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CSA CCSK Exam - Topic 3 Question 88 Discussion

Actual exam question for CSA's CCSK exam
Question #: 88
Topic #: 3
[All CCSK Questions]

Which type of AI workload typically requires large data sets and substantial computing resources?

Show Suggested Answer Hide Answer
Suggested Answer: C

Among AI workloads, Training requires the most computational power and data resources.

Why AI Training is Computationally Intensive?

Large datasets:

AI models (e.g., deep learning, neural networks) require millions or billions of labeled data points.

Training involves processing massive amounts of structured/unstructured data.

High computational power:

Training deep learning models involves running multiple passes (epochs) over data, adjusting weights, and optimizing parameters.

Requires specialized hardware like GPUs (Graphics Processing Units), TPUs (Tensor Processing Units), and HPC (High-Performance Computing).

Long training times:

AI model training can take days, weeks, or even months depending on complexity.

Cloud platforms offer distributed computing (multi-GPU training, parallel processing, auto-scaling).

Cloud AI Training Benefits:

Cloud providers (AWS, Azure, GCP) offer ML training services with on-demand scalable compute instances.

Supports frameworks like TensorFlow, PyTorch, and Scikit-learn.

This aligns with:

CCSK v5 - Security Guidance v4.0, Domain 14 (Related Technologies - AI and ML Security)

Cloud AI Security Risks and AI Data Governance (CCM - AI Security Controls)


by Alecia at May 02, 2025, 05:43 AM

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Cordelia
5 months ago
Wait, isn't Inference also resource-intensive?
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Rodney
5 months ago
I agree, Training is where the heavy lifting happens.
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Denny
5 months ago
Definitely C, Training needs tons of data!
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Shawna
6 months ago
C seems right, but I’m surprised it’s not more obvious!
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Bettina
6 months ago
I thought Data Preparation was the most demanding.
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Barabara
6 months ago
I feel like inference might need some resources too, but it’s mostly about using the model, right? So I guess it’s not the answer here.
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Dudley
6 months ago
I'm a bit confused; I thought data preparation also required significant resources, but maybe not as much as training?
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Bernardine
7 months ago
I remember practicing a question like this, and I think training is the right answer since it involves building the model with large datasets.
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Golda
7 months ago
I think it's definitely training that needs a lot of data and computing power, but I'm not 100% sure.
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Carmen
7 months ago
I'm a little confused by this question. I know training is resource-intensive, but I'm not sure if that's the only AI workload that fits the description. I'll have to review my notes and think it through.
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Hana
7 months ago
Training, for sure. That's where the model really gets built, and it needs all those resources to learn effectively. I feel confident about this one.
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Melda
7 months ago
Okay, let me see. Training seems like the most likely answer, since that's where the model learns from the data. But I should double-check the other options just to be sure.
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Kimbery
8 months ago
Hmm, I'm a bit unsure about this one. I know training is resource-intensive, but I'm not sure if that's the only AI workload that fits the description. I'll have to think this through carefully.
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Malcolm
8 months ago
I'm pretty sure this is asking about the training phase of AI models, which typically requires large datasets and substantial computing power to learn complex patterns.
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Corazon
11 months ago
Hmm, I'd say C) Training. Gotta feed those hungry neural networks, am I right?
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Rolande
11 months ago
I'm going with C) Training. They don't call it 'machine learning' for nothing, you know?
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Tora
10 months ago
True, you need clean and organized data for effective training.
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Latrice
10 months ago
I think data preparation is also important before training the AI model.
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Niesha
10 months ago
Yeah, training AI models can be quite resource-intensive. It's where the magic happens.
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Myrtie
10 months ago
Yeah, without proper training, the AI won't be able to learn and improve.
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Fletcher
11 months ago
Training is definitely the right choice. You need a lot of data and processing power for that.
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Gracia
11 months ago
I agree, training AI models definitely requires a lot of data and computing power.
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Wilbert
11 months ago
That's true, but the question specifically asks about the type of workload that requires large data sets and computing resources, which is training.
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Andra
12 months ago
But what about data preparation? Don't we need to clean and preprocess the data before training?
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Jillian
12 months ago
I agree with Wilbert, training AI models definitely requires large data sets and computing resources.
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Wilbert
1 year ago
I think the answer is C) Training.
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Ria
1 year ago
Definitely C) Training. The more data, the better the model, right? At this rate, I'll need a supercomputer to train my AI!
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Bobbye
1 year ago
C) Training, duh! That's where the real magic happens, baby!
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Larue
12 months ago
C) Training is where the AI model learns from the data and improves its performance.
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Alona
12 months ago
C) Training, duh! That's where the real magic happens, baby!
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Darell
12 months ago
D) Inference
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Derick
12 months ago
C) Training
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Tran
12 months ago
B) Data Preparation
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Janet
1 year ago
A) Evaluation
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