К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
NVIDIA: LLM Experimentation, Deployment, and Ethical AI · LearnSpace
Назад в каталог
courseraПрограммирование

NVIDIA: LLM Experimentation, Deployment, and Ethical AI

Курс от Whizlabs
Средний≈ 4.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

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.

Навыки, которые вы освоите

Responsible AILarge Language ModelingVersion ControlModel DeploymentData EthicsModel OptimizationAI WorkflowsDeep LearningLLM ApplicationArtificial IntelligenceGenerative AIMachine LearningInformation PrivacyMLOps (Machine Learning Operations)

Программа курса

3 модулей · 35 учебных материалов

01Experimentation and Hyperparameter Tuning12 материалов

LLM Optimization & Experimentation

Welcome to the CourseЧтениеOverview of Experimentation and Hyperparameter TuningЧтениеMeet and GreetОбсуждениеPrinciples for Designing Experiments with Large Language Models (LLMs)Видео

Учитесь у экспертов

Whizlabs Instructor

Преподаватель курса

NVIDIA: LLM Experimentation, Deployment, and Ethical AI
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 4.6 ч

3 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Пушту, Испанский, Дари, Японский, Казахский

Часть программы вашего университета
Hyperparameter Tuning of LLMsВидео
A/B TestingВидео
Importance of Version Control SystemsВидео
Understanding NVIDIA BioNeMo LLM serviceВидео
What are NVIDIA AI Agents ?Видео
Using the Mixture of Experts in LLM ArchitecturesВидео
LLM Optimization & Experimentation - Knowledge checkЗадание
Experimentation and Hyperparameter Tuning - AssessmentЗадание
02NVIDIA AI Services and Optimization11 материалов

NVIDIA AI Technologies and Tools Overview

Overview of NVIDIA AI Services and OptimizationЧтениеIntroducing NVIDIA Tensor-RTВидеоUnderstanding NVIDIA TritonВидеоNVIDIA AI WorkflowsВидеоLogistic and Route Optimization - cuOptВидеоNVIDIA RIVAВидеоRecommender System - MerlinВидеоUnderstanding NVIDIA NGCВидеоExam Tips : ExperimentationВидеоNVIDIA AI Technologies and Tools Overview - Knowledge checkЗаданиеNVIDIA AI Services and Optimization - AssessmentЗадание
03Ethical AI and Trustworthiness12 материалов

Ethical AI Practices

Overview of Ethical AI and TrustworthinessЧтениеEthical Principles of Trustworthy AIВидеоData privacy and the importance of data consent.ВидеоNVIDIA in improving AI Trust WorthinessВидеоNVIDIA: Tackling Bias in AI Systems ProcessingВидеоRegistration Process & System SetupВидеоMistakes to avoid before taking the ExaminationВидеоConclusionВидеоEthical AI Practices - Knowledge checkЗаданиеEthical AI and Trustworthiness - AssessmentЗаданиеKey Takeaways of the courseЧтениеCourse ConclusionЧтение