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The NVIDIA Certified Associate Generative AI and LLMs (NCA-GENL) course covers the fundamentals of generative AI and large language models, including prompt engineering, fine-tuning, and deploying models using NVIDIA's AI platform. You'll learn how transformer-based models work, how to evaluate model outputs, and how NVIDIA tools support the generative AI lifecycle. The course combines structured lessons with exam-style practice questions to prepare you for the NCA-GENL exam and the NVIDIA Certified Associate credential. This NVIDIA Certified Associate Generative AI and LLMs training pairs guided lessons with a full NVIDIA Certified Associate Generative AI and LLMs practice test, so you walk into the NCA-GENL exam fully prepared.
The NVIDIA Certified Associate Generative AI and LLMs course is built by Whizlabs to mirror how the real NCA-GENL exam is structured, so the concepts you practice here map directly onto exam day. Whether you're brand new to this area or brushing up before the NCA-GENL exam, this course paces the material so nothing feels rushed.
Fundamentals of generative AI and large language models
Prompt engineering and fine-tuning techniques
Evaluating and deploying LLMs responsibly
Working knowledge of NVIDIA's generative AI tools
Transformer architecture basics
Applying generative AI to real business problems
24x7 support from AI-certified experts
This course is valid for 2 years from the date of purchase
Practice tests with unique, exam-style questions
Detailed explanations for every practice question
Course completion certificate
Official domain-by-domain weightings for the NCA-GENL exam were not included in the source data for this page, so the skill areas below are listed without percentage breakdowns. Verify current weightings on the vendor's official NVIDIA Certified Associate Generative AI and LLMs exam guide before publishing.
Fundamentals of generative AI and large language models
Prompt engineering and fine-tuning techniques
Evaluating and deploying LLMs responsibly
Working knowledge of NVIDIA's generative AI tools
The NVIDIA Certified Associate Generative AI and LLMs course lays out a clear path to the NCA-GENL exam, so you're not guessing what to study next.
Start with the video lessons in this NVIDIA Certified Associate Generative AI and LLMs course to build a working understanding of the core concepts the NCA-GENL exam covers. Then move into the hands-on labs to apply what you've learned in a real environment instead of just reading about it.
Next, work through the NCA-GENL practice test set. Each NVIDIA Certified Associate Generative AI and LLMs practice test question comes with a detailed explanation, so a wrong pick becomes a lesson you actually retain.
When your NCA-GENL practice test scores stay consistently above the passing mark, you're ready to book the NVIDIA Certified Associate Generative AI and LLMs exam. For a fuller walkthrough, refer to a dedicated NVIDIA Certified Associate Generative AI and LLMs exam preparation guide alongside this course.
The NCA-GENL certification has no mandatory prior certification requirement.
Once you pass, the NVIDIA Certified Associate Generative AI and LLMs certification stays valid for Check Site*. Before it expires, you can renew the NCA-GENL certification by retaking the current exam.
Many learners treat the NVIDIA Certified Associate Generative AI and LLMs certification as a step within a broader vendor certification track. Check Whizlabs' related course listings for a logical next-level credential once you've completed this NCA-GENL course.
NCA-GENL validates practical knowledge of generative AI and large language models, one of the fastest-growing areas in tech. It's a credible way to show you understand how LLMs work and how to apply them, whether you're a developer, data professional, or AI enthusiast.
Signals hands-on generative AI knowledge to employers, supporting roles in AI development, MLOps, and applied data science.
Helps your team evaluate and deploy generative AI solutions more confidently, using NVIDIA's tools and best practices.
Builds practical understanding of prompt engineering, fine-tuning, and deploying large language models responsibly.
Generative AI skills are in high demand, and a recognized credential can support stronger compensation conversations.
Exam Format and Information
Prior Certification
Not Required
Exam Validity
Check Site*
Exam Fee
Check Site*
Exam Duration
Check Site*
No. of Questions
Check Site*
Passing Score
Not Published*
Best for those with basic Python and machine learning familiarity, though not formally required.
English; see NVIDIA's certification page for current availability.
Online proctored, multiple choice format.
NCA-GENL has no formal prerequisites, though basic familiarity with Python and machine learning concepts helps. It's designed for developers, data professionals, and AI enthusiasts who want to validate practical generative AI and large language model knowledge.
Developers building generative AI applications.
Data scientists working with large language models.
MLOps engineers deploying generative AI solutions.
Students and professionals new to generative AI.
AI enthusiasts wanting a recognized credential.
Anyone exploring a career in applied generative AI.
Get help from AI-certified trainers on tricky LLM and generative AI concepts.
Structured lessons covering generative AI and LLM fundamentals step by step.
Unique, exam-style questions with detailed explanations for every answer.
Earn a completion certificate to showcase alongside your NCA-GENL credential.
Testimonials
Overall Feedbacks
Within artificial intelligence, generative AI and large language models (LLMs) are two fascinating and exciting subfields. The field of generative AI is broad and includes a variety of AI systems aimed at creating novel and creative content, including literature, art, music, and code.
NVIDIA's Deep Learning Institute (DLI) offers real-world, hands-on education and certification in AI at the cutting edge for developers, educators, students, and lifelong learners. This is a fantastic approach to get the essential AI abilities you'll need to succeed professionally.
Many low-level jobs can be handled by generative AI technologies, but experts need to be careful when using the technology for coding.
With the help of generative AI, users may produce new content quickly using a range of inputs. These models accept text, photos, music, animation, 3D models, and other kinds of data as inputs and outputs.
While not all generative AI tools are based on LLMs, but all generative AI is a type of LLM.
Content aligned to current NCA-GENL objectives
Applying generative AI to real business problems
4.9/5
4.8/5
Juan Carlos Herrera Marchetti
Juan Carlos Herrera Marchetti
