Developing Generative AI Solutions

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Developing Generative AI Solutions

Coursera · Intermediate ·🔍 RAG & Vector Search ·3mo ago

Key Takeaways

Defines generative AI application lifecycle using foundation models

Original Description

In this course, you will explore the generative artificial intelligence (generative AI) application lifecycle, which includes the following: - Defining a business use case - Selecting a foundation model (FM) - Improving the performance of an FM - Evaluating the performance of an FM - Deployment and its impact on business objectives This course is a primer to generative AI courses, which dive deeper into concepts related to customizing an FM using prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

⚡
Your AI Keeps Making Things Up. RAG Is How You Make It Use Real Facts Instead.
Learn how to use RAG to make your AI provide accurate answers based on real facts instead of making things up
Medium · RAG
 ⚡
Evaluation Metrics for RAG: Measure Retrieval, Generation, and End-to-End Quality With Numbers That…
Learn to evaluate RAG models using metrics that measure retrieval, generation, and end-to-end quality
Medium · AI
 ⚡
Evaluation Metrics for RAG: Measure Retrieval, Generation, and End-to-End Quality With Numbers That…
Learn to evaluate RAG models using metrics that measure retrieval, generation, and end-to-end quality
Medium · Data Science
 ⚡
When Does HyDE Help RAG? I Tested 3 Query Types and It Failed on Two
Learn when HyDE retrieval helps or hinders RAG performance across different query types, and why it matters for improving search accuracy
Medium · AI
Up next
RRF vs DBSF with Qdrant: Hybrid Retrieval Fusion for RAG in Python
Professor Py: AI Engineering
Watch →