{"EXAM_SERIES_CODE":"C1000-185","EXAM_STATUS_ID":"1","EXAM_REVIEW_APPROVAL_STATUS_OPS":null,"EXAM_REVIEW_APPROVAL_STATUS_OTHER":null,"EXAM_REVIEW_APPROVAL_STATUS_PUBLISH":null,"EXAM_TITLE":"IBM watsonx Generative AI Engineer v1 - Associate ","WITHDRAWAL_DATE":null,"CREATED_BY_EMAIL":"jessfern@us.ibm.com","CREATED_BY_DATE":"2024-05-08 00:00:00.000000","OWNER_NAME":"Jessica Fernandez","OWNER_EMAIL":"jessfern@us.ibm.com","LAST_MODIFIED_BY_EMAIL":"jessfern@us.ibm.com","LAST_MODIFIED_BY_DATE":"2026-01-13 00:00:00.000000","EXAM_BUSINESS":"IBM Data and AI","EXAM_BRAND":"Watson AI","EXAM_REPLACED_FLAG":false,"REPLACE_BY_EXAM_SERIES_CODE":null,"PREREQUISITE_EXAM_SERIES_CODE":null,"OVERVIEW_JOB_ROLE":"

During exam development, the Subject Matter Experts (SMEs) define all of the tasks, knowledge and experience that an individual would need in order to successfully fulfill their role with the product or solution. These are represented by the objectives below and the questions on the exam are based upon these objective.

","OVERVIEW_JOB_SKILL":"","EXAM_TIME_LIMIT":90,"EXAM_PASSING_SCORE":70,"EXAM_NUMBER_OF_QUESTIONS":62,"EXAM_NUMBER_OF_QUESTIONS_TO_PASS":44,"EXAM_PRICE_DEVELOPED":null,"EXAM_PRICE_EMERGING":null,"EXAM_PRICE_JAPAN":null,"AVAILABLE_FOR_PROCTOR_FLAG":true,"WITHDRAWAL_WARNING_DAYS":30,"BADGE_REPLACED_FLAG":false,"REPLACE_BY_BADGE_ID":null,"EDUCATION_OVERVIEW":"

All IBM certification tests presume a certain amount of \"on-the-job\" experience which is not present in any classroom or Web presentation. The recommended courses and links will help you gain the skill and product knowledge represented in the test objectives. They do not teach the answers to the test questions and are not intended to do so. This information may not cover all subject areas in the certification test or may contain more recent information than is present in the certification test. Taking these or any classes will not guarantee that you will achieve certification.

","JTA_OBJECTIVE_UPLOAD_PATH":null,"JTA_SURVEY_FLAG":true,"JTA_JOB_ROLE_DESCRIPTION":"

An Associate Generative AI Engineer is skilled in selecting, customizing, and prompting large language models, and can design and develop generative AI solutions using the watsonx.ai studio. This includes the ability to connect generative AI solutions to enterprise requirements and understand when various generative AI techniques and models are applicable to specific business problems.

 

Concepts in this Associate level exam include:

 

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An Associate Generative AI Engineer is skilled in selecting, customizing, and prompting large language models, and can design and develop generative AI solutions using the watsonx.ai studio. This includes the ability to connect generative AI solutions to enterprise requirements and understand when various generative AI techniques and models are applicable to specific business problems.

 

Concepts in this Associate level exam include:

 

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An Associate Generative AI Engineer is skilled in selecting, customizing, and prompting large language models, and can design and develop generative AI solutions using the watsonx.ai studio. This includes the ability to connect generative AI solutions to enterprise requirements and understand when various generative AI techniques and models are applicable to specific business problems.

 

Concepts in this Associate level exam include:

 

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  1. Understand the five capabilities of GenAI/LLMs
  2. Articulate the components in Gen AI Patterns
  3. Understand the limitations of GenAI/LLMs
  4. Understand use cases and identify Gen AI application opportunities
  5. Understand how to choose the appropriate model for a use case
  6. Articulate the optimal model architecture based on a use case
  7. Identify and apply various tools and techniques like AI agents, RAG , LangChain , etc
  8. Understand security risks associated with LLMs, prompt engineering, prompt, and data 
     
