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Build Conversational AI using GPT-4

Name: Build Conversational AI using GPT-4
Rating: 4.2 (205 reviews)

Utilize Generative AI capabilities to deliver a magical end-user experience

Created byNeena Sathi

Last updated 7/2023

English

What you'll learn

Dive into Conversational AI by understanding the technologies and components that make up a ChatGPT-based solution.
Hands-on experience prototyping a ChatGPT-based conversational experience
A functional Conversational AI engine prototype demonstrating your chatbot creation skills.
Sample Conversation AI training data covering key concepts: utterances, intents, entities, and dialog flow.
Customizable Python integration code to further develop your Conversational AI expertise.
With tailored course content, we're confident participants will gain insights and skills to excel in Conversational AI and ChatGPT

Course content

7 sections • 22 lectures • 3h 7m total length

Introduction9:05
In this lecture, we will provide brief introduction on the course, specifically course objectives, pre-requisites, audience and expected outcome
Course Outline6:46
In this lecture, we will provide brief outline of course contents
Quick Prototyping with ChatGPT10:02
In this lecture, we will provide a quick demo of ChatGPT
ChatGPT Demonstration objective
Instructors Bio4:59
This lecture provides brief bio on course instructors

Set up OpenAI account9:29
Set up development environment provides step-by-step instructions on how to set up Open Ai account, including secret key and set of APIs needed for building your first conversational ai solution using ChatGPT.
Test the environment9:29
This lecture provides step by step instructions on creating a sample test application for creating a custom recipe using ChatGPT and Dalle on newly created environment from last lecture.
Key Roles of ChatGPT

Conversational AI Concepts17:15
This lecture introduces basic concepts used in a Conversational AI solution
Difference between an intent and an utterance
Generative AI Concepts10:23
This lecture provides basic concepts, tools and technologies used in building generative AI based conversational AI solutions
Conversational AI Solution11:34
In the lecture we will combine predictive and generative capabilities to create a conversational AI solution. We will explore which components could benefit from generative AI and use that as guidance for our sandbox.

Describe Movie Recommendation Use Case8:54
In this very first lecture, we will provide overview on our movie recommendation use case
Design Movie Recommendation Use Case10:47
In this lecture, we'll be discussing the design solution for our movie recommendation project. We'll be exploring the solution components and discussing the important design considerations that need to be taken into account before we begin creating the actual system. So, let's dive in and learn about the key aspects of our solution design.
Movie Recommendation Use Case: Build 14:57
In this lecture, we will focus on building a conversational AI system using GPT-4, specifically within the context of a movie recommendation scenario. We will take you through the process from beginning to end, demonstrating how a user query is analyzed, processed by the backend system, and ultimately, how the results are presented back to the user. Throughout this discussion, we will provide insights into chatGPT prompts for intent detection, entity extraction and response generation.
Movie Recommendation Use Case: Build 29:49
In this lecture, we will cover the second half of our build where we will develop the GPT-4 based natural language front end.
ChatCompletion API

Disambiguation8:47
In this lecture, we will be delving into the topic of disambiguation, which is an advanced topic in conversational AI. Disambiguation can involve simple mechanisms as seen in current commercial products, or it can be far more complex. In this lecture, we will explore what needs to be accomplished to clarify a query and why is it hard?
Additionally, we will provide an example to illustrate disambiguation.
Embedding9:55
In this lecture, we'll explore the concept of embedding and how it can be utilized to incorporate custom knowledge into our generative models. This custom knowledge allows the models to search for and build upon relevant information. By leveraging this embedded knowledge, our models can effectively provide answers to user questions, demonstrating the power of embedding in the context of generative models.
Embedding Example7:45
In this lecture, we will use example of Oscar awards from 2022 and 2023 to show how new information can be ingested and used.
Embedding
System Chemistry5:41
In this lecture, we will cover different user personas and how conversational AI system should be designed to reflect and adjust to user personas. We will also illustrate how to design different user personas using GPT-4 based model.
System Chemistry Example7:54
ChatGPT is a powerful engine. Where would you use this power in an enterprise setting? Enterprises have many opportunities to improve their end user experience in consumer facing as well as business facing situations. In this section, let’s list a couple of consumer and enterprise-facing conversations.

