Basic knowledge of programming (Python or R), machine learning fundamentals, and some experience with deep learning and generative models are recommended.

Enroll in a specialized training course, study official materials, complete hands-on projects, and practice with sample questions and mock exams.

Key topics include machine learning algorithms, generative models (GANs, VAEs), deep learning techniques, data preprocessing, and practical application of AI solutions.

• The exam typically lasts 1.5 to 2 hours, depending on the specific certification and format.

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Exams can be taken online or at authorized testing centers. Check with the certification provider for specific options.

Exam fees vary but generally range from $200 to $400 USD. Check with the certification provider for exact pricing.

The exam usually includes 40-60 questions, consisting of multiple-choice, case studies, and practical scenarios.

• The passing score typically ranges from 70% to 80%, depending on the certification provider.

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Certifications are often valid for 2-3 years. Renewal may require continuing education or re-examination, depending on the provider.

• Yes, you can retake the exam. There may be a waiting period and additional fees for retaking.

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Use official study guides, online courses, textbooks, and practice exams. Engage with online communities and forums for additional support.

While not mandatory, hands-on experience with generative AI and ML projects is highly beneficial for understanding exam concepts and applying knowledge effectively.