What Students Actually Say

Real feedback from learners who've worked through our deep learning programs. Not cherry-picked highlights—just honest perspectives on what worked and what challenged them.

How We Collect Student Feedback

We gather responses through multiple channels throughout the year. Here's how we make sure every voice gets heard—and what we do with that information once it arrives.

1

Mid-Program Check-Ins

Around week six, we send out a quick survey. Nothing fancy—just seven questions about what's clicking and what isn't. Takes about five minutes to fill out, and we actually read every single response.

2

Post-Completion Conversations

Two weeks after graduation, we reach out for a longer chat. Some people write paragraphs, others prefer a phone call. Both work fine. We want to know what stuck with you and what you'd change if you could rewind.

3

Six-Month Follow-Up

This one's optional, but most people respond anyway. Once you've had time to apply what you learned—or realize you needed something different—your perspective shifts. That's the feedback that shapes our next batch of courses.

4

Anonymous Channel Always Open

Sometimes you need to say something without your name attached. We get it. There's a permanent feedback form linked in every course dashboard. No login required, no tracking. Just type and hit send.

Students reviewing course materials and sharing feedback during group discussion

Common Themes from 2024-2025

We've gone through hundreds of responses from the past year. Some patterns keep showing up—both positive notes and areas where we clearly need to improve.

What People Appreciated Most

The pacing came up a lot. Not too rushed, not dragging. People liked having time to actually absorb concepts before moving forward. The project-based approach also got consistent praise—building something real beats watching lectures any day.

  • Instructors who answer questions within 24 hours, even on weekends
  • Code examples that don't assume you already know everything
  • The debugging sessions where we work through actual student errors
  • Having access to course materials forever, not just during the program

Where We're Making Changes

Several students mentioned wanting more guidance on setting up local environments. Fair point—we've added a pre-course setup guide launching in September 2025. Also working on better transitions between modules, since a few people felt lost moving from basic neural networks into convolutional architectures.

Portrait of Isla Thornley, program coordinator
Isla Thornley

Student Experience Coordinator

"I read every piece of feedback that comes through. Some days it's encouraging, other days it's humbling. Both matter equally."

Direct Quotes Worth Reading

We asked if we could share some recent feedback publicly. These three people said yes. Nothing edited except fixing a few typos.

Deep learning training environment with multiple workstations and collaborative learning spaces

From a Career Switcher in Taipei

"I came from graphic design with basically zero programming background. First two weeks were rough—I won't lie. But the mentors never made me feel stupid for asking basic questions. By month three, I'd built a simple image classifier that could tell my cat apart from my friend's cat. Sounds silly, but that moment made everything click."

She went on to complete the full program in October 2024 and now works on computer vision projects for a local e-commerce company. Not instant success, but steady progress that actually led somewhere.

"The curriculum didn't promise I'd become an expert in twelve weeks. It promised I'd understand the fundamentals well enough to keep learning on my own. That's exactly what happened."

Student engaged in hands-on deep learning project work with instructor guidance

From Someone Who Didn't Finish

"I made it through five modules before life got complicated and I had to step away. Here's the thing though—I still use what I learned in those five modules almost every week at my current job. The refund policy was fair, and they let me keep access to everything I'd already completed."

Honest feedback like this helps more than glowing reviews sometimes. Not everyone will finish, and that's okay. What matters is whether the time invested was worth it regardless of completion status.