Udemy

GenAI: Function Calling, Whisper, LangChain (UPDATED 2024)

立即報名
  • 490 名學生
  • 更新於 12/2024
4.4
(40 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
2 小時 27 分鐘
教學語言
英語
授課導師
Sandra L. Sorel
評分
4.4
(40 個評分)
3次瀏覽

課程簡介

GenAI: Function Calling, Whisper, LangChain (UPDATED 2024)

Hands-on projects (JS & Python) to get started fast with Conversational AI, Speech-to-text, Function calling & LangChain

- The OpenAI API is one of the most exciting advancements in the world of natural language and code processing.

- Its powerful models and flexible endpoints offer a wealth of possibilities for web developers looking to take their skills to the next level.

- In this course, you'll dive into the world of OpenAI APIs and GPT language models. Our focus will be on the completions endpoint and how it can be applied to text completion and various other language-processing tasks.

- Students will work on an end-to-end Generative AI project incorporating the learned concepts.

The course includes Projects, Hands-on Labs, Case Studies and Real-world Applications.

# 1:  Introduction to Generative AI :

  • with the OpenAI API to solve a wide range of language processing tasks, including :

    • content generation, summarization, semantic search, and sentiment analysis

  • a quickstart Tutorial to gain experience and build your first AI-powered application with the APIs and the large language models (LLMs).

    • You will learn how to build a simple sample node application. 

    • Along the way, you’ll learn key concepts and techniques :

      • authentication with the API key,

      • prompt design, adjust settings and generate completions

# 2: The Chat models Models:

  • explore the different language models available through the OpenAI API, including the cutting-edge GPT language model

  • integrate the Chat completion API to create an AI-agent

# 3: Speech-to-Text

  • discover the Audio Whisper API to turn audio files into transcriptions

  • implementing Speech-to-Text to convert podcast audio samples into text

# 4: Function Calling in AI Systems

  • extend the LLMs capacities

  • and give the language models the ability to call external APIs and generate extended responses.

# 5: Experiment with LangChain :  a framework to easily create applications with the generative models


# Target and intended audience

Whether you're a seasoned web developer with years of experience or just starting, this course is designed to help you take your skills to the next level.

  • For Web Developers of All Levels

  • Basics of Node JS, ReactJS, and Python

  • No prior programming experience is required, and the course is suitable for developers of all levels, from beginners to advanced.

# Requirements and prerequisites for the course :

  • Basics of web development: HTML,  CSS

  • Some basic programming language

  • The javascript fundamentals and Python


In this comprehensive course, you will gain a deep understanding of the OpenAI API and its capabilities, along with hands-on experience in building your applications using Node.js, ReactJS, and Python.

So why wait?  Enroll now and unleash the full potential of AI and build your first nextGen application.

課程章節

  • 8 個章節
  • 46 堂課
  • 第 1 章 Introduction
  • 第 2 章 GPT models : integrating AI into web projects (Python Quickstart)
  • 第 3 章 Introduction to the ChatGPT AI and the Chat language models (NodeJS)
  • 第 4 章 Build a REST API (NodeJS & ExpressJS)
  • 第 5 章 Build a REST API : connect a React client application
  • 第 6 章 Extend the GPT models capacities with Function Calling (Node.js)
  • 第 7 章 Speech-2-Text (Whisper Audio API): convert audio to text (Python)
  • 第 8 章 LangChain Framework : chain and combine LLM's capabilities (Javascript)

課程內容

  • OpenAI API : learn to interact with the language models and integrate AI into web projects (Javascript and Python)
  • By the end of the course, students will be able to integrate GPT models into various applications, including chatbots and content generators.
  • Chat Completions API : learn to set up and integrate the Chat Completions API into existing projects
  • Function Calling : extend the Large Languages models (LLMs)'s capacities with the ability to call external APIs
  • Speech-to-Text (Whisper Audio) : set up a simple use-case in Python to turn audio files into transcripts
  • Langchain : to simplify the creation of applications using Large Languages models (LLMs)
  • [PROJECT] (Python) : quickstart example to integrate an intelligence layer into a web project
  • [PROJECT] (Nodejs) : Create a customized Chatbot with the Chat language models
  • [PROJECT] (Python) : convert audio podcast samples to text with the Whisper Audio API
  • [PROJECT] (LangChain Javascript) : Build a transcriber and summarizer app with the OpenAI LLMs, Whisper Audio API and the Summarization Chain


評價

  • N
    Neethu Vm
    5.0

    worthful course

  • J
    Juan Carlos Correa Arango
    5.0

    Thanks.

  • S
    Sankar N
    4.0

    Good

  • N
    Nwoye Shedrack
    5.0

    The tutor explanation is satisfying.

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