Ementorhub

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

A/B Testing

Tensorflow

Artificial Intelligence

Natural Language Processing

PyTorch (Machine Learning Library)

Data Ethics

Performance Tuning

Version Control

Application Deployment

Generative AI

Scalability

Deep Learning

MLOps (Machine Learning Operations)

Large Language Modeling

Information Privacy

There are 3 modules in this course

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.

NVIDIA AI Services and Optimization

Ethical AI and Trustworthiness