ChatGPT - Building AI Applications Visually (no-code) from Udemy

Welcome to Building ChatGPT AI Applications Visually (no code) using Flowise and Langchain the ultimate course for effortlessly creating powerful AI solutions using ChatGPT. In this course, you will master the art of building engaging and practical applications that harness the full potential of AI, without the need to delve into coding syntax or complex technical concepts associated with programming languages.

With a 100% visual approach, this course requires no coding background. You will learn to construct useful and robust programs that can be deployed without writing a single line of code.

For example, imagine creating a chatbot that seamlessly integrates within your website, trained on data extracted directly from your website or any relevant source. Through visual techniques, you will learn to scrape information from the websites of your choice, query the collected data, embed the chatbot into your website, and customize its behavior—all without writing code.

In this hands-on course, you'll be actively building 10 projects that range from simple to more advanced applications. We'll begin with an introduction and overview of the course, guiding you through the initial setup. From there, we'll swiftly progress to constructing your first basic AI apps.

We'll focus on a common use case—building chat applications that interact with your own PDF or text files. You'll gain the skills to create a chatbot specifically tailored to your data.

We will demonstrate how to integrate your personalized chatbot into a website and customize its functionality.

You'll discover the process of integrating your AI app as a plugin within the ChatGPT website, enabling it to interact with other ChatGPT plugins.

Finally, we'll guide you through deploying your app into production using the popular Cloud service provider, Render.

Embark on this exciting journey of building AI applications visually, and unlock the potential of ChatGPT to create impressive and impactful solutions. I'm here to support you throughout the course. Let's get started.

What's inside

Learning objectives

Learn how to build ai applications visually -- without writing any code
Learn how to build chat with your own data ai apps
Learn how to create and embed a chatbot right into your website

Integrate your ai app into chatgpt with plugins
Gain hands-on experience with 15 projects

Learn how to build ai applications visually -- without writing any code
Learn how to build chat with your own data ai apps
Learn how to create and embed a chatbot right into your website
Integrate your ai app into chatgpt with plugins
Gain hands-on experience with 15 projects

Syllabus

Introduction

What is a large language model

Setting up the development environment

Build their first AI application

This lecture features website scraping and Q&A. The recording was done previously using a vector database, Pinecone. The steps are the same using the Qdrant vector database. In fact, it is slightly easier in that a namespace does not need to be specified.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Focuses on building AI applications visually, which allows non-technical users to rapidly prototype and deploy AI-powered solutions for their businesses

Uses Flowise and Langchain, which are open-source frameworks that allow developers to orchestrate and manage complex AI workflows and integrations

Requires no coding background, which makes it accessible to individuals with limited technical expertise who want to explore AI application development

Teaches how to create chatbots that interact with PDF and text files, which is useful for building knowledge bases and information retrieval systems

Demonstrates how to deploy AI applications using Render and Replit, which are cloud platforms that offer scalable and cost-effective hosting solutions

Covers integrating AI applications into ChatGPT using plugins, which may require familiarity with the ChatGPT plugin ecosystem and API

Reviews summary

Visual ai application building with chatgpt

According to students, this course offers a highly practical and beginner-friendly introduction to building AI applications visually using Flowise and Langchain, focusing on integrating with custom data and embedding applications. Learners particularly appreciate the no-code approach and the quantity and quality of hands-on projects and demos. While some reviewers found the initial setup could be challenging or parts of the tools evolve, the overall sentiment is strongly positive, highlighting the course's effectiveness in teaching how to build useful AI applications like chatbots that interact with your own documents or websites.

Reliance on external tools may require updates.

"Sometimes the external tools like Flowise or third-party services change, which can make older videos slightly different."

"Keep in mind that the tools used are evolving rapidly, so some steps might look a bit different now."

"While the core concepts are solid, be prepared that updates to Flowise might require minor adjustments on your end."

Instructor is clear, knowledgeable, and helpful.

"The instructor is clear, concise, and easy to follow."

