signed-in applications.
↗READING AND PRACTICEA working library.
Programme documents, original notebooks and learner references.
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