AI Wisdom

NVIDIA associate level

NVIDIA Certified Associate: Generative AI LLMs

Code
NCA-GENL
Length
60 minutes
Price
$125
Valid for
2 years, renewed by retaking the exam
Study time, our estimate
30 to 50 hours

A fast exam on how LLMs work underneath. Unlike the cloud exams, it barely cares about products. It suits engineers who picked up LLMs through APIs and want to fill the theory gap, and the one-hour limit means you need to know it, not look it up.

Take it if

You want the theory behind LLMs, regardless of cloud.

Skip it if

You can already explain attention, embeddings and quantization. Go to the professional level.

Before you start

Check yourself against this list first. If something is missing, close that gap before you pay for an exam.

  • A basic understanding of generative AI and LLMsNVIDIA's only stated prerequisite. Python helps.

Next: NCP-GENL

All exam details
Format
50 to 60 multiple-choice questions
Length
60 minutes
Price
$125
Valid for
2 years, renewed by retaking the exam
Delivery
Proctored, English
Experience
Basic understanding of generative AI and LLMs
If you fail
Wait 14 days

What the exam covers

  • Core ML and AI Knowledge30%
  • Software Development24%
  • Experimentation22%
  • Data Analysis14%
  • Trustworthy AI10%

What to focus on

  • Transformers: attention, positional encoding, tokenization.
  • Embeddings, and how RAG uses them.
  • Sampling settings, and how experiments are designed.
  • Python tooling for ML, and data analysis basics.
  • Bias and trustworthy AI.
Everything on one mapEvery topic and key idea in this certification.
mindmap
  root((NCA-GENL))
    How transformers work
      Attention
      Positional encoding
      Embeddings
    Building and experimenting
      Fair tests
      Imbalance
      Mixed precision
    Trustworthy AI
      Bias
      Guardrails
      Transparency

Lesson 1 of 3, 30% of the exam

How transformers work

The largest domain.

Attention
Weighs how each token relates to the others.
Positional encoding
Adds word order, which attention alone lacks.
Embeddings
Vectors that capture meaning.
From text to tokenA simplified view of one prediction.
flowchart LR
  A["Text"] --> B["Tokens"]
  B --> C["Embeddings plus position"]
  C --> D["Attention layers"]
  D --> E["Next token probabilities"]
  E -->|"Sample with temperature"| F["Output token"]

Common trap

Memorizing terms without being able to explain them.

Try it yourself

Explain attention out loud without notes.

Official docs: Attention Is All You Need

Lesson 2 of 3, 24% + 22% + 14% of the exam

Building and experimenting

Over half the exam is practical.

Fair tests
Compare versions on the same labeled set.
Imbalance
Accuracy can hide a neglected minority class.
Mixed precision
Saves GPU memory where it is safe.
A fair experimentChange one thing and hold the rest still.
flowchart LR
  A["Same test set"] --> B["Version A"]
  A --> C["Version B"]
  B --> D["Score"]
  C --> D
  D --> E["Keep the winner"]

Common trap

Judging a change from one example.

Try it yourself

Compare two prompts on 20 labeled examples.

Official docs: NVIDIA training

Lesson 3 of 3, 10% of the exam

Trustworthy AI

A small domain with a clear idea behind it.

Bias
Models learn unfair patterns from historical data.
Guardrails
Rules around inputs and outputs.
Transparency
Be clear about how a system is used.
Where bias entersIt can start well before the model.
flowchart LR
  A["Historical data"] --> B["Training"] --> C["Model"] --> D["Decisions"]
  D -.->|"Feeds future data"| A

Common trap

Treating bias as only a model problem. It often starts in the data.

Try it yourself

List three bias risks in one dataset.

Official docs: NeMo Guardrails

Study plan

  1. Weeks 1 and 2: deep learning basics

    Work the open Fundamentals of Deep Learning materials from NVIDIA DLI.

  2. Week 3: LLMs

    Take Rapid Application Development With Large Language Models.

  3. Exam week

    Explain attention out loud without notes, then take the mock below.

Exam day and after

  • NVIDIA certifications last two years, and you renew by retaking the exam.
  • Exams are proctored and in English. NVIDIA's FAQ covers both remote and in-person testing, and remote exams allow no breaks.
  • Check the exam page before you plan around a date. NVIDIA has been adding hands-on labs to professional exams.
Test yourself8 practice questions, scored by exam topic.
Start the mock exam

Keep going

Exam facts checked on October 31, 2026 against NVIDIA certification page. Lessons are our own explanations, so use the official docs as the final word, and confirm price and dates before booking.