Discover the journey to the ISTQB AI certification, from motivation to preparation tips. Gain insights on artificial intelligence (AI) testing, skills acquired, and advice for aspiring candidates.
Motivation: Why Pursue the ISTQB AI Certification?
My motivation to obtain the ISTQB AI certification was from my previous experiences and general interest in AI. During my studies, I encountered AI particularly during my master's thesis on deep neural networks. These experiences hit my interest in the diverse applications and technological advancements that AI brings.
Today, AI is becoming increasingly significant in both software development and testing. The desire to deepen my knowledge in this promising field and prepare for future challenges further motivated me to pursue the ISTQB AI certification.
Preparation for the ISTQB AI Exam – How did you prepare yourself, Colin?
My preparation for the ISTQB AI exam began with a detailed review of the syllabus, which includes all the necessary topics for the exam. While extra sources aren't required, it's important to remember that AI is a fast-changing field. So, continuing to learn about AI even after passing the exam is beneficial.
A particularly helpful resource was the Udemy course led by Dr. Stuart Reid, one of the authors of the ISTQB AI syllabus. The course includes practical examples and exercises, spanning 12 hours, which provided an in-depth preparation.
What’s the differences between ISTQB and ISTQB AI
While the structure of the curriculum and exams for ISTQB and ISTQB AI are similar, there are some key differences. The ISTQB AI certification builds on the basics of software testing but focuses on AI-specific quality attributes and technologies.
AI systems are often part of a larger software ecosystem that includes conventional software. A crucial aspect of testing AI systems is evaluating the data used to train the system. This focus on data quality is essential for the reliability and performance of AI.
What knowledge and skills acquired through the ISTQB AI Certification
Through the ISTQB AI certification, I gained comprehensive knowledge of various AI applications and the different AI technologies in use. I developed a deep understanding of the advantages of AI over conventional systems, as well as the risks and potential weaknesses associated with AI.
A central theme was the importance of data and data quality. The quality of the data used to train an AI system is crucial for its performance and reliability. This insight has heightened my awareness of the need for careful data inspection and preparation.
Tips for Aspiring ISTQB AI Certification Candidates
For those considering the ISTQB AI certification, here are some tips:
1. Recommendation for All: The certification is suitable not only for those deeply involved in AI. No prior AI experience is necessary; only the ISTQB Foundation certification is required.
2. Clear Materials: The curriculum and especially the mentioned Udemy course are very well-structured and easy to understand.
3. Precision in Exam Questions: The exam questions can be tricky. Even if you feel confident in the subject matter, it's important to read the questions carefully and answer them thoroughly.
4. Future-Oriented Knowledge: Many software systems will integrate AI components that need to be tested. Additionally, testing tools themselves will increasingly employ AI.
In general the ISTQB AI certification offers a great opportunity to prepare for the growing challenges and opportunities in AI and advance your career in software testing.
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