[New] 2024: The Generative Ai Lifecycle: A Primer

[New] 2024: The Generative Ai Lifecycle: A Primer
Published 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.22 GB | Duration: 3h 4m

A Primer, Prompt Engineering, RAG, PEFT, FINE TUNING, Evaluation Metrics and Benchmarks

What you'll learn

GEN AI lifecycle

Model Selection

Prompt Engineering

Retrieval Augmented Generation (RAG) IN LLMs

FINE TUNING of LLM Model

Tools Agents

Evaluation Metrics

Requirements

Interest in Generative AI

No programming experience needed

Description

IntroductionGenerative AI has rapidly emerged as a transformative force, revolutionizing industries from content creation to drug discovery. At the heart of this revolution lie Large Language Models (LLMs), which have the potential to revolutionize how we interact with information and generate new content.This course serves as a foundational introduction to the generative AI lifecycle, providing you with a comprehensive overview of the key stages involved in developing and deploying LLMs. By understanding the entire process, you'll gain valuable insights into the challenges, opportunities, and best practices associated with generative AI.Course ObjectivesGain a foundational understanding of the key stages in the generative AI lifecycle.Explore the role of LLMs in driving innovation and problem-solving.Learn about the importance of data quality and preprocessing in LLM development.Understand the different techniques used to train and fine-tune LLMs.Explore the role of evaluation metrics in assessing LLM performance.Discover the potential applications of LLMs across various domains.Course StructureThis course is designed to provide a concise overview of the generative AI lifecycle. Each lecture will introduce a key stage, providing you with essential information and context. For a more in-depth exploration of each topic, we recommend our comprehensive course, "Mastering Generative AI: From LLMs to Applications."Key Topics CoveredIntroduction to Generative AI and LLMsThe Generative AI LifecycleModel Selection for Pre-trained modelsModel Training and Fine-TuningEvaluation Metrics and BenchmarkingApplications of Generative AIBy completing this course, you'll have a solid foundation in the generative AI lifecycle, enabling you to make informed decisions and effectively leverage LLMs in your work. We encourage you to explore our more advanced course, "Mastering Generative AI: From LLMs to Applications," for a deeper dive into each topic and practical hands-on experience.

Overview

Section 1: Introduction

Lecture 1 Introduction to Gen-AI

Lecture 2 GEN-AI Lifecycle

Lecture 3 How to improve LLM responses

Lecture 4 Prompt Engineering

Lecture 5 Introduction to RAG -Retrieval Augmented Generation IN LLMs

Lecture 6 Introduction to Prompt tuning

Lecture 7 Quantization intuition challenges and need

Lecture 8 Fine Tuning Model Intuition

Lecture 9 Introduction to LLM Fine Tuning

Lecture 10 Evaluation Metrics Rouge Score

Lecture 11 BLEU Score

Lecture 12 Introduction to RLHF

Lecture 13 Evaluation Benchmarks : GLUE SUPER GLUE

Lecture 14 Evaluation Benchmarks : HELM

Lecture 15 Tools and Agents

Lecture 16 Loading your LLM using Langchain

Tech managers,directors,ML Engineers,other tech leaders,Software Engineers,AI Developers,Data Scientists

We need your support!
Make a donation to help us stay online
        
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
	
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem

Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u

USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm