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  • Home
  • Class Video
    • Ethical Hacking and SOC Engineering batches
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    • DevOps Engineering with Cloud Computing batches
    • Professional Data Analyst with AI batches
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  • Question Bank
    • Data Analyst Job Interview (only for Consultants)
    • SOC Analyst Job Interview (only for Consultants)
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    • to Get One-on-One Support from a Mentor (for Students only)
    • to Set Mock Interview (to Proceed Towards Job Placement)
    • for Job Placement (only if you Pass the Mock Interview)
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  • Applied Software Engineering with AI (ASEA 100 WEM 2026)

Applied Software Engineering with AI (ASEA 100 WEM 2026)

  • By PeopleNTech
  • Software Engineering
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    • What Does an AI-Driven Test Automation Engineer Do?

      An AI-Driven Test Automation Engineer is a specialist who leverages artificial intelligence to ensure software runs flawlessly—without relying solely on manual testing. Their role blends coding skills, AI algorithms, and advanced testing principles to:

      • Build intelligent test frameworks that learn from past results and adapt to new scenarios automatically.

      • Integrate AI-powered tests into the development process so defects are predicted and prevented before reaching production.

      • Collaborate with developers, data scientists, and QA teams to optimize performance, security, and reliability.

      • Harness cutting-edge AI and automation platforms like Testim, Mabl, Applitools, Functionize, Selenium with AI plugins, and Playwright.

      • Continuously refine pipelines for speed, precision, and scalability—using AI insights to improve every iteration.

      AI-driven test automation is becoming essential in industries like e-commerce, fintech, healthcare IT, and enterprise software, where quality and release speed are mission-critical.

      What Is AI-Driven Test Automation?
      AI-driven test automation enhances traditional automation by integrating machine learning and natural language processing to:

      • Automatically generate, maintain, and optimize test cases based on changing application behavior.

      • Predict high-risk areas of code and prioritize tests accordingly.

      • Reduce maintenance by self-healing broken test scripts when UI or API changes occur.

      • Support continuous integration (CI) and continuous delivery (CD) pipelines with intelligent test scheduling.

      This approach ensures consistent, accurate results while freeing QA teams to focus on exploratory and creative problem-solving.

      Career Outlook in the U.S.
      The future for AI-driven QA engineers is exceptionally bright:

      • Projected growth: 20%+ from 2023 to 2033—faster than traditional QA roles.

      • Thousands of openings each year for AI Test Engineers, SDETs, and Intelligent QA Specialists.

      • Strong demand in sectors like finance, SaaS, telecommunications, and AI-powered startups.

      • AI and automation together now rank among the top five most sought-after skills in modern software teams.

      Show More

      Course Content

      LMS Usage Instructions

      • How to use the LMS for your Learning

      Orientation Class

      • Live Class Video of 22nd August 2026
        01:59:57

      ASEA Class 01

      • Live Class Video of 5th September 2026
        03:40:25

      ASEA Class 02

      • Live Class Video of 6th September 2026
        03:43:42

      ASEA Class 03

      • Live Class Video of 12th September 2026
        03:46:42

      ASEA Class 04

      • Live Class Video of 13th September 2026
        04:02:31

      A course by

      P
      PeopleNTech

      Course Includes:

      • Price:
        $5,000.00
      • Instructor:PeopleNTech
      • Lessons:6
      • Students:13
      • Level:Expert
      • Certifications:No
      $5,000.00
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