GitHub Certified - Agentic AI Developer with Practice Exam

+ D0 - Welcome from Alex Kropf 1 lecture

00.01 Welcome and Project Files Locked

+ Domain 1 - Prepare agent architecture and SDLC processes (15-20%) 1 lecture

Welcome to Domain 1 Locked

+ 01.01 Integrate agents into the software development lifecycle 3 lectures

01.01a Identify steps for agents to perform Locked

01.01b Identify and mitigate common antipatterns in agents Locked

01.01c Define inputs outputs and success criteria for agents Locked

+ 01.02 Define boundaries between planning, reasoning, and action 5 lectures

01.02a Configure agent planning to be distinct from agent execution Locked

01.02b Configure an agent to output a structured plan Locked

01.02c Validate agent plans Locked

01.02d Prevent agent action until the agent checked and approved Locked

↔️ Agent Frontmatter Fields Preview Free preview

+ 01.03 Configure observability and control for autonomous agents 4 lectures

01.03a Plan and implement the degree of agent autonomy Locked

01.03b Configure agent to produce inspectable artifacts Locked

↔️ Hook Events Locked

↔️ Hook Tools Locked

+ Domain 2 - Implement Tool Use and Environment Interaction (20-25%) 1 lecture

Welcome to Domain 2 Locked

+ 02.01 Select and configure agent tools 4 lectures

02.01a Identify required tools Locked

02.01b Configure agent tools Locked

02.01c Configure agent tool permissions Locked

↔️ Agent Tools Locked

+ 02.02 Configure MCP servers 5 lectures

02.02a Add an MCP server as a tool to an agent Locked

02.02b Configure a GitHub remote MCP server Locked

02.02c Configure MCP registries Locked

02.02d Configure MCP allow lists Locked

↔️ GitHub Copilot Files and Directories Locked

+ 02.03 Integrate agents within development environments 8 lectures

02.03a Evaluate the execution context for an agent Locked

02.03b Configure an agent's scope to a specific repository Locked

02.03c Configure an agent to be invoked in a CI workflow Locked

02.03d Configure an agent to use branchbased scope Locked

02.03e Enable an agent to perform autonomous actions Locked

02.03f Configure an agent to handle environmentspecific constraints Locked

↔️ GitHub Copilot CLI Commands Locked

↔️ GitHub Copilot CLI Flags Locked

+ 02.04 Operate agents with safe execution paths and robust error handling 6 lectures

02.04a Implement error handling Locked

02.04b Implement retries Locked

02.04c Implement rollbacks Locked

02.04d Implement escalation paths Locked

02.04e Implement traceability and accountability for agent actions Locked

↔️ GitHub Copilot CLI Slash Commands Locked

+ Domain 3 - Manage Memory, State, and Execution (10-15%) 1 lecture

Welcome to Domain 3 Locked

+ 03.01 Implement agent memory strategies 3 lectures

03.01a Choose between shortterm longterm and external memory Locked

03.01b Scope agent memory to taskrelevant information Locked

03.01c Define memory expiration pruning and reset rules Locked

+ 03.02 Persist agent state and manage context drift 3 lectures

03.02a Capture task progress and decisions as durable artifacts Locked

03.02b Resume agent work without repeating steps Locked

03.02c Detect and correct drift during extended agent execution Locked

+ 03.03 Ensure continuity of agent memory and state 4 lectures

03.03a Share agent state Locked

03.03b Prevent conflicting context Locked

03.03c Prevent stale context Locked

↔️ Copilot CLI Paths Locked

+ Domain 4 - Perform Evaluation, Error Analysis, and Tuning (15-20%) 1 lecture

Welcome to Domain 4 Locked

+ 04.01 Define success criteria and evaluation signals 5 lectures

04.01a Specify expected outcomes and operational constraints Locked

04.01b Identify qualitative and quantitative evaluation signals Locked

04.01c Align evaluation criteria with development intent Locked

04.01d Generate evaluation signals by using automated scanning tools Locked

↔️ Evaluation Signals Locked

+ 04.02 Analyze agent failures and identify root causes 2 lectures

04.02a Identify failures Locked

04.02b Classify root causes Locked

+ 04.03 Tune agent behavior based on evaluation results 2 lectures

04.03 Tune agent behavior based on evaluation results Locked

↔️ Agent Symptom & Fix Locked

+ Domain 5 - Orchestrate Multi-Agent Coordination (15-20%) 7 lectures

05.01a Apply an orchestration pattern to coordinate multiple agents Locked

05.01b Configure agent isolation for parallel execution Locked

05.01c Detect and resolve agent conflicts Locked

05.02 Configure observability for multiagent behavior Locked

05.03 Detect and respond to multiagent failures Locked

05.04 Manage the lifecycle of agents within multiagent workflows Locked

↔️ Agent Coordination Patterns Locked

+ Domain 6 - Implement Guardrails and Accountability (10-15%) 3 lectures

06.01 Define autonomy levels Locked

06.02 Implement guardrails and humanintheloop workflows Locked

↔️ Agent Control Types Locked

+ D7 - Challenge Your FREE Practice Exam 2 lectures

07.01 Where to go from here Locked

07.01 Where to go from here Locked