Udemy - AI QA Testing AI Apps with DeepEval, RAGAs, HF & Ollama

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Free Download Udemy - AI QA Testing AI Apps with DeepEval, RAGAs, HF & Ollama
Published: 3/2025
Created by: Karthik KK
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 56 Lectures ( 5h 56m ) | Size: 2.91 GB

Roadmap to become AI QA Engineer to test LLMs and AI Application using DeepEval, RAGAs and HF Evaluate with Local LLMs
What you'll learn
Understand the purpose of Testing LLM and LLM based Application
Understand DeepEval and RAGAs in detail from complete ground up
Understand different metrics and evaluations to evaluate LLMs and LLM based app using DeepEval and RAGAs
Understand the advanced concepts of DeepEval and RAGAs
Testing RAG based application using DeepEval and RAGAs
Testing AI Agents using DeepEval to understand how tool callings can be tested
Requirements
Basics of working with LLM like using ChatGPT
Basics of any programing language like Java or Javascript
Basics of python will be a plus
Description
AI QA: Testing AI Apps with DeepEval, RAGAs, HF & OllamaMaster the essential skills for testing and evaluating AI applications, particularly Large Language Models (LLMs). This hands-on course equips developers, data scientists, and AI practitioners with cutting-edge techniques to assess AI performance, identify biases, and ensure robust application development.Topics Covered:Section 1: Foundations of AI Application Testing (Introduction to LLM testing, AI application types, evaluation metrics, LLM evaluation libraries).Section 2: Local LLM Deployment with Ollama (Local LLM deployment, AI models, running LLMs locally, Ollama implementation, GUI/CLI, setting up Ollama as API).Section 3: Environment Setup (Jupyter Notebook for tests, setting up Confident AI).Section 4: DeepEval Basics (Traditional LLM testing, first DeepEval code for AnswerRelevance, Context Precision, evaluating in Confident AI, testing with local LLM, understanding LLMTestCases and Goldens).Section 5: Advanced LLM Evaluation (LangChain for LLMs, evaluating Answer Relevancy, Context Precision, bias detection, custom criteria with GEval, advanced bias testing).Section 6: RAG Testing with DeepEval (Introduction to RAG, understanding RAG apps, demo, creating GEval for RAG, testing for conciseness & completeness).Section 7: Advanced RAG Testing with DeepEval (Creating multiple test data, Goldens in Confident AI, actual output and retrieval context, LLMTestCases from dataset, running evaluation for RAG).Section 8: Testing AI Agents and Tool Callings (Understanding AI Agents, working with agents, testing agents with and without actual systems, testing with multiple datasets).Section 9: Evaluating LLMs using RAGAS (Introduction to RAGAS, Context Recall, Noise Sensitivity, MultiTurnSample, general purpose metrics for summaries and harmfulness).Section 10: Testing RAG applications with RAGAS (Introduction and setup, creating retrievers and vector stores, MultiTurnSample dataset for RAG, evaluating RAG with RAGAS).
Who this course is for
QA Engineers
AI QA Test Engineers
Business Analyst
AI Engineers
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2.78 GB | 13min 9s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