"He explains the concepts well and walks through the builds step-by-step."

"Great instructor who knows the material and presents it effectively."

"I appreciated the detailed explanations provided throughout the lessons."

Course is well-suited for those new to AI/building.

"As someone completely new to building AI apps, this course was an excellent starting point."

"The instructor breaks down potentially complex ideas into easy-to-understand steps."

"Perfect for beginners who want to quickly get hands-on with building AI applications."

"Even without a technical background, I felt empowered to create functional AI tools."

Practical projects are a major strength.

"The best part of this course is the hands-on projects. Building alongside the instructor solidified my understanding."

"Building real applications like chatting with my own PDF was incredibly useful and directly applicable."

"The multiple demos and project builds make this very practical and less theoretical."

"The projects cover a good range of use cases, from simple bots to integrating with websites and data."

"I loved that we built so many different apps; it gave me a lot of confidence to start my own projects."

Build AI apps visually without writing code.

"I wanted to learn how to build AI applications but dreaded the coding... This course delivers on its promise of no-code."

"The visual approach using Flowise makes complex AI concepts accessible even if you have zero programming experience."

"Truly 'no-code'! I was able to build working applications just by following the visual flow diagrams and instructions."

"Great course to learn how to build ChatGPT apps without writing code. Flowise is amazing and easy to use."

"I'm a beginner with no coding background and found this course incredibly easy to follow and understand."

Initial environment setup can be tricky.

"Getting the initial environment set up correctly took me a bit longer than expected."

"Some issues encountered during the setup phase, though troubleshooting helped."

"The very first steps to get Flowise running seemed a little finicky at times."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in ChatGPT - Building AI Applications Visually (no-code) with these activities:

Review Foundational AI Concepts

Show steps

Solidify your understanding of core AI concepts to better grasp the applications built in the course.

Browse courses on Large Language Models

Show steps

Review the basics of neural networks.
Understand the concept of embeddings.
Familiarize yourself with transformer architectures.

Review 'Building Applications with Generative AI'

Show steps

Gain a deeper understanding of generative AI principles and techniques.

View RAG-Driven Generative AI: Build custom... on Amazon

Show steps

Read the chapters on prompt engineering.
Study the examples of building AI applications.
Experiment with the code snippets provided in the book.

Build a Simple Q&A Chatbot

Show steps

Practice building a chatbot to reinforce your understanding of the course material.

Show steps

Choose a dataset of text or documents.
Use Flowise to create a chatbot flow.
Integrate the chatbot with a simple web interface.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Review 'LangChain in Action'

Show steps

Gain a deeper understanding of LangChain and its capabilities.

View Putting Knowledge to Work on Amazon

Show steps

Read the chapters on chains and agents.
Experiment with the code examples provided in the book.
Apply the concepts learned to your own AI projects.

Create a Tutorial on Flowise Components

Show steps

Deepen your understanding of Flowise by creating a tutorial for other learners.

Show steps

Select a specific Flowise component or feature.
Create a video or written tutorial explaining its usage.
Share your tutorial on a relevant online forum.

Contribute to Flowise Documentation

Show steps

Improve your understanding of Flowise by contributing to its open-source documentation.

Show steps

Identify areas in the documentation that need improvement.
Submit a pull request with your changes.

Deploy a Chatbot to a Cloud Platform

Show steps

Solidify your deployment skills by deploying a chatbot to a cloud platform.

Show steps

Choose a cloud platform (e.g., Render, Replit).
Package your Flowise application for deployment.
Configure the cloud platform and deploy your application.
Test the deployed chatbot to ensure it is working correctly.

Career center

Learners who complete ChatGPT - Building AI Applications Visually (no-code) will develop knowledge and skills that may be useful to these careers:

Chatbot Developer

A Chatbot Developer specializes in creating conversational AI agents, and this course is valuable because it focuses extensively on building exactly these types of applications. The course's hands-on projects, such as creating chatbots that interact with PDF files or websites, directly align with the work a Chatbot Developer does. This course's curriculum, which covers integrating a chatbot into a website and customizing its behavior, is a core component of this career. The course also teaches how to integrate an app with ChatGPT using plugins, which is directly relevant to a chatbot developer's scope.