Summary4:45
In this lecture we will summarize course contents and will provide References to aid in future learning as it relates to ChatGPT and OpenAI
Use Case Examples5:48
In this lecture, we will list several consumer and enterprise-facing use cases that can utilize Ai powered engine like ChatGPT for building Conversational AI solutions
Bonus Lecture4:05
In the lecture, we will cover various course offerings from Applied AI Institute

Requirements

Familiarity with Conversational AI and ChatGPT is desired but not required
Knowledge of Python is required. Since we'll be using Python throughout the course for various tasks, it's essential that you're familiar with basic commands and Jupyter Notebooks.
Please note that to aid in your learning, we'll supply sample Python code during relevant course assignments, enabling you to concentrate on grasping and applying the concepts while avoiding coding complexities.

Description

Conversational AI is very popular today. We see numerous examples all throughout the day.

At home, you may have a home assistant, such as Alexa, or Google Home, or apps such as Google Assistant for setting up appointment.

If you are traveling for work, you may be talking to airline reservation chatbot for travel arrangement or hotel concierge services for hotel reservation.

Conversational AI is every where – home, work - you name it,

If you have an iPhone or iPad, you probably have Siri ready to work at your voice command.

During Covid-19 era, the emphasis on online customer engagement is rapidly increasing and more and more organizations are moving from static web pages to messaging interfaces. How do you start defining a Conversational AI solution that goes beyond simple messaging?

In 2023, we are seeing an unprecedented improvement in conversation quality with ChatGPT. Are you ready to use ChatGPT for your conversational AI solution?

Conversational AI has evolved significantly. Let me tell you all about it. It all started with Eliza in the 1960s, the very first conversation prototype. Fast forward a few years, and we saw structured conversations using bots and expert systems. Then came the big leap forward with natural language classification, Named Entity Recognition, and the rise of intelligent QA systems. The Replika experiment delved into the fascinating world of psychology, helping AI develop chemistry and engagement with users. Soon after, Conversational AI made its way into the commercial world, with big names like IBM Watson Assistant and Google Dialog Flow making waves. And finally, here we are today, with ChatGPT- a state-of-the-art language model that can engage in natural conversations on a wide range of topics.

On behalf of the Applied AI Institute, we are thrilled to welcome you to the "Build Conversational AI using GPT-4" course, a part of our Conversational and Generative AI series. This course is tailored to provide a comprehensive understanding of consultative engagement techniques to enhance end-user experiences by leveraging Conversational and Generative AI technologies, including the powerful ChatGPT.

The course is divided into multiple chapters

Chapter 1 - Introduction will provide overview of course including course objectives, intended outcomes, pre-requisite, course outline with an initial exposure to ChatGPT experience
Chapter 2 – What is conversation AI introduces you to key elements of a good conversational AI solution with an example
Chapter 3 – Set up development environment provides step-by-step instructions on how to set up Open Ai account, including secret key and set of APIs needed for building your first conversational ai solution using ChatGPT. It also created a sample test application for creating a custom recipe using ChatGPT and Dalle.
Chapter 4 – Generative AI Solution provides key concepts, tools and solutions used in building predictive and generative based conversational AI solutions.
Chapter 5 – Prototype Conversation Generative AI Solution provides step by step instructions on how to design and build a movie recommendation solution using ChatGPT and your proprietary data sets and recommendation engine
Chapter 6 introduces Advanced topics such as Disambiguation, Embedding, Chatbot System Chemistry. It also lists Conversational AI use cases which can be implemented using Generative AI technologies like ChatGPT.
Finally in Chapter 7 we summarize course contents and provide next steps as well as future learning in this area.

To successfully complete and receive certification for the course:

1. Complete all interactive quizzes after each section

2. Download sample training data and code, Complete all class assignment refine your training data as you go.

With tailored course content, we're confident that participants will gain insights and skills to excel in Conversational AI and ChatGPT

Who this course is for:

Business professionals: Those aiming to improve customer experiences with Conversational AI and explore ChatGPT opportunities
IT professionals: Individuals seeking to deepen their Conversational AI understanding and create user-friendly chatbots
Senior students in Business & IT: Learners aiming to expand their skills in Conversational AI and ChatGPT for career and academic growth
Consultants and service providers: Professionals offering Conversational AI solutions to clients while staying up-to-date with advancements

Build Conversational AI using GPT-4

What you'll learn

Explore related topics

Course content

Introduction4 lectures • 31min

What is Conversational AI1 lecture • 9min

Set-up Environment2 lectures • 19min

Conversational Generative AI Solution3 lectures • 39min

Prototype a use case using ChatGPT4 lectures • 34min

Advanced Concepts5 lectures • 40min

Summary3 lectures • 15min

Requirements

Description

Who this course is for: