Current
Intermediate
AI Engineering: Agents
Weights & Biases · Weights & Biases · Updated March 2026
Platform rating
4.6/5
AI Tutor Rating
8.6/10
Duration
2 hours
Classes
6
Short practical course on architecting and evaluating production-grade AI agents with tools, memory, orchestration, and MCP concepts.
What you'll get
Design reliable single-agent and multi-agent architectures
Integrate tools, memory, and retrieval patterns
Benchmark agents across accuracy, latency, and cost
Apply MCP-aware interoperability patterns
Fit
Best for
Developers
AI Engineers
Data Scientists
Technical Builders
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Basic LLM app development recommended
Pricing
Free
Certification
No
Growth Leverage: Completing this course opens opportunities for roles such as AI Engineer, ML Ops Specialist, or Technical Architect, focusing on AI agent development. It enhances qualifications for certifications in AI architecture and interoperability standards, positioning candidates for advanced projects in tech firms or AI startups.
Skills Value: Skills from this course enable tackling complex issues in AI agent integration and optimization, highly sought after in industries like finance and healthcare. Employers are willing to pay a premium, often 15-20% above average salaries, reflecting the growing demand for expertise in AI agent architecture.
AI Agents
Multi-Agent
MCP
Agent Evaluation