Mastering Generative AI engineering of tomorrow

Mastering Generative AI engineering of tomorrow, available at $34.99, with 18 lectures, 1 quizzes, and has 11 subscribers.

You will learn about Understand the theory, the economic as well as the technical reasoning behind generative Artificial Intelligence Master multiple Large Language Models – LLMs Learn how to approach the development of GenAI models Master Foundational Models completely Discover value chain creation with generative AI Master Variational Autoencoders Create a powerful versatile GenAI application from scratch Learn how vector databases work Acquire a great intuition how to introduce GenAI to your team Master Stable Diffusion Make accurate predictions about mainstream adoption of various GenAI approaches Learn to make reliable analysis on AI open source projects Create strong added value to your business Use GenAI for personal purpose Master LLM powered autonomous agents Learn about FinGPT – the framework for creating LLM for financial applications Master LoRA – Low-Rank Adaptation of Large Language Models Understand the theory behind Large Language Models and how they work under the hood Learn about promising current and future use cases that can be tackled with GenAI Learn to understand advanced tech like Transformers This course is ideal for individuals who are This course is for a diverse audience, including AI/ML enthusiasts, data scientists, researchers, students, developers, economists and anyone harboring a curiosity about Generative AI. It is particularly useful for This course is for a diverse audience, including AI/ML enthusiasts, data scientists, researchers, students, developers, economists and anyone harboring a curiosity about Generative AI.

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Summary

Title: Mastering Generative AI engineering of tomorrow

Price: $34.99

Number of Lectures: 18

Number of Quizzes: 1

Number of Published Lectures: 18

Number of Published Quizzes: 1

Number of Curriculum Items: 19

Number of Published Curriculum Objects: 19

Original Price: $34.99

Quality Status: approved

Status: Live

What You Will Learn

Understand the theory, the economic as well as the technical reasoning behind generative Artificial Intelligence

Master multiple Large Language Models – LLMs

Learn how to approach the development of GenAI models

Master Foundational Models completely

Discover value chain creation with generative AI

Master Variational Autoencoders

Create a powerful versatile GenAI application from scratch

Learn how vector databases work

Acquire a great intuition how to introduce GenAI to your team

Master Stable Diffusion

Make accurate predictions about mainstream adoption of various GenAI approaches

Learn to make reliable analysis on AI open source projects

Create strong added value to your business

Use GenAI for personal purpose

Master LLM powered autonomous agents

Learn about FinGPT – the framework for creating LLM for financial applications

Master LoRA – Low-Rank Adaptation of Large Language Models

Understand the theory behind Large Language Models and how they work under the hood

Learn about promising current and future use cases that can be tackled with GenAI

Learn to understand advanced tech like Transformers

Who Should Attend

This course is for a diverse audience, including AI/ML enthusiasts, data scientists, researchers, students, developers, economists and anyone harboring a curiosity about Generative AI.

Target Audiences

This course is for a diverse audience, including AI/ML enthusiasts, data scientists, researchers, students, developers, economists and anyone harboring a curiosity about Generative AI.

Welcome to “Mastering Generative AI engineering of tomorrow”, an in-depth designed course destined to immerse you in the realm of Generative Artificial Intelligence. In this explorative journey, you will uncover the intricacies and extensive capabilities of generative models, engaging with both their theoretical foundations and practical implementations.

The aim of this course is to enable you to build limitless AI applications with the Falcon open-sourced LLM.

Most developers build “wrappers” for AI chatbots which are completely dependent the AI companies providing them, which can at any moment choke off the said applications by changing their terms of use.

With this course you will learn how to build AI applications without relying on third party APIs.

What you will learn:

Understand the theory, the economic as well as the technical reasoning behind generative Artificial Intelligence

Master multiple Large Language Models – LLMs

Learn how to approach the development of GenAI Models

Master Foundational Models

Discover value chain creation with generative AI

Master Variational Autoencoders

Create a powerful versatile limitless GenAI application

Learn how vector databases work

Have a great intuition how to introduce GenAI to your team

Master Stable Diffusion

Make accurate predictions about mainstream adoption of various GenAI approaches

Make reliable analysis on AI open source projects

Create strong added value to your business

Use GenAI for personal purpose

Master LLM powered autonomous agents

Learn about FinGPT – the framework for creating LLM for financial applications

Master LoRA – Low-Rank Adaptation of Large Language Models

Understand the theory behind Large Language Models and how they work under the hood

Learn about promising current and future use cases that can be tackled with GenAI

Learn to understand advanced tech like Transformers

#AI

#ArtificialIntelligence

#OpenAI

#ChatGPT

#Programming

#Finance

#Python

Course Curriculum

Chapter 1: Introduction

Lecture 1: Intro

Lecture 2: Course description

Lecture 3: Where did generative AI come from?

Lecture 4: Artificial Intelligence keywords List

Chapter 2: Part 1 – Technical part

Lecture 1: Variational autoencoders (VAEs) & Generative adversarial networks (GANs)

Lecture 2: Transformers

Lecture 3: Large Language Model – LLM

Lecture 4: Inner workings of LLM

Lecture 5: Stable diffusion

Lecture 6: LoRA – Low-Rank Adaptation of Large Language Models

Chapter 3: Part 2 – Economic part: Use cases and mainstream adoption

Lecture 1: Practical overview of generative AI models

Lecture 2: Advantages of LLMs / generative and other types of AI / Value chain creation

Chapter 4: Part 3 – Building LLM applications for production

Lecture 1: Prompt optimization and evaluation. Prompting. Fine tuning. Vector databases

Lecture 2: LLM Powered Autonomous Agents

Lecture 3: LLM key points

Lecture 4: LLM for finance

Chapter 5: Part 4 – Build own limitless generative AI application with Falcon 40B LLM

Lecture 1: Introduction to the components of your own limitless generative AI application

Lecture 2: Coding the limitless generative AI application

Chapter 6: Quiz

Instructors

Nedim Begic
Computer Research Scientist

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Frequently Asked Questions

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