See salaries and explore the career path for Chatbot Developer

AI Application Developer

An AI Application Developer builds and deploys AI-powered tools, and this course directly supports that work by teaching how to create various AI applications using a visual, no-code approach. This role involves designing and implementing AI solutions, and proficiency with no-code tools, as taught in this course, provides a way to rapidly prototype and deploy AI applications. The course gives direct experience in building chatbots, which is a common deliverable of an AI Application Developer. Furthermore, this course teaches how to deploy an app using Render, a common cloud service provider.

See salaries and explore the career path for AI Application Developer

AI Project Manager

An AI Project Manager is responsible for overseeing AI projects from planning to completion. This course provides the manager with an understanding of the building blocks of AI applications, particularly those using visual development tools. This course provides exposure to the AI technology landscape, which will help the manager guide project teams and set realistic expectations. The project style of the course may help the project manager understand project timelines and processes. The course’s focus on chatbots and data integration is especially applicable to AI project management.

See salaries and explore the career path for AI Project Manager

Technology Evangelist

A Technology Evangelist promotes and educates others about the benefits of new technologies, and this course teaches the practical aspects of AI development using a no-code approach. This course is a useful way to demonstrate and explain the capabilities of AI to an audience. The hands-on projects in the course, such as building chatbots and integrating them into websites, can be turned into demonstrations for the evangelist. The course's focus on visually creating AI applications without code is also very relevant for demonstrations.

See salaries and explore the career path for Technology Evangelist

Technical Product Manager

A Technical Product Manager guides the development of technical products, including those using artificial intelligence. This course is valuable because it provides hands-on experience in building various AI applications without writing code. This knowledge helps a product manager to understand what is possible and feasible when developing AI-driven products. This course's material on chatbot development, web integration, and plugin integration also allows the product manager to better understand technical requirements. The course also showcases the deployment process.

See salaries and explore the career path for Technical Product Manager

AI Solutions Architect

An AI Solutions Architect designs and oversees the implementation of AI solutions. This course may be useful because it provides a broad overview of building various AI applications without needing to code, allowing the AI Solutions Architect to understand what is possible to produce using no-code methods. This knowledge of no-code approaches to AI helps an architect assess which methods and tools are most appropriate for a particular project. The course’s teaching on visual AI application development also helps the architect understand the overall architecture of an AI system.

See salaries and explore the career path for AI Solutions Architect

Innovation Manager

An Innovation Manager leads the effort to implement new technologies and strategies within an organization. This course provides a foundation in practical AI application development, which may help an Innovation Manager discover new approaches and applications of AI. The no-code approach taught in the course means that an Innovation Manager can use this knowledge to quickly prototype new AI solutions. The course’s practical, hands-on projects allow an Innovation Manager to test and validate ideas within the organization. The manager will also find the material on chatbot and web integration useful.

See salaries and explore the career path for Innovation Manager

Data Analyst

A Data Analyst interprets and analyzes data, and this course teaches an analyst how to integrate AI into their workflow, particularly when it comes to data interaction. The methods taught in this course, such as creating chatbots that respond to data queries, may be useful for a data analyst to create more accessible and understandable outputs. This course teaches a method to interact with databases using AI. The hands-on projects, which focus on building practical applications, can help a data analyst understand how AI can be used to work with data.

See salaries and explore the career path for Data Analyst

Automation Specialist

An Automation Specialist focuses on streamlining processes using technology, and this course may provide valuable skills for incorporating AI into automation workflows. The course's focus on building no-code AI applications is highly relevant, as it enables an Automation Specialist to set up and deploy AI tools for automation purposes with minimal coding effort. The course may be particularly relevant when the automation requires intelligent chatbots or the ability to interact with various data sources like PDFs or websites. The course also emphasizes practical, hands-on projects, which is useful in this career.

