Machine Learning Engineering
An intensive programme for people who already code and want to build production machine learning. You train models for vision, language and tabular data on the GPU-enabled lab at The AI Hub, learn to evaluate them honestly, and ship them as working services.
- Level
- Intermediate
- Duration
- 12 weeks
- Format
- In person at The AI Hub, Kano, with dedicated GPU lab time.
- Credential
- Certificate plus a deployed capstone project
What you will be able to do
- Build supervised and unsupervised models with scikit-learn
- Train deep learning models in PyTorch on GPUs
- Evaluate models for accuracy, fairness and drift
- Deploy models behind an API and monitor them
Who it is for
- Software developers
- Data analysts
- Engineering and science graduates
Before you start
Working Python. Completing Python for Data Science meets this requirement.
Curriculum
- 01
Classical machine learning
Regression, classification, trees and ensembles.
- 02
Deep learning with PyTorch
Neural networks, training loops and GPUs.
- 03
Computer vision
Image classification for agriculture and health use cases.
- 04
Natural language processing
Text models for English and Hausa.
- 05
MLOps
Packaging, serving, monitoring and retraining.
- 06
Capstone
An end-to-end deployed model, presented to industry reviewers.
Fees, dates and sponsorship
Apply and admissions will send the current fee schedule, next start date and payment options. Organisations can sponsor learners or book a private cohort.