AI Orchestration Course in Hyderabad

Module 1: Workflow Thinking and Use-Case Scoping

Identify the user, task, source data and measurable acceptance criteria. Decide which steps should use ordinary code and where a model may help. Practice: write a workflow brief with an explicit stop condition and a manual fallback.

Module 2: Python, JSON and API Readiness

Use functions, dictionaries, exceptions, virtual environments and environment variables. Read JSON responses and handle missing fields. Practice: call a sample API, validate its response and keep credentials outside source code.

Module 3: Model Calls and Structured Outputs

Separate system instructions, user inputs and retrieved content. Define a schema for classification or extraction and validate returned fields. Practice: turn a support request into a typed record without treating generated text as trusted code.

Module 4: Tool Contracts and Permission Boundaries

Describe tool inputs, outputs, allowed actions and failure responses. Distinguish read-only lookups from actions that change external systems. Practice: build a restricted lookup tool and reject invalid or unauthorized arguments.

Module 5: Sequential Workflows and Prompt Chains

Break a task into small steps with inspectable intermediate outputs. Pass only the context the next step needs. Practice: extract facts, draft a response and check it against a rubric, with a clear error path at every stage.

Module 6: Routing, Branching and Parallel Steps

Choose routes using rules or a validated model decision. Combine independent results and define what happens when one branch fails. Practice: route incoming requests to a knowledge lookup, an account query or a human queue.

Module 7: LangGraph State and Execution

Represent a workflow using state, nodes and edges. Make state changes explicit and inspect the route taken by a request. Practice: implement a small stateful workflow and compare its behavior with a simpler Python baseline.

Module 8: Retrieval as a Workflow Component

Prepare permitted documents, retrieve relevant passages and carry source references into the answer. Add an insufficient-evidence route. Practice: answer a question with citations or explain why the available documents cannot support an answer.

Module 9: Human Approval and Escalation

Pause before sensitive actions and show the reviewer the proposed action and supporting context. Handle rejection, changed inputs and expired approvals. Practice: review an outbound response before a mock send step is allowed.

Module 10: Persistence, Retries and Recovery

Distinguish transient failures from invalid requests. Set retry limits, timeouts and idempotency keys for side effects; understand checkpoint recovery. Practice: resume an interrupted run without creating a duplicate action.

Module 11: n8n and Business-System Integration

Connect triggers, webhooks, data transformations and an AI step in a visual workflow. Keep credentials scoped and test integrations using sample data. Practice: send a structured result to a test destination with an approval branch.

Module 12: Bounded Agents and Multi-Agent Patterns

Compare a fixed workflow, a single tool-using agent and a multi-agent arrangement. Use a handoff only when responsibilities are genuinely different. Practice: add a specialist review step with a task boundary, iteration limit and final owner.

Module 13: Evaluation and Failure-Case Testing

Create a small evaluation set covering normal inputs, ambiguity, missing data, tool failures and adversarial text. Compare task completion, factual support and unauthorized-action attempts. Practice: keep a before-and-after test report.

Module 14: Tracing, Cost and Latency

Inspect model calls, tool calls and state transitions. Redact sensitive data in traces and identify repeated work. Practice: measure run time and token usage, then reduce unnecessary calls without weakening the acceptance checks.

Module 15: Deployment and Operational Controls

Package the application with configuration, access controls, health checks and usage limits. Separate development and production credentials. Practice: demonstrate a controlled deployment and write a rollback and resource-cleanup checklist.

Module 16: Capstone, Documentation and Handover

Bring the workflow together in one scoped project. Submit the architecture, reproducible setup, evaluation evidence and known limitations. Practice: demonstrate a successful run, a failed run and the recovery path in a short technical presentation.