Section 1: Introduction to AI concepts - LLM's & RAG LLM's
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Lecture 1: What this course offers? FAQ"s -Must Watch (9:12)
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Lecture 2: Course outcome - Setting the stage of expectation
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Lecture 3: Introduction to Artificial Intelligence and LLM's - How they work (6:17)
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Lecture 4: Overview of popular LLM"s and Challenges with these general LLM's (6:15)
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Lecture 5: What is Retrieval Augmented Generation (RAG)? Understand its Architecture (12:39)
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Lecture 6: End to end flow in RAG Architecture and its key advantages (12:07)
Section2: Understand RAG (Retrieval Augmented Generation) - LLM Architecture with Usecase
Section 3: Getting started with Practice LLM's and the approach to evaluate /Test
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Lecture 9: Course resources download
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Lecture 10: Demo of Practice RAG LLM's to evaluate and write test automation scripts (6:51)
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Lecture 11: Understanding implementation part of practice RAG LLM's to understand context (8:36)
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Lecture 12: Understand conversational LLM scenarios and how they are applied to RAG Arch (5:47)
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Lecture 13: Understand the Metric benchmarks for Document Retrieval system in LLM (8:12)
Section 4: Setup Python & Pytest Environment with RAGAS LLM Evaluation Package Libraries
Section 5: Programmatic solution to evaluate LLM Metrics with Langchain and RAGAS Libraries
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Lecture 18: Making connection with OpenAI using Langchain Framework for RAGAS (15:49)
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Lecture 19: End to end -Evaluate LLM for ContextPrecision metric with SingleTurn Test data (20:38)
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Lecture 20: Metrics document download
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Lecture 21: Communicate with LLM's using API Post call to dynamically get responses (9:51)
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Lecture 22: Evaluate LLM for Context Recall Metric with RAGAS Pytest Test example (13:22)
Section 6: Optimize LLM Evaluation tests with Pytest Fixtures & Parameterization techniques
Section 7: Evaluate LLM Core Metrics and importance of EvalDataSet in RAGAS Framework
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Lecture 26: Understand LLM's Faithfulness and Response relevance metrics conceptually (4:56)
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Lecture 27: Build LLM Evaluation script to test Faithfulness benchmarks using RAGAS (9:42)
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Lecture 28: Reading Test data from external json file to LLM evaluation scripts (9:58)
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Lecture 29: Understand how Metrics are used at different places of RAG LLM Architecture (10:34)
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Lecture 30: Factual Correctness - Build a single Test to evaluate multiple LLM metrics (12:02)
Section 8: Upload LLM Evaluation results & Test LLM for Multi Conversational Chat History
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Lecture 31: Understand EvaluationDataSet and how it help in evaluating Multiple metrics (9:41)
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Lecture 32: Upload the LLM Metrics evaluation results into RAGAS dashboard portal visually Lesson (8:22)
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Lecture 33: How to evaluate RAG LLM with multi conversational history chat (7:59)
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Lecture 34: Build LLM Evaluation Test which can evaluate multi conversation - example (17:42)
Section 9: Create Test Data dynamically to evaluate LLM & Generate Rubrics Evaluation Score
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Lecture 35: How to Create Test Data using RAGAS Framework to evaluate LLM (15:02)
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Lecture 36: Load the external docs into Langchain utils to analyze and extract test data (8:52)
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Lecture 37: Install and configure NLTK package to scan the LLM documents & generating tests (20:11)
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Lecture 38: Generate Rubrics based Criteria Scoring to evaluate the quality of LLM responses (11:46)
Section 10: Conclusion and next steps!
Section 11: Optional - Learn Python Fundamentals with examples
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Lecture 41: Python hello world Program with Basics (8:35)
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Lecture 42: Datatypes in python and how to get the Type at run time (5:17)
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Lecture 43: List Datatype and its operations to manipulate (12:47)
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Lecture 44: Tuple and Dictionary Data types in Python with examples (8:28)
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Lecture 45: If else condition in python with working examples (3:10)
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Lecture 46: How to Create Dictionaries at run time and add data into it (7:55)
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Lecture 47: How loops work in Python and importance of code idendation (8:58)
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Lecture 48: Programming examples using for loop - 1 (4:17)
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Lecture 49: Programming examples using While loop - 2 (10:28)
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Lecture 51: OOPS Principles : Classes and objects in Python (7:38)
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Lecture 50: What are functions? How to use them in Python (10:46)
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Lecture 52: What is Constructor and its role in Object oriented programming (13:38)
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Lecture 53: Inheritance concepts with examples in Python (12:12)
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Lecture 54: Strings and its functions in python (9:53)
Section 12: Optional - Overview of Pytest Framework basics with examples