","EXAM_OBJECTIVE_ORDER":0,"TINSERTTS":"2026-01-13 18:14:56.887668","TLASTUPDTS":"2026-01-13 18:14:56.887668"},{"EXAM_SERIES_CODE":"C1000-185","EXAM_OBJECTIVE_ID":1,"EXAM_OBJECTIVE_TITLE":"Prompt Engineering","PERCENTAGE_OF_OBJECTIVE_QUESTIONS":"16","EXAM_OBJECTIVE_DESCRIPTION":"
  1. Differentiate between zero-shot and few-shot prompting 
  2. Design prompts based on use case
  3. Generate prompt templates 
  4. Determine the best model parameters for each GenAI prompt 
  5. Describe the benefits of using prompt variables
  6. Describe the benefits of Prompt Lab
  7. Articulate hyper parameter tuning 
  8. Articulate model risks 
","EXAM_OBJECTIVE_ORDER":1,"TINSERTTS":"2026-01-13 18:14:56.891643","TLASTUPDTS":"2026-01-13 18:14:56.891643"},{"EXAM_SERIES_CODE":"C1000-185","EXAM_OBJECTIVE_ID":2,"EXAM_OBJECTIVE_TITLE":"Fine-Tuning","PERCENTAGE_OF_OBJECTIVE_QUESTIONS":"31","EXAM_OBJECTIVE_DESCRIPTION":"
  1. Understand the difference between hard and soft prompts
  2. Reconstruct prompts to reduce the cost of using GenAI models
  3. Plan for Data elements for application usage
  4. Articulate model quantization techniques
  5. LoRA
  6. Prepare the dataset for training
  7. Customize LLMs with InstructLab
  8. Generate synthetic data using the User Interface
     
","EXAM_OBJECTIVE_ORDER":2,"TINSERTTS":"2026-01-13 18:14:56.895736","TLASTUPDTS":"2026-01-13 18:14:56.895736"},{"EXAM_SERIES_CODE":"C1000-185","EXAM_OBJECTIVE_ID":3,"EXAM_OBJECTIVE_TITLE":"Retrieval-Augmented Generation (RAG)","PERCENTAGE_OF_OBJECTIVE_QUESTIONS":"17","EXAM_OBJECTIVE_DESCRIPTION":"
  1. Describe embeddings in the context of GenAI
  2. Generate vector embeddings utilizing models
  3. Describe when to use a vector database
  4. Develop using libraries 
","EXAM_OBJECTIVE_ORDER":3,"TINSERTTS":"2026-01-13 18:14:56.900024","TLASTUPDTS":"2026-01-13 18:14:56.900024"},{"EXAM_SERIES_CODE":"C1000-185","EXAM_OBJECTIVE_ID":4,"EXAM_OBJECTIVE_TITLE":"Deployment","PERCENTAGE_OF_OBJECTIVE_QUESTIONS":"13","EXAM_OBJECTIVE_DESCRIPTION":"
  1. Plan for a deployment based on client needs
  2. Deploy AI Assets
  3. Deploy a custom model
  4. Plan out deployment of prompts for versioning
  5. High level architecture for deployment options
","EXAM_OBJECTIVE_ORDER":4,"TINSERTTS":"2026-01-13 18:14:56.904595","TLASTUPDTS":"2026-01-13 18:14:56.904595"},{"EXAM_SERIES_CODE":"C1000-185","EXAM_OBJECTIVE_ID":5,"EXAM_OBJECTIVE_TITLE":"Integration with Model Orchestration","PERCENTAGE_OF_OBJECTIVE_QUESTIONS":"8","EXAM_OBJECTIVE_DESCRIPTION":"
  1. Integrate watsonx.ai with Other Services/Manage APIs and SDKs
  2. Orchestrate AI Workflows
  3. Understand real-world Integration Scenarios
  4. Develop LLM based applications with LangChain
","EXAM_OBJECTIVE_ORDER":5,"TINSERTTS":"2026-01-13 18:14:56.942391","TLASTUPDTS":"2026-01-13 18:14:56.942391"}],"RESOURCES":[{"TYPE":"Web Resource","RESOURCES":[{"RESOURCE_TITLE":"Certification Prep Session: IBM watsonx Generative Al Engineer v1 - Associate","RESOURCE_DESCRIPTION":"

Get prepared with this Certification Prep Session on IBM watsonx Generative AI Engineer v1 – Associate. The session provides a clear overview of exam objectives, essential concepts, and practical guidance to help candidates strengthen their skills in generative AI ensuring they are well prepared to achieve certification success.

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