IAPP Artificial Intelligence Governance Professional AIGP Dumps in PDF

Free IAPP AIGP Real Questions (page: 1)

Machine learning is best described as a type of algorithm by which?

  1. Systems can mimic human intelligence with the goal of replacing humans.
  2. Systems can automatically improve from experience through predictive patterns.
  3. Statistical inferences are drawn from a sample with the goal of predicting human intelligence.
  4. Previously unknown properties are discovered in data and used to predict and make improvements in the data.

Answer(s): B

Explanation:

Machine learning (ML) is a subset of artificial intelligence (AI) where systems use data to learn and improve over time without being explicitly programmed. Option B accurately describes machine learning by stating that systems can automatically improve from experience through predictive patterns. This aligns with the fundamental concept of ML where algorithms analyze data, recognize patterns, and make decisions with minimal human intervention.


Reference:

AIGP BODY OF KNOWLEDGE, which covers the basics of AI and machine learning concepts.



You asked a generative Al tool to recommend new restaurants to explore in Boston, Massachusetts that have a specialty Italian dish made in a traditional fashion without spinach and wine. The generative Al tool recommended five restaurants for you to visit.

After looking up the restaurants, you discovered one restaurant did not exist and two others did not have the dish.

This information provided by the generative Al tool is an example of what is commonly called?

  1. Prompt injection.
  2. Model collapse.
  3. Hallucination.
  4. Overfitting.

Answer(s): C

Explanation:

In the context of AI, particularly generative models, "hallucination" refers to the generation of outputs that are not based on the training data and are factually incorrect or non-existent. The scenario described involves the generative AI tool providing incorrect and non-existent information about restaurants, which fits the definition of hallucination.


Reference:

AIGP BODY OF KNOWLEDGE and various AI literature discussing the limitations and challenges of generative AI models.



Each of the following actors are typically engaged in the Al development life cycle EXCEPT?

  1. Data architects.
  2. Government regulators.
  3. Socio-cultural and technical experts.
  4. Legal and privacy governance experts.

Answer(s): B

Explanation:

Typically, actors involved in the AI development life cycle include data architects (who design the data frameworks), socio-cultural and technical experts (who ensure the AI system is socio-culturally aware and technically sound), and legal and privacy governance experts (who handle the legal and privacy aspects). Government regulators, while important, are not directly engaged in the development process but rather oversee and regulate the industry.


Reference:

AIGP BODY OF KNOWLEDGE and AI development frameworks.



A company is working to develop a self-driving car that can independently decide the appropriate route to take the driver after the driver provides an address.

If they want to make this self-driving car "strong" Al, as opposed to "weak," the engineers would also need to ensure?

  1. That the Al has full human cognitive abilities that can independently decide where to take the driver.
  2. That they have obtained appropriate intellectual property (IP) licenses to use data for training the Al.
  3. That the Al has strong cybersecurity to prevent malicious actors from taking control of the car.
  4. That the Al can differentiate among ethnic backgrounds of pedestrians.

Answer(s): A

Explanation:

Strong AI, also known as artificial general intelligence (AGI), refers to AI that possesses the ability to understand, learn, and apply intelligence across a broad range of tasks, similar to human cognitive abilities. For the self-driving car to be classified as "strong" AI, it would need to possess full human cognitive abilities to make independent decisions beyond pre-programmed instructions.


Reference:

AIGP BODY OF KNOWLEDGE and AI classifications.



Which of the following is NOT a common type of machine learning?

  1. Deep learning.
  2. Cognitive learning.
  3. Unsupervised learning.
  4. Reinforcement learning.

Answer(s): B

Explanation:

The common types of machine learning include supervised learning, unsupervised learning, reinforcement learning, and deep learning. Cognitive learning is not a type of machine learning; rather, it is a term often associated with the broader field of cognitive science and psychology.


Reference:

AIGP BODY OF KNOWLEDGE and standard AI/ML literature.



Case Study:
Please use the following answer the next question:

ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.

ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC intends to use its historical customer data--including applications, policies, and claims--and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed tA. human underwriter for final review.

ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.

The best approach to enable a customer who wants information on the Al model's parameters for underwriting purposes is to provide?

