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Crafting Generative AI Web Apps with Streamlit & LangChain
Rating: 3.6 out of 5(20 ratings)
1,162 students

Crafting Generative AI Web Apps with Streamlit & LangChain

From Zero to AI Hero: Build & Deploy Cutting-Edge AI Web Apps with Streamlit, LangChain, NLTK & External APIs
Created byViSTEM: Empowering Minds
Last updated 9/2024
English
English [Auto],

What you'll learn

  • Build a comprehensive AI-powered web application for research papers, integrating features learned throughout the course
  • Gain a foundational understanding of artificial intelligence and its applications in web development
  • Develop proficiency in using Streamlit to create engaging and dynamic web applications with interactive components
  • Learn how to effectively use LangChain to integrate and manage AI models within your applications
  • Acquire skills in managing and persisting state across user interactions in Streamlit apps to enhance user experience
  • Create a functional text summarizer using natural language processing techniques to extract key information from texts
  • Learn how to access and use the arXiv API to retrieve and manage academic research papers and metadata

Course content

3 sections • 13 lectures • 1h 11m total length

  • Introduction3:18

    Explore building generative AI web apps with Streamlit and Lang Chain, integrating NLTK text processing, arXiv API access, and conversational agents on a research paper platform.

  • Streamlit Basics10:33

    Explore how Streamlit enables turning data scripts into shareable web apps for data science and machine learning, including interactive elements such as text input, sliders, buttons, select boxes, and dataframes.

  • State Management in Streamlit1:41
  • How to setup OpenAI0:50
  • LangChain Basics6:33

    Master LangChain basics by building an LM chain with a prompt template to translate English text into French, using an OpenAI API key and GPT-3.5 turbo.

  • Build a Text Summarizer with NLP12:14

    Build a text summarizer using natural language processing with NLTK, leveraging stopwords, Punkt for the tokenizer, a frequency table, and sentence scoring to generate a concise summary.

Requirements

  • Beginner Python Experience

Description

Unlock the power of artificial intelligence by learning how to build dynamic AI-powered web applications with Streamlit and LangChain. This hands-on course will guide you from understanding the basics of AI to implementing advanced features like NLP-based text summarization and API integrations. Perfect for developers, data scientists, and AI enthusiasts, this course offers a step-by-step approach to mastering the tools needed to create your own AI-driven web apps.


What You Will Learn:

In this course, you'll gain a solid understanding of AI fundamentals and learn to build interactive web applications using Streamlit. You'll explore LangChain integration, master state management in Streamlit, and apply natural language processing to create a text summarizer. Additionally, you'll set up the arXiv API and utilize LangChain's output parsers to manage research data. By the end of the course, you'll have the skills to develop your own AI-powered web apps, culminating in two final projects that showcase your ability to build a sophisticated AI research paper web application.


By the end of this course, you’ll have the skills and confidence to build your own AI web applications, making advanced AI accessible and interactive. Whether you're looking to enhance your career or embark on new projects, this course is your gateway to building AI-driven solutions.

Who this course is for:

  • Developers aiming to build and deploy AI-powered web applications
  • Developers wanting to integrate AI functionalities into their web projects
  • Professionals looking to apply AI and NLP in real-world applications.
  • Students and researchers needing practical AI and web development experience
  • Engineers wanting to expand their skills with AI and web development tools
  • Teachers wanting to include AI and web development in their curriculum

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