Graph Machine Learning
From classical algorithms to graph neural networks
About this program
Six months on machine learning over graphs. Cover classical graph algorithms, node embeddings, modern GNNs (GCN, GraphSAGE, GAT), heterogeneous graphs, and applications to fraud, drug discovery, and knowledge graphs.
Student ratings
Outstanding — 351 verified Canadian graduates rated this program 4.9/5. Reviews emphasize the applied capstone, instructor responsiveness, and career outcomes.
- 5★331
- 4★9
- 3★7
- 2★2
- 1★2
Who this program is for
- →Practitioners already shipping ml engineering work who want depth
- →Senior engineers, data scientists, and technical leads
- →Canadian residents seeking a verifiable diploma credential
Topics you'll cover
6 modules across 6 months — 24 lessons in total.
Full syllabus
Module 1 · Month 1 — Graph Foundations▾
- L1Graph data structures
- L2Classical algorithms
- L3NetworkX
- L4Lab: exploration
Module 2 · Month 2 — Node Embeddings▾
- L1DeepWalk, node2vec
- L2Matrix factorization
- L3Embeddings for downstream tasks
- L4Lab: fraud features
Module 3 · Month 3 — GNN Basics▾
- L1Message passing
- L2GCN, GraphSAGE, GAT
- L3Training tricks
- L4Lab: citation networks
Module 4 · Month 4 — Advanced GNNs▾
- L1Heterogeneous graphs
- L2Temporal GNNs
- L3Subgraph sampling
- L4Lab: large-scale graph
Module 5 · Month 5 — Applications▾
- L1Fraud and AML
- L2Drug discovery
- L3Recommendations
- L4Knowledge graphs + LLMs
Module 6 · Month 6 — Capstone▾
- L1Real graph problem
- L2Build and evaluate
- L3Production considerations
- L4Final review
What you'll be able to do
- ●Build production GNN models
- ●Use heterogeneous graphs
- ●Apply graphs to fraud and recommendation
- ●Combine LLMs with knowledge graphs
- ●Scale GNN training
Career paths after graduation
Frequently asked questions
How much does the Graph Machine Learning cost?▾
Tuition is $175 CAD, paid once. You can pay in full at checkout or choose an interest-free monthly plan. A 30-day refund window applies from your enrollment date.
How long is the Graph Machine Learning program?▾
Self-paced. Most students complete it in 6 months at roughly 8 hours per week, but you can go faster or slower — you keep lifetime access.
What are the prerequisites?▾
Python; Deep learning fundamentals
Is the diploma recognized in Canada?▾
Yes. Graduates receive the Altaris AI Academy Diploma in ML Engineering — a verifiable credential with a unique certificate number you can publish on LinkedIn and that any employer can verify at altarisai.org/verify.
What is the refund policy?▾
Full refund within 30 days of enrollment, no questions asked. After day 30, prorated refunds are available per our Refund Policy.
Who teaches the program?▾
Working Canadian AI practitioners — not academics. Every module is built and reviewed by a lead instructor working in the field today.
Students also enrolled in
More ML Engineering programs from Altaris.