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ONESOFT

9

QA Engineering: Data, UX & Product Quality

550 000 ₸
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Allocated 22 Quotas

About course

More on ONESOFT

Testing is one of the most popular entry points into the IT sector, and by 2026, this role will no longer be about ‘clicking buttons’, but about product thinking, AI tools and working with data. The programme combines the core QA engineering (test design, Jira/TestRail, REST/SOAP/Postman, iOS/Android mobile testing) with four new modules: AI Engineering (Prompt Engineering, test case generation via LLM), Product Thinking (User Stories, metrics, Risk-Based Testing), UX/UI Audit (Nielsen’s heuristics, WCAG 2.2) and SQL for data validation. The course’s main feature is its own simulator in the form of a web application, where you practise test cases, bug reports, UI audits and SQL using scenarios that closely resemble real-world work. 67% of the course is spent on practical work in the simulator, analysing real-world cases from e-commerce, banking and mobile apps, and group work on Miro. The course is taught by 7 active industry professionals: Head of QA, Head of Academy, QA Team Lead, and an Automation QA specialist with experience in AI testing of LLM applications. By the end of the course, you’ll be a Junior/Junior+ QA Engineer with a ready-to-go capstone portfolio (test plan, AI-generated test cases, bug reports, UX audit, SQL checks) and interview-ready skills.

Special condition

Financial terms: the majority of the cost is covered by a government voucher; the remaining amount of 150,000 ₸ is paid by the participant themselves, is not included in the funding amount and is non-refundable. Penalties of up to 200,000 ₸ (up to 50% of the funding amount) apply in the following cases: withdrawal from the course without a valid reason, systematic breaches of academic discipline, or breaches of the terms of the contract or legal regulations.

Course details

level

For all

Study format

Online

Entrance exams

No

Duration, in weeks

28

Education language

Russian

Qualifications

junior

Skills


After the course you can: 🔧 QA Engineering core - work in SDLC/STLC and Agile/Scrum/Kanban - apply test design techniques: equivalence classes, boundary values, decision tables, pairwise, state transition - create test plans, test cases, checklists, bug reports, traceability matrices - work with Jira (workflow, JQL, dashboards) and TestRail - test REST/SOAP APIs in Postman - test mobile apps on iOS and Android (Xcode, Android Studio, Charles, Fiddler) - work with HTTP, OSI, Chrome DevTools, Cookies/LocalStorage 🤖 AI Engineering - use LLMs in QA work (understanding limitations and privacy) - apply prompt frameworks: CRISPE, RTF, COSTAR, chain-of-thought - generate test cases, test data, and bug reports with AI - build your own QA Engineer Promptbook 📈 Product Thinking - write User Stories (INVEST) and Acceptance Criteria (Given-When-Then) - work with product metrics (North Star, AARRR, HEART) and QA metrics (defect leakage, MTTD/MTTR) - prioritize using RICE, MoSCoW, ICE, Kano - apply Risk-Based Testing and estimate effort 🎨 UX/UI auditing - apply Nielsen's 10 heuristics and the laws of Hick/Fitts/Miller - run UI audits and form testing - perform cross-browser and cross-device testing - check interfaces against WCAG 2.2 using axe DevTools, Lighthouse, WAVE 🗄 Data Analytics with SQL - write SELECT, filters, JOINs, aggregations, subqueries - validate data and calculate product metrics with SQL

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