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Generative AI – Syllabus
Generative AI – Syllabus Table Of Contents: GenAI Road Map For Beginners. GenAI Using Langchain. Introduction To Langchain. Langchain Components. Langchain Models. Prompts In Langchain. Structured Output In Langchain. Output Parser In Langchain. Chains In Langchain. What Is Runnable In Langchain? Langchain Runnables. Document Loaders In Langchain. Text Splitter In Langchain. Vector Stores In Langchain. Retrievers In LangChain. Retrieval Augmented Generation. Building RAG system In LangChain. Tools In LangChain. Tool Calling In LangChain.
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Generative AI
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GenAI – Internal Q & A Model
Gen AI – Q & A Model Table Of Contents: Define The Problem Statement. Steps To Complete This Use Case. (1) Define The Problem Statement (2) Step-by-Step Guide to Build HR Policy Assistant (RAG-based) (3) Collect & Prepare HR Documents. (1) Install Required Libraries pdfplumber python-docx unstructured pip install pdfplumber python-docx unstructured (2) Load and Extract Text from Documents import os import pdfplumber from docx import Document def load_text_from_pdf(file_path): text = “” with pdfplumber.open(file_path) as pdf: for page in pdf.pages: text += page.extract_text() + “n” return text def load_text_from_docx(file_path): doc = Document(file_path) return “n”.join([para.text for para in doc.paragraphs]) def load_text_from_txt(file_path):
