API Testing & Automation Training in Pune with Placement

The mental model everything else depends on. Client-server architecture, what an API actually is, web services, and REST as an architectural style rather than a synonym for JSON over HTTP — including an honest comparison with SOAP, which still runs in plenty of Indian banking and insurance systems.

Then HTTP itself, in the detail a tester needs: the request and response anatomy, methods and their idempotency, status codes and what each class actually promises, headers, query and path parameters, and cookies. JSON and XML close the module, since those are the payloads you will spend two months asserting against.

Postman used the way a professional tester uses it, not the way a tutorial demonstrates it. Installation and setup, then building requests across every method — GET, POST, PUT, PATCH, DELETE — with headers, query parameters and request bodies constructed deliberately.

Response validation covers status, headers, body and response time. Then the organisational layer that separates a working tester from someone clicking Send: collections that model a real API surface, environments for dev, staging and production, and the variable hierarchy — global, collection, environment and local — which is the thing most people get subtly wrong and then debug for an hour.

The subject that blocks more new API testers than any other, because every real API is protected and every protection scheme works differently. Basic authentication and why it survives only behind TLS, API keys and where they belong in a request, and Bearer tokens.

JWT gets proper treatment — structure, claims, expiry and what a tester can and cannot verify from a token — followed by OAuth 2.0 and its grant types, including the authorisation-code flow you will meet most often. The module ends on the distinction that produces the most severe real defects: authentication testing (are you who you claim) versus authorisation testing (are you allowed to do this).

Turning a collection into an executable regression suite without leaving Postman — the step that makes API testing repeatable for testers who are not yet writing framework code.

Postman scripting with JavaScript: pre-request scripts for setup and token acquisition, and test scripts with `pm.test` assertions against status, schema and body. Variables carry values between requests, dynamic data handles timestamps and unique identifiers, and request chaining lets one call feed the next — create a resource, capture its id, use it, delete it. The Collection Runner then executes the whole suite, including data-driven runs from CSV or JSON.

Reading the specification is the fastest route to good test coverage, and most testers never learn to do it properly. Swagger and the OpenAPI specification: how an API describes its own paths, parameters, request bodies, responses and schemas.

The module teaches you to derive test cases directly from a spec — every enum is a set of valid values and an invalid one, every required field is a negative case, every documented status code is an expected outcome. Testing APIs straight from Swagger UI, API contracts, and request and response schemas close it, setting up the schema validation and contract testing that arrive in Module 7.

The module where you stop clicking and start engineering. You pick one of three stacks and build a real framework in it: Rest Assured with Java if you are heading for Java teams, Python Requests with PyTest if you prefer Python or already know it, or Playwright API testing with TypeScript if you also want UI automation in the same tool. The concepts are identical across all three, so the choice is about your target job, not difficulty.

Request and response specifications remove repetition, serialisation and deserialisation map payloads to data models, and assertions verify structure as well as values. Then the framework layer: parameterisation and data-driven testing, reusable API clients, configuration management, authentication handling in one place, logging, reporting, and an architecture a new joiner can navigate.

The coverage that separates a competent API tester from a thorough one. Schema validation asserts the shape of a response, not just its values — the check that catches a backend change before it breaks three consumers. Contract testing extends that between services.

Then the cases that matter and get skipped: negative testing, boundary testing, error handling and error-response consistency, rate-limit behaviour, pagination correctness across page boundaries, and file-upload APIs. Database validation confirms that a successful response actually persisted what it claimed, and end-to-end API workflows chain multiple services into the business flows a user would recognise.

Two adjacent disciplines at the depth a QA engineer is actually expected to own. On performance: validating response times against a stated budget, basic load testing to see how an endpoint behaves under concurrency, and rate limiting as both a functional behaviour and a protection mechanism.

On security: authentication vulnerabilities, authorisation issues including the broken-object-level-authorisation defect that dominates real API breaches, input validation, injection testing, and sensitive data exposure in responses and logs — framed by the OWASP API Security list. This is a tester's working grounding, deliberately not a penetration-testing course.

Making the suite run without you. Git and GitHub for automation projects — branching, pull requests and review applied to test code — then Newman, which runs a Postman collection from the command line and is the bridge that lets non-framework work still run in CI.

Jenkins and GitHub Actions cover the pipeline itself: triggering on push and pull request, environment-based execution so the same suite runs against dev, staging and production with different variables, secret handling for tokens, scheduled regression runs, and publishing test reports where a delivery manager can read them.