<TL/> Tensorloom
AI development workspace
▸ read the syllabus first — enrolment follows from fit

Build AI Systems
From First Principles

Tensorloom runs structured courses on machine learning engineering for people who write code and want to understand what they are building. Syllabus, assessment rubric, and workload estimates published up front.

+60 3 5628 9174
[email protected]
Bangsar, Kuala Lumpur
View Courses & Enrol

Our Courses

Three courses, defined scope

Each course has a published syllabus, weekly contact hours, assessment method, and prerequisites. The school will say plainly if a course is not the right fit.

python_ml_practice.py RM 980
Python for Machine Learning
010203040506

Python for Machine Learning Practice

Eight weeks. Entry course for people who write some code but have not worked with numerical libraries. Covers NumPy, pandas, vectorisation, notebook discipline, and environment management.

  • ›3 contact hours / week
  • ›5 hrs exercises / week
  • ›Weekly graded notebooks
  • ›Data-cleaning project
  • ›Written completion record
ASSESS: Weekly graded notebooks + short project
PREREQ: Readiness quiz required before enrolment
CERT: Written record of completion issued
Request Enrolment
deep_learning_systems.py RM 3,200
Deep Learning Systems
010203040506

Deep Learning Systems

Fourteen weeks. Building and training neural networks with intent. Covers backpropagation, initialisation, convolutional and attention-based architectures, distributed training, profiling, and reproducibility.

  • ›6 contact hours / week
  • ›10–12 hrs lab / week
  • ›4 laboratory reports
  • ›Published-result reproduction
  • ›Compute sandbox provided
ASSESS: 4 lab reports + reproduction of published result
COMPUTE: Sandbox environment for course duration
SOURCE: All references cited by name
Request Enrolment
employer_cohort.py RM 4,700 / cohort
Employer Cohort
010203040506

Employer Cohort with Project Supervision

Twenty weeks. Deep learning syllabus combined with supervised work on an internal problem. Scoping workshop, weekly cohort sessions, fortnightly code review, midpoint architecture review, and documentation handover.

  • ›Up to 12 engineers
  • ›Fortnightly code review
  • ›Midpoint architecture review
  • ›Staging deployment supervision
  • ›2 post-completion clinics
SCOPE: Standard 12-seat cohort engagement
NOTE: School supervises engineering practice
SYSTEMS: Employer retains production responsibility
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Why Tensorloom

What makes the workbench different

Syllabus published before enrolment

Every course lists its topics, session structure, prerequisites, and assessment method. You read it before committing, not after.

Assessment by doing, not memorising

Graded notebooks, lab reports, and project work replace multiple-choice tests. Evaluation is on what you build and what you write about it.

Compute provided where needed

The Deep Learning Systems course includes a sandbox environment for the full duration. You work on real hardware without arranging it yourself.

Sources named in the syllabus

Where course material draws on published research, the paper is cited by name. You can read the original. Nothing is presented as proprietary knowledge.

Readiness check, plain response

The entry course uses a published quiz to assess fit. If the course is not right for where you are now, the school will say so directly.

Employer cohort against real work

The cohort programme works on a problem the employer brings, reviewed against the employer's own repository. Teaching does not happen in a vacuum.

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Which course fits your workload?

Send a message with your current experience level and which course you are looking at. We will review the readiness quiz with you and confirm whether the course schedule suits your availability.

Get in Touch
+60 3 5628 9174
[email protected]

// faq

Common questions

Do I need a degree to enrol in Python for Machine Learning Practice?
No degree requirement. The course is for people who already write some code — in any language — but have not worked with Python's numerical libraries. Applicants take a published readiness quiz beforehand. The result tells both you and the school whether the starting point is a good match for the course pace.
What does "contact hours" mean in practice?
Contact hours are the scheduled sessions where you attend instruction — live or recorded — with an instructor present or available for questions. They are separate from the exercise and lab hours listed alongside each course. The total time commitment per week is the sum of both figures.
Is the Deep Learning Systems course taught online or in-person?
Tensorloom is an online school. Sessions are conducted remotely. Laboratory work is done in the provided compute sandbox, which you access from your own machine. The school is based in Bangsar, Kuala Lumpur, and in-person arrangements for individual sessions can be discussed on request.
What do you mean by "reproduction of a published result" in the Deep Learning course?
The final assessment asks you to take a published research paper — one assigned or approved by the instructors — and reproduce its main training result within an agreed tolerance, using the methods described in the paper. You document your process, where you deviated, and why. The emphasis is on understanding what you are doing, not on achieving a particular benchmark score.
How does the Employer Cohort pricing work?
The RM 4,700 figure reflects a standard twelve-seat cohort engagement over twenty weeks. Cohorts with fewer seats or different scope are priced separately after a scoping workshop with engineering leadership. The school invoices the employer directly; individual engineers do not manage payments.
What happens to data I submit through the contact form?
Contact form submissions are used to respond to enquiries and, where you have agreed, to send relevant course updates. Data is held in accordance with the school's Privacy Policy, which follows PDPA (Personal Data Protection Act 2010, Malaysia). The full policy is linked at the bottom of the form.
Is there a refund if the course is not a good fit after it starts?
Refund terms are set out in the Terms and Conditions linked below. In general, a partial refund is available if a withdrawal request is received before a specified point in the course, which varies by programme. The readiness quiz is there precisely to reduce the chance of mismatch before fees are paid.

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Find Us

68 Jalan Kemuja, 59000 Bangsar, Kuala Lumpur

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Send an Enquiry

Tell us which course interests you and your current experience level. We'll follow up within one business day.

Contact Details

Address

68 Jalan Kemuja
59000 Bangsar
Kuala Lumpur, Malaysia

Office Hours

Monday – Friday: 9:00 am – 6:00 pm
Saturday: 10:00 am – 2:00 pm
Sunday: Closed

RESPONSE: Within 1 business day
LANG: English (Bahasa Malaysia on request)
SCOPE: Individual and employer enquiries welcome
enquiry_form.py

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