Diplomas
Diploma in Machine Learning & Deep Learning
A deep specialisation for those who want to build models, not just use them
- On campus
- Hybrid
- Employment rate: 86%
Fees
- Duration
- 18 months
- Total hours
- 700 training hours
- Credit hours
- 46
- Next intake
- 1 March 2027
Overview
If you already know how to program and want to specialise at the core of the field, this diploma takes you from the mathematics behind backpropagation to fine-tuning large models. The emphasis is deep understanding: why does training stall? why does a model collapse on new data? how do you read a loss curve the way a radiologist reads a scan? Graduates can read a recent research paper and implement it.
Deep learning engineers are among the highest-paid groups in the technology market, because combining theoretical understanding with practical ability is rare.
Learning outcomes
- Build neural architectures from scratch and understand every component
- Diagnose training problems and read performance curves
- Fine-tune large language models at reasonable cost
- Read a recent research paper and implement its idea
- Optimise inference latency and operating cost
Curriculum
Semester 1 — Mathematical & Algorithmic Base
Semester 2 — Deep Architectures
Semester 3 — Scaling & Capstone
Capstone project
An applied research project: you pick a recent paper, reproduce its results, then extend it to a local use case. The final output is a published model with a technical report suitable for publication or for presenting to a specialised employer.
Graduate projects galleryTarget roles
Admission requirements
- Prior programming background (Python at minimum)
- Familiarity with linear algebra and probability basics
- Passing the technical placement test
Required documents
- ID or residency copy
- Latest qualification certificate
- CV
- GitHub link if available
Fees & instalments
36,000SAR
- Published fees include learning materials, assessment fees and the certificate.
- Diplomas can be paid in interest-free semester instalments; courses support monthly instalments via Tabby and Tamara.
- A merit scholarship of up to 30% for applicants with a high previous qualification average.
- mada
- Visa / Mastercard
- Apple Pay
- Tabby — instalments
- Tamara — instalments
- Bank transfer
Program faculty
Dr. Lama Alharbi
PhD in Computer Science; led machine learning teams in digital retail before moving to teaching full time. Believes a curriculum without an applied project is just a summary.
Eng. Sara Alqahtani
Computer vision engineer who worked on visual inspection systems in industrial production lines, with published work in pattern recognition.
Eng. Abdullah Alzahrani
Built Arabic AI assistants for government entities and service companies; focused on rigorous output evaluation rather than demos.
Frequently asked questions
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