The Case for Doing This Differently
Not every AI training programme is the same. Here is what we do, why we do it, and what we deliberately do not offer.
Back to HomeSix Things That Shape the Experience
Ordered Steps
Topics are sequenced so that each one depends only on what has already been covered. No concept is introduced before its prerequisites have been applied.
Schedules That Fit Real Life
Weekend and weekday options mean you do not have to choose between the track and your current commitments. The schedule is a design decision, not an afterthought.
Specific Written Feedback
Instructors respond to each exercise submission in writing. Feedback addresses your work, not a template response based on the topic.
Team Programmes on Your Stack
The Team Upskilling Programme is built around the employer's actual codebase and problems — not a standard curriculum applied regardless of context.
GPU Credits on the Intensive Track
The Weekday Intensive includes GPU credits so that participants can run training jobs without setting up their own compute infrastructure during the programme.
Honest Completion Records
Records state what was covered. If something was not completed, the record reflects that. We do not issue records that imply more than what actually happened.
Instructors Who Have Done the Work
The people who teach at Gradient Yard have backgrounds in applied machine learning, software engineering, and data science. They have built and maintained models in commercial or research settings before teaching. This matters because the questions participants ask — about why something fails, how to interpret an evaluation metric, when a simpler approach is preferable — are easier to answer if the instructor has faced them in practice.
A Curriculum That Builds Rather Than Jumps
Many AI courses move quickly through foundational topics because they are positioned as prerequisites to get through, not subjects worth understanding. At Gradient Yard, the pace is set by the curriculum's structure rather than a desire to reach more advanced material sooner. Each terrace is cleared before the next is opened.
Tools That Match What Practitioners Use
Tracks are taught using the same libraries and workflows that practitioners encounter in actual model development — Python data tools, standard training frameworks, and evaluation practices that transfer to real environments. The Weekday Intensive includes GPU credits so participants can run meaningful training jobs during the programme.
Multiple Points of Contact During a Track
Participants on the Weekend Entry Track have a study partner from week one, access to office hours on Wednesday evenings, and written feedback on every exercise. Participants on the Weekday Intensive have a mentor assigned throughout, daily standups, and paired programming sessions. Team participants have weekly clinics and a follow-up after the programme ends.
Pricing That Reflects Scope, Not Prestige
The three tracks are priced at RM 780, RM 3,240, and RM 4,620 respectively. Each price reflects the scope of what is included — session hours, instructor time, materials, GPU credits where relevant, and follow-up clinics where applicable. There are no hidden add-ons. The enrolment agreement states what is included before payment is made.
Typical Approach vs Gradient Yard
Typical AI Training
- Topics covered in the order the slides were written, not the order they build on each other
- Feedback is a rubric score or generic comment on the topic
- Schedule does not account for participants who have jobs
- Team programmes use the same exercises regardless of the team's actual stack
- Completion record implies skills that may not have been covered
- Employment outcomes implied without basis
Gradient Yard
- Topics sequenced so each builds on the previous — verified in the curriculum review after every cohort
- Written feedback specific to your submission, reviewed by the instructor
- Weekend and weekday tracks designed for people with existing commitments
- Team exercises built from the employer's own stack and live problems
- Completion record states only what was covered — accurate, not aspirational
- No employment claims of any kind
Three Distinctive Features
Terrace Index Navigation
Each track includes a written terrace index — a structured document showing where a participant is, what they have completed, and what comes next. It is updated as the track progresses, so participants always know their position in the curriculum rather than guessing how far through they are.
Before-and-After Skills Table
At the start of a track, participants complete a brief exercise that establishes what they can do before it begins. At the end, they revisit comparable tasks. This creates a concrete record of what changed, not just a list of topics attended.
A Plain Statement of What We Do Not Provide
Every track page includes a written list of things the school does not offer — employment connections, accredited credentials, salary projections, placement services. We include this because we think clarity about scope is more useful than silence on the subject.
Four Years of Measured Progress
38+
COHORTS RUNWeekend, Weekday and Team programmes since 2021
420+
PARTICIPANTSIndividual learners across all track types
19
TEAM PROGRAMMESDelivered to engineering teams in Malaysia since 2022
7
INSTRUCTORSWith backgrounds in applied ML, software engineering and data science
See Which Track Matches Your Situation
Send an enquiry with a brief description of your background and schedule. We will point you to the right track and the next available intake.
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