See salaries and explore the career path for Automation Specialist

Digital Transformation Consultant

A Digital Transformation Consultant advises organizations on adopting new technologies, and this course may help give a consultant the necessary knowledge about AI to make such recommendations. The course's teaching of how to build no-code AI applications using a visual interface can demonstrate to clients the types of AI tools that are feasible for them to implement. This course’s coverage of integrating AI into websites and chatbots is particularly useful for a consultant advising on digital transformation. The course also teaches how to deploy applications, which could also be helpful.

See salaries and explore the career path for Digital Transformation Consultant

Machine Learning Engineer

A Machine Learning Engineer is responsible for developing and deploying machine learning models, and this course may be helpful because it provides a practical understanding of how AI applications are built without code. Though this role does involve coding, this course can provide an understanding of how non-coders can interact with AI models, which may help the machine learning engineer design and develop tools that are more widely accessible. The course teaches the full process of deployment, which is helpful to a Machine Learning Engineer. The course provides hands-on building of chatbots using AI.

See salaries and explore the career path for Machine Learning Engineer

Business Intelligence Analyst

A Business Intelligence Analyst analyzes business data to provide insights, and this course teaches the analyst how to integrate AI tools into their workflow, helping them create new techniques for extracting information. The methods taught in this course, including creating chatbots for querying data, will help the analyst explore new ways for users to interact with business information. The course’s focus on hands-on projects helps the analyst understand how AI can be utilized in real-world scenarios. This course touches on data analysis using AI tools.

See salaries and explore the career path for Business Intelligence Analyst

UX Designer

A UX Designer creates user-friendly interfaces for digital products, and this course may be helpful because it provides insight into how AI features can be integrated into various applications. This course's focus on building chatbots and integrating them into websites can inform a UX Designer. The designer will understand the kinds of AI applications that are possible and can plan for user interactions. The course provides experience handling the deployment of a web application, which may be of use to a UX designer.

See salaries and explore the career path for UX Designer

Technical Writer

A Technical Writer creates documentation for technical products, and this course may be valuable in order to understand how AI products are created and deployed. The curriculum, with its focus on hands-on projects in building AI applications without code, gives the technical writer a practical understanding of the end-to-end process. This insight could help the technical writer produce more useful and relevant documentation. In particular, understanding how chatbots, website integration, and plugins work will give the technical writer better context.

See salaries and explore the career path for Technical Writer

Computational Linguist

A Computational Linguist develops and refines computer systems to process and understand human language. This course may be useful for a computational linguist because it provides a practical, hands-on understanding of how AI models can be used to build conversational chatbots and develop other language-based applications. The course's focus on chatbot development, integration with websites, and use of plugins, gives this practitioner the context to see how language models can be used. This course is of use to see how the practical applications of AI models can be built

See salaries and explore the career path for Computational Linguist

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in ChatGPT - Building AI Applications Visually (no-code).

Putting Knowledge to Work

Save

Provides a comprehensive guide to using LangChain for building AI applications. It covers various aspects of LangChain, including prompt engineering, chains, and agents. It useful reference tool for understanding the underlying principles of LangChain and how to use it effectively. This book adds more depth to the existing course.

Putting Knowledge to Work

Paperback

Check price

Putting Knowledge to Work

Kindle Edition

Check price

RAG-Driven Generative AI

Save

Provides a practical guide to building AI applications using generative models. It covers various techniques and tools relevant to the course, offering a deeper understanding of the underlying principles. While not strictly required, it serves as a valuable resource for expanding your knowledge and exploring advanced applications. This book is commonly used by industry professionals.

RAG-Driven Generative AI: Build custom retrieval...

Kindle Edition

ChatGPT - Building AI Applications Visually (no-code)

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Visual ai application building with chatgpt

Activities

Career center

Reading list

Share

Similar courses