IBM watsonx Generative AI Engineer - Associate - C1000-185 certification

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IBM C1000-185 Exam Syllabus Topics:

IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. When addressing bias in a generative AI model, which of the following strategies is least likely to be effective in reducing biased outputs during text generation?

A) Training the model on a diverse and representative dataset
B) Using temperature control during generation to manage diversity in responses
C) Incorporating fairness constraints during the model's training phase
D) Leveraging prompt rephrasing techniques to remove bias-inducing keywords or phrases

2. You are managing a generative AI model deployment in IBM Watsonx and need to implement prompt versioning to ensure traceability and reproducibility of model behavior over time.
Which of the following strategies best enables versioning of prompts during deployment?

A) Storing prompts in a flat file system and manually tracking versions.
B) Disabling versioning for prompts since it is not required for generative models.
C) Relying on model checkpointing to manage both model weights and prompts.
D) Using a source control system (e.g., Git) to track prompt changes alongside model code.

3. In developing an LLM-based conversational AI application using LangChain, you want the AI to perform complex tasks, such as answering questions based on dynamic knowledge from multiple sources (e.g., databases, APIs, etc.).
Which approach using LangChain best supports this requirement by combining various tools into a structured workflow for the AI to follow?

A) Build a chain of multiple LangChain agents, each handling a specific task (e.g., querying an API, accessing a database) to ensure data from various sources is used effectively.
B) Use a single LangChain agent to directly query all external data sources, allowing it to gather information on demand.
C) Integrate LangChain memory with an agent to handle all external data retrieval without needing to build complex chains.
D) Create a LangChain chain that connects different tools (e.g., API access, database queries) in a sequential or branching manner to process and combine data dynamically.

4. You are tasked with designing a prompt template to assist a chatbot in generating professional email responses for customer service inquiries. The system should prioritize politeness, clarity, and conciseness.
What elements should be included in the prompt template to achieve the best results, considering optimal behavior of a large language model (LLM)? (Select two)

A) Provide the customer's emotional context for better alignment with the tone
B) Specify the output tone as polite and professional
C) Include examples of informal customer service responses for variability
D) Instruct the model to limit responses to a specific character count
E) Ask the model to generate multiple versions of the response and rank them

5. In the context of Tuning Studio in IBM watsonx, what is one of the key benefits of using Compute Unit Hours (CUHs) during the fine-tuning process?

A) It allows for the precise allocation of computational resources to manage budget constraints.
B) It reduces the time required to train models by lowering the accuracy threshold.
C) It provides real-time feedback on model deployment success rates.
D) It limits the number of model versions stored, improving system performance.

Solutions: