GenAI Readiness Test to evaluate the skills and knowledge of GenAI tools
The Mercer | Mettl GenAI Readiness Assessment evaluates candidates' comprehension and utilization of generative models. It assesses candidates' proficiency in essential areas and ensures the evaluation encompasses technical expertise and ethical awareness in using these powerful tools.
Available on request
Coding, Domain
Intermediate
30 minutes
30 questions
Data Scientist, Data Engineer, Machine Learning Engineer, Computer vision engineer, Deep learning engineers, Natural language processing engineer, Text processing engineer
English India
About the Mercer | Mettl GenAI Readiness Test
The Gen AI Readiness Test evaluates an organization's preparedness for adopting Generative AI technologies. It helps identify strengths and gaps in readiness, ensuring the organization is well-equipped to integrate and leverage AI effectively and responsibly.
Advantages of GenAI Readiness Test
- Identifies gaps and areas for improvement: The Gen AI Readiness Test helps organizations pinpoint improvement areas in their infrastructure, data management, and expertise, allowing them to address gaps before implementing Generative AI technologies.
- Optimizes resource allocation: By assessing current capabilities and needs, the test guides organizations in making informed decisions about where to invest in technology, training, and other resources, leading to more efficient and effective AI integration.
- Focus on technical aspects of AI: The assessment is focused on the technical aspects of Gen AI. For e.g., Fundamentals of generative AI or common generative models or how to build an effective prompt to avoid bias or what type of prompts to be used in different scenarios etc.
- Improves competitive advantage: By preparing thoroughly for Generative AI adoption, organizations can leverage AI technologies more effectively, leading to innovation, improved efficiency, and a stronger competitive position in the market.
What is inside this GenAI Readiness Test?
The test consists of thirty questions with an intermediate difficulty level. The test duration is thirty minutes.
What skills does this GenAI Readiness Test cover?
- Gen AI fundamentals: The skills in this competency include generative models: VAEs, GANs, transformers, applications: text generation, image creation, code generation, Tensorflow, Pytorch, OpenAI Gym and Transformers (Hugging Face).
- Prompt engineering: The skills in this competency include Prompt Structuring: zero-shot, few-shot techniques, bias mitigation, evaluate coherence and factual accuracy.
- Infrastructure for GenAI- The skills in this competency include Computational Resources: GPUs, TPUs, Cloud Platforms: Google Colab, and Amazon Sage Maker.
- Scalability: IaaC, Containerization, and Monitoring & Logging Tools: ELK, Kibana, Logstash.
- Model selection and evaluation- The skills in this competency include strengths and weaknesses of different models: VAEs, GANs, model selection: suitable model for text generation vs image generation, evaluation: inception score (IS) for image generation; BLEU score for text generation and fine tuning: hyperparameter tuning.
What roles can you assess using the GenAI Readiness Test?
- Machine learning engineer
- Data scientist
- Data engineer
- Deep learning engineer
- Natural language processing engineer
- Computer vision engineer
- Text processing engineer
GenAI Readiness Test competency framework
Get a detailed look inside the test
GenAI Readiness Test competencies under scanner
Gen AI Readiness skills
Competencies:
The skills in this competency include generative models: VAEs, GANs, transformers, applications: text generation, image creation, code generation, Tensorflow, Pytorch, OpenAI Gym and Transformers (Hugging Face).
The skills in this competency include Prompt Structuring: zero-shot, few-shot techniques, bias mitigation, evaluate coherence and factual accuracy.
The skills in this competency include Computational Resources: GPUs, TPUs, Cloud Platforms: Google Colab, and Amazon Sage Maker.
IaaC, Containerization, and Monitoring & Logging Tools: ELK, Kibana, Logstash.
The skills in this competency include strengths and weaknesses of different models: VAEs, GANs, model selection: suitable model for text generation vs image generation, evaluation: inception score (IS) for image generation; BLEU score for text generation and fine tuning: hyperparameter tuning.
Customize this GenAI Readiness Test
Flexible customization options to suit your needs
Choose easy, medium or hard questions from our skill libraries to assess candidates of different experience levels.
Add multiple skills in a single test to create an effective assessment. Assess multiple skills together.
Add, edit or bulk upload your own coding questions, MCQ, whiteboarding questions & more.
Get a tailored assessment created with the help of our subject matter experts to ensure effective screening.
The Mercer | Mettl GenAI Readiness Assessment advantage
- Industry Leading 24/7 Support
- State of the art examination platform
- Inbuilt Cutting Edge AI-Driven Proctoring
- Simulators designed by developers
- Tests Tailored to Your business needs
- Support for 20+ Languages in 80+ Countries Globally
Frequently Asked Questions (FAQs)
1. Does the assessment cover all aspects of generative AI development?
The assessment focuses primarily on core competencies essential for generative AI fundamentals, prompt engineering, etc.
2. Is the assessment tailored to specific industries or domains?
The assessment is industry agnostic. It evaluates general generative AI capabilities rather than industry-specific knowledge.
3. Does the assessment consider the ethical implications of generative AI?
This assessment does not cover the ethical or behavioural aspects associated with generative AI adoption. However, the assessment measures the functional understanding of what typical ethical behaviour is. Separate assessments to measure the ethical implications of generative AI can also be offered.
4. What is the purpose of the GenAI Readiness Test?
he GenAI Readiness Test assesses how prepared an organization or individuals from the AI team is for integrating and utilizing Generative AI technologies. It evaluates various aspects such as proficiencies in ML, DL, AI, fundamentals in generative models, transformer architecture, prompt engineering skills and model evaluation.
5. Who should take the GenAI Readiness Test?
The test is suitable for organizations and individuals who are considering the implementation of Generative AI technologies. It includes IT and data teams, AI strategists, and anyone involved in the planning and executing of AI projects. It is helpful for both large enterprises and smaller organizations aiming to harness the benefits of AI.
6. How can the GenAI Readiness Test results be used?
Results from the test provide insights into an organization's or team’s current preparedness for generative AI adoption. They can be used to identify gaps in skills, guide resource allocation, refine AI strategies, and enhance ethical and governance practices. The results help organizations develop a targeted action plan to address deficiencies and better align their AI initiatives with business objectives.
