NVIDIA: Advanced LLM Experimentation, Deployment, and Ethical AI is the sixth course in the Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs - Associate Specialization. This course equips learners with advanced knowledge on experimenting with Large Language Models (LLMs), optimizing them for deployment, and understanding the ethical considerations in AI systems.
NVIDIA: LLM Experimentation, Deployment, and Ethical AI
NVIDIA: LLM Experimentation, Deployment, and Ethical AI
This course is part of Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs Specialization
Instructor: Whizlabs Instructor
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
4 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Experiment with LLMs using hyperparameter tuning and A/B testing.
Apply version control and optimize AI workflows with NVIDIA tools like BioNeMo, Triton, and TensorRT.
Understand ethical AI principles, data privacy, and methods to minimize bias and enhance AI trustworthiness.
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February 2025
Assessments
6 assignments
Taught in English
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This course is part of the Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course
Welcome to Week 1 of NVIDIA: LLM Experimentation, Deployment, and Ethical AI. This week, we will cover the essential principles for designing experiments with Large Language Models (LLMs). We’ll dive into the process of Hyperparameter Tuning for LLMs and explore techniques like A/B Testing to optimize model performance. Next, we’ll discuss the importance of Version Control Systems in managing LLM models and experiments. We will also introduce NVIDIA BioNeMo, a powerful LLM service, and explore how NVIDIA AI Agents enhance LLM capabilities. Finally, we will look at the Mixture of Experts architecture in LLMs, highlighting its role in improving model efficiency. By the end of the week, you'll gain valuable insights into experimenting with LLMs and fine-tuning their performance for real-world applications.
What's included
7 videos2 readings2 assignments1 discussion prompt
Welcome to Week 2 of the NVIDIA: LLM Experimentation, Deployment, and Ethical AI course. This week, we will explore key NVIDIA AI services and their role in optimizing machine learning and deep learning workflows. We will begin with an introduction to NVIDIA TensorRT for accelerating AI inference and NVIDIA Triton for scalable model deployment. Next, we will cover NVIDIA AI Workflows, including cuOpt for logistics and route optimization, NVIDIA Riva for speech AI, and Merlin for building recommender systems. Additionally, we will discuss NVIDIA NGC, a hub for AI software and pre-trained models. Finally, we will provide exam tips on AI experimentation and best practices. By the end of the week, you will gain a solid understanding of NVIDIA's AI services and their applications in real-world scenarios.
What's included
8 videos1 reading2 assignments
Welcome to Week 3 of the NVIDIA: LLM Experimentation, Deployment, and Ethical AIcourse. This week, we will explore the ethical principles of trustworthy AI, emphasizing the importance of data privacy and user consent in AI applications. Next, we will examine NVIDIA’s role in enhancing AI trustworthiness and discuss strategies for minimizing bias in AI systems. We will also cover key steps in the registration process and system setup for assessments. Finally, we will highlight common mistakes to avoid before taking the examination and conclude with key takeaways on building responsible AI systems. By the end of the week, you will have a solid understanding of ethical AI and best practices for trustworthy AI development.
What's included
7 videos3 readings2 assignments
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