Ementorhub

What you'll learn

Train and evaluate generative AI models using real-world techniques

Apply Retrieval Augmented Generation (RAG) to improve output accuracy

Understand emerging trends in GenAI architecture and deployment

Translate GenAI advancements into practical, industry-ready solutions

Skills you'll gain

Scalability

Innovation

Real Time Data

ChatGPT

PyTorch (Machine Learning Library)

Emerging Technologies

Tensorflow

Large Language Modeling

Generative AI

Deep Learning

Artificial Intelligence and Machine Learning (AI/ML)

OpenAI

Data Ethics

Prompt Engineering

Natural Language Processing

There are 2 modules in this course

To be successful in this course, you should have a foundational understanding of machine learning, language models, and basic Python programming. By the end of this course, you will be able to: - Train and Evaluate GenAI Models: Build and assess model quality using proven techniques - Enhance Outputs with RAG: Apply retrieval-augmented generation for more accurate responses - Track Emerging Trends: Understand scalable architectures and real-time GenAI innovations - Prepare for Industry Use: Translate GenAI advancements into real-world business applications Ideal for AI practitioners, data scientists, and ML engineers advancing their generative AI expertise.

Training, Evaluation, and Future of Generative AI