AI Programming
Deep Learning with PyTorch
An advanced course on building, training and debugging neural networks with PyTorch.
AdvancedOn campus4.9(52)
4,900SAR
- Start date
- 7 December 2026
- Duration
- 6 days · 36 training hours
- Seats
- 4 / 16
4 seats left
A one-minute introduction from the trainer
Added after the recording session
Your trainer
Eng. Sara Alqahtani
Neural Networks & Computer Vision
Computer vision engineer who worked on visual inspection systems in industrial production lines, with published work in pattern recognition.
9 years of experience
Course outline
day by day
1
Days 1–2: PyTorch fundamentals
- Tensors and autograd
- Writing the training loop by hand
- Devices and acceleration
2
Days 3–4: Architectures
- Convolutional networks
- Transfer learning
- Data augmentation
3
Days 5–6: Debugging and project
- Reading loss curves
- Handling overfitting
- A complete classification project
What will you build?
- A custom image classifier on your own data
- A hand-written training loop
- An organised experiment report
Who is this course for?
- Anyone who finished the ML bootcamp
- An engineer specialising in deep learning
And who it is not for
- Complete machine learning beginners
Prerequisites
- • Prior machine learning experience
- • Strong Python
- • Linear algebra basics
Completion certificate
An accredited certificate with a QR verification code linking to your Thinkers Club profile.
INVEX
Accredited completion certificate
QRThe course includes
- 36 hours in a GPU-equipped lab
- Cloud training credit
- An accredited certificate
Trainee reviews
Writing the training loop by hand on day one changed how I understood everything that followed.
Nawaf Alanazi
Software Engineer
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