-
AgenticAI – Understanding Agentic AI ?
Agentic AI – Understanding Agentic AI . Table Of Contents: What Is Agentic AI ? Key Features of Agentic AI. How Is It Different From Regular AI? Examples Of Agentic AI. How To Mention The Goals Of The AgenticAI Model ? (1) What Is Agentic AI ? Agentic AI is a type of smart computer program that can think for itself, make decisions, and take actions to reach a goal—kind of like a little robot brain with a mission. (2) Key Features of Agentic AI: (3) How Is It Different From Regular AI? Regular AI waits for you to tell
-
Agentic AI – Syllabus
Agentic AI Syllabus Table Of Contents Foundatation Of Agentic AI. User Interaction Layer Of Agentic AI. Input Validation & Guardrails Layer Of Agentic AI. Orchestration / Control Layer Of Agentic AI. Agent Selection & Role Assignment Layer Of Agentic AI. Reasoning & Planning Layer (Inside the Agent) Of Agentic AI. Knowledge Retrieval Layer (RAG) Of Agentic AI. Memory Layer (Context & Experience) Of Agentic AI. LLM (Model) Layer — Intelligence Core Of Agentic AI. Tool & Action Layer (Execution) Of Agentic AI. Observation & Feedback Layer Of Agentic AI. Reflection & Iteration Layer Of Agentic AI. Output Validation & Safety Layer Of
-
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):
