AI development courses for working developers
Short courses and a part-time programme covering language model APIs, fine-tuning, and machine learning engineering. Taught honestly — syllabus, workload and prerequisites stated plainly.
What we teach
Three focused offerings. Each one states its prerequisites and workload before you read anything else about it.
Working with Language Model APIs
RM 890 · 4 weeks · 2 hrs/session
Covers prompt structure, structured output, tool calling, streaming, token accounting, caching, retries, and evaluation. Every example is in plain functions — JavaScript or Python.
Prerequisite
You write JavaScript or Python professionally.
- Live sessions + recordings
- Reference repository included
- Evaluation harness you keep
- Written feedback on two exercises
Weekend Intensive: Fine-Tuning Small Models
RM 1,340 · 2 days · 6 hrs/day
Dataset construction, formatting, deduplication, parameter-efficient adaptation, hyperparameter choices that matter, evaluation, and knowing when fine-tuning isn't the right tool. Up to 16 participants.
Prerequisite
Comfortable with PyTorch basics.
- Sessions + recordings + notebooks
- Compute credit allowance included
- You leave with a trained adapter
- Written review of your eval report
Machine Learning Engineering Programme
RM 4,600 · 20 weeks · ~12 hrs/week
Data pipelines, feature stores, experiment tracking, reproducible training, model serving, latency profiling, canary releases and drift monitoring. 70% project work; three reviewed projects plus a capstone.
Prerequisite
Professional software experience and Python familiarity. A short technical conversation before enrolment.
- Twice-weekly live sessions
- Three reviewed projects + capstone
- Line-by-line written reviews
- Mentor office hours + cohort channel
→ output: you know what each course covers, what it costs, and whether you're eligible to join.
How we run things
A few things that shape how every course and programme at Neuralaya is structured.
Prerequisites stated plainly
Every course lists what you need to know before joining. No vague "beginner-friendly" language that wastes your time.
Honest workload estimates
Hours per week are stated as numbers, not adjectives. You can check whether the schedule fits your situation before you commit.
Working code, not slides
You leave each short course with a repository or notebook you wrote and can run. Long programme learners ship three reviewed projects and a capstone.
Written feedback, not grades
Reviews are written by practising engineers and go line by line. A number tells you nothing useful; a paragraph on why a function is structured badly does.
What we deliberately leave out
Each course includes a "not covered here" section. Scope boundaries are stated so you can decide whether a course fits what you're trying to learn.
Small cohorts
The weekend intensive caps at 16. The programme has a cohort channel and office hours. You are not watching a recording alone.
Not sure which course fits your situation?
Send us a message with where you are technically and what you're trying to build or learn. We'll describe which course makes sense and why — no pressure to enrol.
Common questions
Do I need a machine learning background to join the API course?
Are sessions recorded if I miss one?
What does the technical conversation before the programme look like?
Is a certificate issued on completion?
Can my company pay for a course?
How is the ML Engineering Programme different from a short course?
What data do you collect when I enquire?
Find Us
Get in touch
Contact details
Phone
+60 4-261 9473Address
72 Lebuh Chulia
10200 George Town
Pulau Pinang, Malaysia
Office hours
Monday – Friday: 10:00 – 18:00 MYT
Saturday: 10:00 – 14:00 MYT
Sunday: Closed
[response_time, typical]
We aim to reply to all enquiries within one working day. For the ML Engineering Programme, we'll also schedule a short technical conversation before confirming a place.