AI in Mobile QA

Name: AI in Mobile QA
Rating: 4.1 (3 reviews)

For QA about AI

Created byVladislav Kazachek

Last updated 5/2026

English

English [Auto],

What you'll learn

Use ChatGPT, Gemini, and AI agents in real QA workflows
Analyze requirements, documentation, and UI/UX with AI tools
Work with APIs, JSON, SQL, and Logcat without deep coding skills
Improve testing efficiency and reduce repetitive manual tasks with AI

Course content

5 sections • 20 lectures • 1h 50m total length

Introduction0:37
Lesson 1 Why Traditional QA Is Dying? Reducing TTM and a Survival Strategy in IT2:27
Transform traditional QA into quality architecture by leveraging AI to move quality left, accelerate tests to minutes, and let humans validate foundations, logic, and accountability.
Test Lessen 1
Lesson 2 Evolution of the Role: From "Executor" to "Validator" and Quality Archi2:27
Test 2
Lesson 3 The QA Delegation Matrix: 5 Criteria for Choosing Tasks for AI7:44
Test 3
Lesson 4 Shift Left and AI: A Strategy for Testing Requirements and Design Befor2:32
Shift-left testing with AI agents accelerates requirement and design validation before coding, using autonomous IE agents to reveal logical conflicts, UX risks, and design mismatches.
Test 4

Lesson 1 From Chatbots to Autonomous Agents: The Strategic Transformation of Mob8:31
Test 1
Lesson 2 Comparative Overview of Next-Generation AI Tools: Android Studio Gemini7:49
Test 2
Lesson 3 The Perfect Prompt Formula for Analytics: Context + Task + Format AI T8:41
Learn to transform QA with the perfect prompt formula—context, task, and format—and become an AI orchestrator who uses autonomous agents while guarding data security and ensuring human oversight.
Test 3
Lesson 4 Red Lines: What Must Never Be Shared with Public AI Tools8:25

Lesson 1 Reverse-Engineering Specs: Finding Logical Gaps and Contradictions10:25
Discover how AI-driven QA accelerates mobile testing by reverse engineering specs to uncover logical contradictions, audit visuals and code, and enforce golden rules of AI QA.
Lesson 2 Case Study: Detecting Hardcoded Data and Navigation Errors via LLM8:29
Explore how AI-powered QA accelerates mobile testing, from LLM-driven analysis to project-aware agents, using the CatApp case study to reveal semantic AI analysis, visual audits, and safety best practices.
Test 1
Practice: Working with project documentation using AI tools.0:37

Lesson 1 Pixel Perfect Audit: Using Computer Vision to Compare Figma Designs and2:18
Test 1
Lesson 2 The Stitch Tool: Prototyping Mobile Adaptations When No Design Exists7:49
Explore how the Stitch tool bridges ideas to mobile prototypes when no design exists, using precise prompts to turn web patterns into adaptable mobile interfaces, and integrate QA safeguards.
Test 2
Practice: Working with Figma designs and using AI tools to assist QA testers.0:16
Practice: Working with Figma designs and using AI tools to assist QA testers.

Before starting the next task, use the following material0:19
Lesson 1 Reading Code Without Programming Skills8:47
Test 1
Lesson 2 Data Manipulation: The SQL and JSON Revolution in Mobile Testing6:29
Test 2
Lesson 3 Decoding Logcat: Instant Root Cause Analysis of Crashes and Errors8:27
Decode logcat with AI to rapidly identify root causes of crashes in mobile apps. Cross-reference stack traces with manifest files and RCA prompts for actionable diagnoses and robust QA.
Test 3
Lesson 4 Data De-identification Methods and Working Within “Permitted Boundaries7:08
Test 4

Requirements

No programming experience is required
Basic understanding of software testing is helpful but not mandatory

Description

This course contains the use of artificial intelligence.

This course is designed for Manual QA Engineers, Mobile Testers, and IT professionals who want to integrate AI into their daily work and stay competitive in today’s software industry.

What You Will Learn:

AI Tools: Use Claude Code, ChatGPT, Gemini, and AI Agents for real-world QA tasks.
Requirement Analysis: Find logical gaps and inconsistencies in project documentation.
Test Coverage: Improve your testing depth using AI-driven strategies.
Design & UI/UX: Conduct UI/UX audits and verify Figma designs.
Technical Skills: Work with APIs, JSON, SQL, and Logcat logs more efficiently.
Troubleshooting: Investigate app crashes and technical bugs faster.
Data Security: Learn how to handle sensitive project data safely.
Efficiency: Reduce repetitive manual tasks using AI automation.

Program Overview

The program combines practical knowledge of Android and iOS testing with modern AI workflows used by real product teams. You will cover documentation analysis, visual checks, prompt engineering, and technical troubleshooting through hands-on exercises.

Additional Topics:

How the QA role is evolving in the era of Artificial Intelligence.
The difference between standard Chatbots and autonomous AI Agents.
Strategies for safely delegating tasks to AI.
Practical methods to succeed without deep programming skills.
How to combine human analytical thinking with AI productivity tools.

By the end of this course, you will understand how to use AI not as a replacement for QA engineers, but as a powerful assistant for faster analysis, smarter testing, and better decision-making.

Who this course is for:

Manual QA engineers who want to use AI in daily testing tasks
Mobile testers working with Android and iOS applications
Junior QA specialists who want stronger technical skills
IT specialists interested in AI-assisted testing workflows
Beginners exploring modern software testing and AI tools
QA engineers who want to improve productivity and analytical skills

AI in Mobile QA

What you'll learn

Explore related topics

Course content

Module 1. A New Paradigm: QA in the Age of Artificial Intelligence5 lectures • 16min

Module 2. The Technology Stack: Chatbots vs. Agents4 lectures • 33min

Module 3. AI Audit of Documentation and Requirements (Hands-On with the CatApp)3 lectures • 20min

Module 4. Visual Audit and UI/UX Testing3 lectures • 10min

Module 5. Technical Testing: Code, Databases, and the Network Layer5 lectures • 31min

Requirements

Description

Who this course is for: