What Learners Say, in Their Own Words
We do not edit these for polish. We share them because they are an honest reflection of what studying at Akal Academy is actually like.
Back to Home340+
Learners enrolled
4.7/5
Average satisfaction
92%
Course completion rate
1 day
Tutor response time
From the Learners Themselves
Zulaikha Amin
Kuala Lumpur · HR professional
"I had no background in data at all. The Foundations course was the first time AI felt like something I could actually understand rather than just be impressed by. The exercises were harder than I expected, but the tutor was patient and specific in her comments. I am now mid-way through the ML course."
June 2025 · Foundations of AI and Data
Rajan Krishnan
Penang · Software developer
"I had tried two other ML courses before this one. Both moved quickly and left me copying code I did not really follow. The Machine Learning Essentials course here is slower, but that is the point. By week six I was actually reasoning about why a model performed the way it did, not just hoping the numbers looked right."
May 2025 · Machine Learning Essentials
Nurul Tasya
Shah Alam · Finance analyst
"What I appreciated most was that the course description matched what was actually inside. I have enrolled in courses elsewhere that promised things they did not deliver. Here, the tutor told me in our pre-enrolment conversation that it would be challenging — and she was right. But the feedback kept me on track."
June 2025 · Foundations of AI and Data
Chan Hoong Kit
Johor Bahru · Data technician
"The Deep Learning course was the most demanding thing I have done as an adult learner. The capstone project pushed me to think independently in a way that previous coursework never did. Farouk's written review of my project was thorough — two pages of specific notes. That alone was worth the course fee."
May 2025 · Deep Learning and Language Models
Siti Puteri
Kuala Lumpur · Graduate student
"I had read some university-level material on machine learning before enrolling, so I thought the Foundations course might be too easy. It was not. The exercises revealed gaps I did not know I had — particularly around data preparation. I am glad I started there rather than jumping in at the ML course."
July 2025 · Foundations of AI and Data
Azlan Mokhtar
Selangor · Operations manager
"I was sceptical that an online course would be worth the time. The difference here is the tutor — Nurul responded to my question the next morning with a detailed explanation that addressed exactly where I was confused. That kind of support changes what learning feels like."
June 2025 · Machine Learning Essentials
How Some Learners Worked Through the Courses
Zulaikha worked in HR and wanted to understand how AI tools were beginning to affect her field. She had no coding background and had found most online explanations either too technical or too vague.
She began with the Foundations course and took it steadily over the six weeks, spending around seven hours per week. The tutor helped her interpret the data exercises in HR-relevant terms, which kept the material grounded.
By the end, she could read data reports critically and identify when visualisations were misleading. She enrolled in the ML course the following month and is continuing through the sequence.
Chan had been working with structured data in his role but had no experience with machine learning. He had tried a popular online ML course but struggled when the material moved past model fitting without explanation.
He enrolled directly in ML Essentials after a pre-enrolment conversation confirmed he had the Python foundation needed. Over ten weeks, he submitted six exercises and received detailed written notes on each.
He completed the course with a solid understanding of model evaluation — how to interpret results and where common metrics can give a misleading picture. He applied these skills to a project at work within two months.
Rajan had completed the first two Akal Academy courses and wanted to develop a working understanding of how transformer models operate — without just using them as black boxes through an API.
The Deep Learning course covered neural network fundamentals before moving to attention and transformers. His capstone project was a small text classification system that he built and evaluated over the final four weeks, with mentor feedback at each stage.
He completed the capstone with a working model and a mentor review that identified two architectural choices he had not fully justified. The process of responding to that feedback was, he noted, more useful than the coding itself.
Reach Us Directly
Phone
+60 3-5518 7263Location
Shah Alam, Selangor
Office Hours
Mon–Fri 9am–6pm
Considering Enrolling?
Send us a message and we will help you find the right starting point and tell you honestly what to expect.
Get in Touch