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FileName :1 -Introduction to Testing of LLM Applications.mp4 | Size: (62.01 MB)
FileName :2 -Understanding different types of AI Applications.mp4 | Size: (104.25 MB)
FileName :3 -Understanding different Evaluation Metrics to evaluate AI Applications.mp4 | Size: (45.33 MB)
FileName :4 -Different LLM libraries to Evaluate LLMs and LLM Applications.mp4 | Size: (72.26 MB)
FileName :1 -Introduction and setup.mp4 | Size: (34.56 MB)
FileName :2 -Creating Retriever for Actuals and Vector Stores for Context.mp4 | Size: (26.25 MB)
FileName :3 -Creating MultiTurnSample DataSet for RAG Application to Test.mp4 | Size: (55.53 MB)
FileName :4 -Evaluating RAG with RAGAs.mp4 | Size: (46.86 MB)
FileName :1 -Introduction.mp4 | Size: (28.64 MB)
FileName :2 -Understanding different Models.mp4 | Size: (21.09 MB)
FileName :3 -Running LLM locally using Ollama.mp4 | Size: (61.86 MB)
FileName :4 -Using Ollama Models in GUI.mp4 | Size: (29.36 MB)
FileName :5 -Understanding Ollama with few more command line interface commands.mp4 | Size: (13.45 MB)
FileName :6 -Starting Ollama with API to run as a API server.mp4 | Size: (31.42 MB)
FileName :1 -Introduction.mp4 | Size: (72.12 MB)
FileName :2 -Creating Jupyter Notebook for Tests and Test Execution.mp4 | Size: (25.67 MB)
FileName :3 -Setting up Confident AI.mp4 | Size: (52.6 MB)
FileName :1 -Testing LLMs with Traditional Approach.mp4 | Size: (40.56 MB)
FileName :2 -Writing First DeepEval Code for AnswerRelevance.mp4 | Size: (57.39 MB)
FileName :3 -Testing LLMs for Context Precision.mp4 | Size: (101.04 MB)
FileName :4 -Evaluating LLMs and check the Evaluated Testcases in Confident AI.mp4 | Size: (72.78 MB)
FileName :5 -Running EvaluationTests of LLMs (DeepSeek R1) using Local LLM with Ollama.mp4 | Size: (32.92 MB)
FileName :6 -Understanding LLMTestCases in Depth.mp4 | Size: (71.3 MB)
FileName :7 -Understanding Golden And Dataset in Depth.mp4 | Size: (76.62 MB)
FileName :8 -Creating Goldens using List Array.mp4 | Size: (66.47 MB)
FileName :1 -Introduction.mp4 | Size: (32.37 MB)
FileName :2 -Using LangChain to Invoke LLM for our Test Source.mp4 | Size: (58.1 MB)
FileName :3 -Evaluating LLM with Answer Relevancy using Local LLM.mp4 | Size: (58.94 MB)
FileName :4 -Evaluating LLM with Context Precision using Local LLM.mp4 | Size: (90.4 MB)
FileName :5 -Evaluating LLM with Bias using Local LLMs.mp4 | Size: (51.12 MB)
FileName :6 -Using GEval for Custom Criteria to Evaluate LLM.mp4 | Size: (75.69 MB)
FileName :7 -Using GEval to perform Bias Testing using Local LLMs.mp4 | Size: (52.12 MB)
FileName :1 -Introduction to RAG.mp4 | Size: (39.49 MB)
FileName :2 -Understanding RAG application.mp4 | Size: (38.19 MB)
FileName :3 -Working with RAG application as a Demo.mp4 | Size: (70.88 MB)
FileName :4 -Creating GEval for RAG application.mp4 | Size: (61.6 MB)
FileName :5 -Testing RAG with GEval for Conciseness & Completeness Metrics.mp4 | Size: (66.09 MB)
FileName :1 -Introduction.mp4 | Size: (36.82 MB)
FileName :2 -Creating Multiple Test Data.mp4 | Size: (41.72 MB)
FileName :3 -Creating Goldens and Pushing it to Confident AI.mp4 | Size: (21.71 MB)
FileName :4 -Creating Actual Output and Retrieval Context for LLMTestCase.mp4 | Size: (63.52 MB)
FileName :5 -Creating LLMTestCases with Actual And Retrieval Context from Dataset.mp4 | Size: (39.68 MB)
FileName :6 -Running Evaluation to verify RAG and check the same from Confident AI.mp4 | Size: (49.06 MB)
FileName :1 -Understanding AI Agents.mp4 | Size: (47.49 MB)
FileName :2 -Working with an AI Agent.mp4 | Size: (55.64 MB)
FileName :3 -Understanding how to test an AI Agent.mp4 | Size: (9.74 MB)
FileName :4 -Testing an AI Agent without using Actual System Under Test.mp4 | Size: (74.67 MB)
FileName :5 -Testing an AI Agent without using Actual SUT (Contd ).mp4 | Size: (42.38 MB)
FileName :6 -Testing AI Agents with Actual System instead of Fake System.mp4 | Size: (43.14 MB)
FileName :7 -Testing AI Agents with Multiple Datasets.mp4 | Size: (59.35 MB)
FileName :1 -Introduction.mp4 | Size: (57.8 MB)
FileName :2 -Context Recall with RAGAs.mp4 | Size: (79.71 MB)
FileName :3 -Noise Sensitivity Metrics with RAGAs.mp4 | Size: (42.87 MB)
FileName :4 -MultiTurnSample with RAGAs along with Evaluate.mp4 | Size: (84.09 MB)
FileName :5 -General Purpose Metrics - Aspect Critics For summary of data from LLM.mp4 | Size: (73.26 MB)
FileName :6 -General Purpose Metrics - Detect Harmfulness from the content generated.mp4 | Size: (63.25 MB)

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