  1. A transparency notice.
  2. An opt-out mechanism.
  3. Detailed terms of service.
  4. Customer service support.

Answer(s): A

Explanation:

The best approach to enable a customer who wants information on the AI model's parameters for underwriting purposes is to provide a transparency notice. This notice should explain the nature of the AI system, how it uses customer data, and the decision-making process it follows. Providing a transparency notice is crucial for maintaining trust and compliance with regulatory requirements regarding the transparency and accountability of AI systems.


Reference:

According to the AIGP Body of Knowledge, transparency in AI systems is essential to ensure that stakeholders, including customers, understand how their data is being used and how decisions are made. This aligns with ethical principles of AI governance, ensuring that customers are informed and can make knowledgeable decisions regarding their interactions with AI systems.



Case Study:

Please use the following answer the next question:

ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.

ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC intends to use its historical customer data--including applications, policies, and claims--and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed a human underwriter for final review.

ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.

Which of the following is the most important reason to train the underwriters on the model prior to deployment?

  1. To provide a reminder of a right appeal.
  2. To solicit on-going feedback on model performance.
  3. To apply their own judgment to the initial assessment.
  4. To ensure they provide transparency applicants on the model.

Answer(s): C

Explanation:

Training underwriters on the model prior to deployment is crucial so they can apply their own judgment to the initial assessment.
While AI models can streamline the process, human judgment is still essential to catch nuances that the model might miss or to account for any biases or errors in the model's decision-making process.


Reference:

The AIGP Body of Knowledge emphasizes the importance of human oversight in AI systems, particularly in high-stakes areas such as underwriting and loan approvals. Human underwriters can provide a critical review and ensure that the model's assessments are accurate and fair, integrating their expertise and understanding of complex cases.



Case Study:

Please use the following answer the next question:

ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.

ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC intends to use its historical customer data--including applications, policies, and claims--and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed .. human underwriter for final review.

ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.

During the first month when ABC monitors the model for bias, it is most important to?

  1. Continue disparity testing.
  2. Analyze the quality of the training and testing data.
  3. Compare the results to human decisions prior to deployment.
  4. Seek approval from management for any changes to the model.

Answer(s): A

Explanation:

During the first month of monitoring the model for bias, it is most important to continue disparity testing. Disparity testing involves regularly evaluating the model's decisions to identify and address any biases, ensuring that the model operates fairly across different demographic groups.


Reference:

Regular disparity testing is highlighted in the AIGP Body of Knowledge as a critical practice for maintaining the fairness and reliability of AI models. By continuously monitoring for and addressing disparities, organizations can ensure their AI systems remain compliant with ethical and legal standards, and mitigate any unintended biases that may arise in production.



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A
AI Tutor Explanation
4/25/2026 1:42:20 PM

Question 104:

  • Correct answer: D) Multi-Terabyte (TB) Range

  • Brief explanation:
- clustering keys organize data into micro-partitions to improve pruning when queries filter on those columns. - The performance benefit is most significant for very large tables; for small tables the overhead of maintaining clustering outweighs gains. - Therefore, as a best practice, define clustering keys on tables at the TB scale.

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Community Helper
4/25/2026 2:03:10 AM

Q23: Fabric Admin is correct. Because Domain admin cannot create domains. Only Fabric Admin can among the given options. Q51: Wrapping @pipeline.parameter.param1 inside {} will return a string. But question requires the expression to return Int, so correct answer should be @pipeline.parameter.param1 (no {})

A
AI Tutor Explanation
4/23/2026 3:07:03 PM

Question 62:

  • Correct answer: D (per the page)

  • Note: The explanation text on the page describes option B (use ZDX score and Analyze Score to trigger the Y Engine analysis), indicating a mismatch between the stated answer and the rationale.

  • Key concept: For fast root-cause analysis, leverage telemetry and auto-correlated insights:
- Use the user’s ZDX score for AWS and run Analyze Score to activate the Y Engine, which correlates metrics across network, client, and application to pinpoint the issue quickly.
  • Why the other options are less effective:
- A: Only checks for outages; doesn’t provide actionable root-cause analysis. - C: Deep Trace helps visibility but is manual and time-consuming. - D: Packet capture is invasive and slow; not the quickest path to root cause.

