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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

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

10 reviews

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

10 reviews

Intermediate level

Recommended experience

5 hours to complete

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.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

6 assignments

Taught in English

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Build your subject-matter expertise

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.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

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.

The course covers key topics such as hyperparameter tuning, A/B testing, version control, and NVIDIA tools like BioNeMo, Triton, and TensorRT. Learners will also gain insights into optimizing AI workflows using cuOpt, NGC, and Merlin. Ethical AI principles, data privacy, and minimizing bias are emphasized to ensure trustworthiness in AI systems. Course Structure: The course is divided into three modules, each containing lessons and video lectures. Learners will engage with approximately 4:30-5:00 hours of video content, combining both theory and hands-on practice. Each module is complemented with quizzes to assess comprehension and reinforce learning. Module 1: Experimentation and Hyperparameter Tuning Module 2: NVIDIA AI Services and Optimization Module 3: Ethical AI and Trustworthiness By the end of this course, learners will be able to: - 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. This course is ideal for AI researchers, developers, and practitioners looking to enhance their skills in LLM experimentation, optimization, and ethical AI.

Module details

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

7 videosTotal 30 minutes

Principles for Designing Experiments with Large Language Models (LLMs)6 minutes
Hyperparameter Tuning of LLMs4 minutes
A/B Testing4 minutes
Importance of Version Control Systems4 minutes
Understanding NVIDIA BioNeMo LLM service4 minutes
What are NVIDIA AI Agents ?3 minutes
Using the Mixture of Experts in LLM Architectures5 minutes

2 readingsTotal 20 minutes

Welcome to the Course10 minutes
Overview of Experimentation and Hyperparameter Tuning10 minutes

2 assignmentsTotal 40 minutes

LLM Optimization & Experimentation - Knowledge check15 minutes
Experimentation and Hyperparameter Tuning - Assessment25 minutes

1 discussion promptTotal 10 minutes

Meet and Greet10 minutes

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

8 videosTotal 30 minutes

Introducing NVIDIA Tensor-RT4 minutes
Understanding NVIDIA Triton4 minutes
NVIDIA AI Workflows4 minutes
Logistic and Route Optimization - cuOpt4 minutes
NVIDIA RIVA4 minutes
Recommender System - Merlin4 minutes
Understanding NVIDIA NGC4 minutes
Exam Tips : Experimentation1 minute

1 readingTotal 10 minutes

Overview of NVIDIA AI Services and Optimization10 minutes

2 assignmentsTotal 40 minutes

NVIDIA AI Technologies and Tools Overview - Knowledge check15 minutes
NVIDIA AI Services and Optimization - Assessment25 minutes

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.