advancedFree
Machine Learning with Graphs
by Jure Leskovec · Stanford Online
4.7(1,800 reviews)
80K+ enrolled10 weeksUpdated 2024-04
What You'll Learn
Understand the fundamentals and key concepts of graph neural networks
Apply graph neural networks techniques to solve real-world problems
Understand the fundamentals and key concepts of node embeddings
Apply node embeddings techniques to solve real-world problems
Understand the fundamentals and key concepts of knowledge graphs
Apply knowledge graphs techniques to solve real-world problems
About This Course
Stanford course covering graph neural networks, node embeddings, knowledge graphs, and community detection.
Curriculum
Module 1: Graph neural networks3 lessons
- Introduction to graph neural networks
- Graph neural networks in Practice
- Hands-on Exercise: Graph neural networks
Module 2: Node embeddings3 lessons
- Introduction to node embeddings
- Node embeddings in Practice
- Hands-on Exercise: Node embeddings
Module 3: Knowledge graphs3 lessons
- Introduction to knowledge graphs
- Knowledge graphs in Practice
- Hands-on Exercise: Knowledge graphs
Module 4: Deep learning3 lessons
- Introduction to deep learning
- Deep learning in Practice
- Hands-on Exercise: Deep learning
Instructor
Jure Leskovec
Instructor at Stanford Online
Pros & Cons
Pros
- Highly rated by students
- Completely free to access
- High-quality video lectures
- Taught by Jure Leskovec
Cons
- No certificate provided
- Requires significant prior knowledge
- Self-paced requires discipline
Free
Enroll Now