What you'll learn

Learn to Build a Custom Generative AI Application
Understand the Role of Open AI's APIs in Solution Design
Grasp the Concepts of Large Language Models and Fine-Tuning
Learn to Integrate Generative AI Models into Existing Workflows

Requirements

Basic Understanding of Capabilities of Generative AI Products like ChatGPT
The Basics of Working of an API
Preliminary Level Understanding of Python Programming

Description

Welcome to "Generative AI Application Development," a comprehensive, step-by-step tutorial designed to equip you with the skills and knowledge needed to build powerful generative AI applications. This course takes a structured approach to developing applications using OpenAI's state-of-the-art Generative AI models, focusing on text-based solutions. The course will use 3 examples to explain the process of Generative AI based application Development.In this course, you will:Explore the fundamentals of Generative AI and its applications.Learn the technology behind Generative AI Learn the entire development process, from defining the problem to designing and implementing your solution.Gain hands-on experience in building and fine-tuning text-based AI models.Understand how to test, optimize, and deploy generative AI applications effectively.We'll also cover best practices for scaling and maintaining your AI solutions, ensuring you're ready to tackle real-world projects.Whether you're a developer looking to expand your AI skills, or someone interested in building cutting-edge applications, this course is designed to provide you with the tools and confidence to succeed.Please note: This course is for educational purposes only. Learners are encouraged to perform due diligence, follow Organization guidelines and consult experts when applying these concepts in real-world scenarios. Also, kindly note that this course does not make any commitment for job offers or assistance.

Overview

Section 1: Introduction
Lecture 1 Introduction to the Instructors
Lecture 2 What is Expected from the Course
Section 2: A Comprehensive

Overview

of Generative AI
Lecture 3 Industry wide adoption of Generative AI
Lecture 4 An

Overview

of Generative AI
Lecture 5 Generative AI Products
Lecture 6 What is a Large Language Model (LLM)
Lecture 7 Architecture of a Large Language Model
Lecture 8 Pre-Trained Models for Generative AI
Lecture 9 Pre-Trained Models for Text Processing
Lecture 10 Criteria to Select a Pre-trained Model
Lecture 11 Importance of LLM Documentation
Lecture 12 Research Rally
Section 3: Solution Development Options - API and Local Deployment
Lecture 13 Section Introduction
Lecture 14 What is an API and How Does it Work?
Lecture 15 Solution Development - APIs and Local Deployment
Lecture 16 Project Phases Workflow - Without API (Local deployment)
Lecture 17 Project Phases Workflow - Using API
Lecture 18 Let's Set up the Lab
Section 4: Sentiment Analysis with Large Language Model
Lecture 19 Sentiment Analysis

Overview

and Approaches
Lecture 20 Pros and Cons of Sentiment Analysis with Generative AI
Lecture 21 Code Walkthrough in Google Collab - Sentiment Analysis
Section 5: Language Translation with Large Language Model
Lecture 22 Language Translation - Need and Current Approaches
Lecture 23 Pros and Cons of using Generative AI for Translation
Lecture 24 Code Walkthrough in Google Collab - Text Translation
Section 6: Factors to Consider During Generative AI Solution Development
Lecture 25 Testing Generative AI Applications
Lecture 26 Deploy Generative AI Applications
Lecture 27 Fine-Tuning - Customise a Pre-trained LLM
Lecture 28 Pricing Considerations for LLM Models
Lecture 29 Research Rally - Pricing for GPT Models
Lecture 30 Responsible AI Usage
Lecture 31 The future of Large Language Models
Section 7: Conclusion
Lecture 32 Thank you
Coders and Developers Who Develop Custom Solutions,Solution Architects and Design Experts,Project Managers Who Manage an Application Development Project,Business Professionals Interested in

Overview

of Application Development

Homepage:

https://www.udemy.com/course/mastering-text-processing-with-large-language-models/