Software Testing Course in Mumbai with Gen AI

Order entry is where test design starts. Price bands and lot sizes give you boundaries to probe; market, limit, stop-loss, and AMO orders form equivalence classes; margin rules fit a decision table; and an order's journey from placed to executed, part-filled, or rejected becomes a state transition diagram. Smoke, sanity, regression, and exploratory passes find real bugs, which you classify by severity and priority inside Jira.

A sprint from the tester's chair: sprint planning, the daily stand-up, sprint review, and retro, with every user story judged against acceptance criteria and a strict Definition of Done (DoD). Jira is set up for the trading app from scratch (Scrum board, custom workflows, saved JQL filters, QA dashboards), and your master test plan puts the riskiest financial flows first.

Databases, the way a QA engineer at a broker uses them. A schema of clients, orders, trades, and holdings teaches primary/foreign keys and constraints, followed by filtering, sorting, grouping, joins (INNER, LEFT, RIGHT), and nested queries. Each query has a mission: seeding mock test data or proving that a simulated stock purchase truly credited holdings and adjusted the ledger.

Programming tailored for people who have never coded before. Choose Python or Java. Start with data types, variables, conditionals, loops, functions, and Object-Oriented Programming (classes, encapsulation, inheritance, polymorphism, exception handling). The module ends with building a utility script that feeds client and order records from CSV, JSON, and Excel directly into your test suites.

Selenium WebDriver takes full control over the browser. Learn robust element location via dynamic XPath, CSS selectors, and element IDs. Replace arbitrary sleep pauses with explicit and fluent waits. Handle complex alerts, modal pop-ups, iframes, multi-window tabs, dynamic dropdowns, and interactive order-book data tables. Package scripts into modular PyTest or TestNG suites that execute across Chrome, Firefox, and Edge.

A fast crash course in modern TypeScript before diving into Microsoft Playwright. Experience user-centric locators (`getByRole`, `getByText`), auto-waiting assertions, reusable fixtures, stored browser authentication states to bypass repeated logins, network call mocking to simulate exchange server failures, file upload testing for KYC documents, parallel worker execution, and debugging via Playwright Trace Viewer.

Deconstruct the trading application's backend architecture. Master REST conventions: HTTP verbs (GET, POST, PUT, DELETE, PATCH), resource endpoints, custom headers, query/path parameters, and HTTP response status codes (200, 201, 400, 401, 403, 500). Build Postman collections, define environments, manage Bearer / JWT auth tokens, and write JavaScript assertions for schema and payload verification.

Transform Postman collections into production-grade automated code using Python Requests or Java REST Assured. Pass dynamic order IDs from one endpoint to the next, refresh authentication tokens automatically, and drive tests from external data files. Construct end-to-end integration tests chaining the client order API, mock exchange response, and PostgreSQL database verification into a unified test pipeline.

Learn to use Generative AI as an intelligent QA co-pilot. When complex new BFSI requirements arrive (e.g. intraday square-off margin limits), craft structured prompts to generate positive, negative, and edge test scenarios. Have AI synthesize large realistic sets of dummy client KYC profiles and order histories. Crucially, master data privacy protocols: understand which proprietary customer data and API keys must NEVER be input into public LLMs.

Coding alongside modern AI tools: pair programming with GitHub Copilot and ChatGPT inside VS Code. Generate boilerplate Page Object models, decode cryptic stack traces, refactor brittle XPath locators, and generate regex assertions. Learn the critical human-in-the-loop engineering standard: never commit or push AI-generated code to main without running, validating, and debugging it locally first.

Assemble standalone scripts into an enterprise-grade QA framework. Implement the Page Object Model (POM) architecture with clean separation of locators, test logic, and test data. Manage codebase versions with Git (feature branches, commits, pull requests, merge conflict resolution). Configure a Jenkins CI/CD pipeline triggered on every GitHub push, generating interactive Allure reports with step logs and automatic failure screenshots.

The grand finale: execute a complete, end-to-end quality assurance engagement on a simulated stock-trading application. You author the master test plan, write manual Jira test packs, script UI suites in Selenium & Playwright, automate REST API endpoints, seed SQL data, wire the suite into Jenkins, and generate Allure reports. Finally, you prepare to showcase it: resume rework, LinkedIn rebranding, public GitHub portfolio, and rigorous mock interview rounds.