A
AI Tutor Explanation
4/23/2026 12:26:21 PM

Question 32:

  • Answer: A (2.4GHz)

  • Why: Lower-frequency signals have longer wavelengths and experience less attenuation when passing through walls and obstacles. Higher frequencies (5GHz, 6GHz) are more easily blocked by walls. NFC operates over very short distances and is not meant to penetrate walls. So 2.4 GHz best penetrates physical objects like walls.

A
AI Tutor Explanation
4/21/2026 8:48:36 AM

Question 3:

  • False is the correct answer (Option B).

Why:
  • In Snowflake, a database is a metadata object that exists within a single Snowflake account. Accounts are isolated—there isn’t one database that lives in multiple accounts.
  • You can access data across accounts via data sharing or database replication, but these create separate database objects in the other accounts (e.g., a database in the consumer account created from a share), not a single shared database across accounts.

So a single database cannot exist in more than one Snowflake account.

A
Anonymous User
4/16/2026 10:54:18 AM

Question 1:

  • Correct answer: Edate = sys.argv[1]
  • Why this is correct:
- When a Databricks Job passes parameters to a notebook, those parameters are supplied to the notebook's Python process as command-line arguments. The first argument after the script name is sys.argv[1], so date = sys.argv[1] captures the passed date value directly.
  • How it compares to other options:
- date = spark.conf.get("date") reads from Spark config, not from job parameters. - input() waits for user input at runtime, which isn’t how job parameters are provided. - date = dbutils.notebooks.getParam("date") would work if the notebook were invoked via dbutils.notebook.run with parameters, not

A
Anonymous User
4/15/2026 4:42:07 AM

Question 528:

  • Correct answer: NSG flow logs for NSG1 (Option B)

  • Why:
- Traffic Analytics uses NSG flow logs to analyze traffic patterns. You must have NSG flow logs enabled for the NSGs you want to monitor. - An Azure Log Analytics workspace is also required to store and query the traffic data. - Network Watcher must be available in the subscription for traffic analytics to function.
  • What to configure (brief steps):
- Ensure Network Watcher is enabled in the East US region (for the subscription/region). - Enable NSG flow logs on NSG1. - Ensure a Log Analytics workspace exists and is accessible (read/write) so Traffic Analytics can store and query logs.
  • Why other options aren’t correct:
- “Diagnostic settings for VM1” or “Diagnostic settings for NSG1” alone don’t guarantee flow logs are captured and sent to Log Analytics, which Traffic Analytics relies on. - “Insights for VM1” is not how Traffic Analytics collects traffic data.

A
Anonymous User
4/15/2026 2:43:53 AM

Question 23:
The correct answer is Domain admin (option B), not Fabric admin.

  • Domain admin provides domain-level management: create domains/subdomains and assign workspaces within those domains, which matches the tasks while following least privilege.
  • Fabric admin is global-level access and is more privileges than needed for this scenario (it would grant broader control across the Fabric environment).

A
Anonymous User
4/14/2026 12:31:34 PM

Question 2:
For question 2, the key concept is the Longest Prefix Match. Routers pick the route whose subnet mask is the most specific (largest prefix length) that still matches the destination IP.
From the options:

  • A) 10.10.10.0/28 ? 10.10.10.0–10.10.10.15
  • B) 10.10.13.0/25 ? 10.10.13.0–10.10.13.127
  • C) 10.10.13.144/28 ? 10.10.13.144–10.10.13.159
  • D) 10.10.13.208/29 ? 10.10.13.208–10.10.13.215

The destination Host A’s IP must fall within 10.10.13.208–10.10.13.215 for the /29 to be the best match. Since /29 is the longest prefix among the matching options, Router1 will use 10.10.13.208/29.
Thus, the correct answer is D.

S
srameh
4/14/2026 10:09:29 AM

Question 3:

  • Correct answer: Phase 4, Post Accreditation

  • Explanation:
- In DITSCAP, the four phases are: - Phase 1: Definition (concept and requirements) - Phase 2: Verification (design and testing) - Phase 3: Validation (fielding and evaluation) - Phase 4: Post Accreditation (ongoing operations and lifecycle management) - The description—continuing operation of an accredited IT system and addressing changing threats throughout its life cycle—fits the Post Accreditation phase, which covers operations, maintenance, monitoring, and reauthorization as threats and environment evolve.

O
onibokun10
4/13/2026 7:50:14 PM

Question 129:
Correct answer: CNAME

  • A CNAME record creates an alias for a domain, so newapplication.comptia.org will resolve to whatever IP address www.comptia.org resolves to. This ensures both names point to the same resource without duplicating the IP.
  • Why not the others:
- SOA defines authoritative information for a zone. - MX specifies mail exchange servers. - NS designates name servers for a zone.
  • Notes: The alias name (newapplication.comptia.org) should not have other records if you use a CNAME for it, and CNAMEs aren’t used for the zone apex (root) domain. This scenario uses a subdomain, so a CNAME is appropriate.

A
Anonymous User
4/13/2026 6:29:58 PM

Question 1:

  • Correct answer: C

  • Why this is best:
- Uses OS Login with IAM, so SSH access is granted via Google accounts rather than distributing per-user SSH keys. - Granting the compute.osAdminLogin role to a Google group gives admin access to all team members in a centralized, auditable way. - Access is auditable: Cloud Audit Logs show who accessed which VM, satisfying the security requirement to determine who accessed a given instance.
  • How it works:
- Enable OS Login on the project/instances (enable-oslogin metadata). - Add the team’s

A
Anonymous User
4/13/2026 1:00:51 PM

Question 2:

  • Answer: D. Azure Advisor

  • Why: To view security-related recommendations for resources in the Compute and Apps area (including App Service Web Apps and Functions), you use Azure Advisor. Advisor surfaces personalized best-practice recommendations across resources, including security, and shows which resources are affected and the severity.

  • Why not the others:
- Azure Log Analytics is for ad-hoc querying of telemetry, not for viewing security recommendations. - Azure Event Hubs is for streaming telemetry data, not for security recommendations.
  • Quick tip: In the portal, navigate to Azure Advisor and check the Security recommendations for App Services to see actionable items and affe

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Don
4/11/2026 5:36:42 AM

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M
Mogae Malapela
4/8/2026 6:37:56 AM

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A
Anon
4/6/2026 5:22:54 PM

Are these the same questions you have to pay for in ExamTopics?

L
LRK
3/22/2026 2:38:08 PM

For Question 7 - while the answer description indicates the correct answer, the option no. mentioned is incorrect. Nice and Comprehensive. Thankyou

R
Rian
3/19/2026 9:12:10 AM

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G
Gerrard
3/18/2026 6:58:37 AM

The DP-900 exam can be tricky if you aren't familiar with Microsoft’s specific cloud terminology. I used the practice questions from free-braindumps.com and found them incredibly helpful. The site breaks down core data concepts and Azure services in a way that actually mirrors the real test. As a resutl I passed my exam.

V
Vineet Kumar
3/6/2026 5:26:16 AM

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J
Joe
1/20/2026 8:25:24 AM

Passed this exam 2 days ago. These questions are in the exam. You are safe to use them.

N
NJ
12/24/2025 10:39:07 AM

Helpful to test your preparedness before giving exam

A
Ashwini
12/17/2025 8:24:45 AM

Really helped

J
Jagadesh
12/16/2025 9:57:10 AM

Good explanation

S
shobha
11/29/2025 2:19:59 AM

very helpful

P
Pandithurai
11/12/2025 12:16:21 PM

Question 1, Ans is - Developer,Standard,Professional Direct and Premier

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Einstein
11/8/2025 4:13:37 AM

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David
10/31/2025 4:06:16 PM

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Thor
10/21/2025 5:16:29 AM

Anyone used this dump recently?

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Vladimir
9/25/2025 9:11:14 AM

173 question is A not D

K
khaos
9/21/2025 7:07:26 AM

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Katiso Lehasa
9/15/2025 11:21:52 PM

Thanks for the practice questions they helped me a lot.

E
Einstein
9/2/2025 7:42:00 PM

Passed this exam today. All questions are valid and this is not something you can find in ChatGPT.

V
vito
8/22/2025 4:16:51 AM

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