Mastering ChatGPT: A Comprehensive Guide to Natural Language Generation | Daniel Berkal | Skillshare

Playback Speed

  • 0.5x
  • 1x (Normal)
  • 1.25x
  • 1.5x
  • 2x

Mastering ChatGPT: A Comprehensive Guide to Natural Language Generation

teacher avatar Daniel Berkal, Consumer Research

Watch this class and thousands more

Get unlimited access to every class
Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Watch this class and thousands more

Get unlimited access to every class
Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Lessons in This Class

    • 1.



    • 2.



    • 3.



    • 4.



    • 5.



    • 6.



    • 7.



    • 8.



  • --
  • Beginner level
  • Intermediate level
  • Advanced level
  • All levels

Community Generated

The level is determined by a majority opinion of students who have reviewed this class. The teacher's recommendation is shown until at least 5 student responses are collected.





About This Class

Take your language generation skills to the next level with this comprehensive guide to using the ChatGPT model. Learn how to fine-tune and train the model for specific tasks, and how to use advanced features to improve performance. This class is packed with actionable tips and real-world examples to help you become a pro at generating human-like text.

What You Will Learn:

-How to access and use the ChatGPT model

-Proper data formatting for optimal results

-Fine-tuning and training the model for specific tasks

-Using advanced features to improve performance

-Common use cases for ChatGPT such as language translation, text summarization, and text completion

-Best practices for using ChatGPT and avoiding common mistakes

Why You Should Take This Class:

This class is perfect for anyone who wants to take their language generation skills to the next level. Whether you're a developer, a writer, or a marketer, the skills you'll learn in this class will be useful to you. You'll learn how to use the ChatGPT model effectively, fine-tune and train it for specific tasks, and use advanced features to improve performance. 

Who This Class is For:

This class is for anyone who is interested in learning about natural language generation and how to use the ChatGPT model. No prior knowledge or experience is required.


To take this class, you will need a computer with internet access. You will also need access to the ChatGPT model, which can be obtained through the OpenAI API or by using an open-source implementation of the model. Any necessary resources such as datasets and templates will be provided as part of the class.

Meet Your Teacher

Teacher Profile Image

Daniel Berkal

Consumer Research


Hello, I'm Daniel.  

I'm SVP and a partner at The Palmerston Group, a global qualitative research firm.  I've personally conducted hundreds of energetic interviews of various sizes, ethnographies, mystery shops and ideation sessions among consumers and professionals in North America, Central America, Europe & Asia.

I've had a stellar career working on some of the most innovative brands in business and have been best known for completely immersing myself in consumer environments in a creative way.  With projects featured in Fast Company and Forbes, I've been called "Hands down, the most unique, thought-provoking and game-changing qualitative researcher in the business. Period."  &nb... See full profile

Level: All Levels

Class Ratings

Expectations Met?
  • 0%
  • Yes
  • 0%
  • Somewhat
  • 0%
  • Not really
  • 0%

Why Join Skillshare?

Take award-winning Skillshare Original Classes

Each class has short lessons, hands-on projects

Your membership supports Skillshare teachers

Learn From Anywhere

Take classes on the go with the Skillshare app. Stream or download to watch on the plane, the subway, or wherever you learn best.


1. INTRO + WELCOME: Everybody has been talking about chat GPT. What does this mean? What does it do and how can it help you? This is a six part class about chat GPT. How to effectively use it, how to get it to help you in your daily routine. And we'll explore some best practices. This class talks about everything from inputting and formatting data to how to fine tune and train chat GPT to learn what you're looking for. We'll talk about a couple of advanced features. There's also going to be a really interesting class project where you can try the skills you learn in this class. On chat to PT, will look at some use cases. And we'll talk about best practices. Whether you're a novice at AEI or really experienced in the field, this class should help you. This is a quick class intended for all levels. I'm looking forward to having you as a part of it. 2. INTRODUCTION TO CHATGPT: In this lesson, we'll cover the basics of chat GPT, what it is, and how it works. We'll also discuss its capabilities and how to access and use the model. What is chat GPT. Gpt-3 is a large language model developed by a company called Open AI. It's a variant of the GPT model and specifically designed for natural language generation tasks. One of this GPT mean CPT stands for generative pre-training transformer. I know that sounds very complicated, but that's what the chat GPT-2 is all about. Chat is the ability to talk with a generative pre-training transformer model. Charge. If it is a software that's been trained on a wide range of Internet text. And it's capable of generating texts that's pretty human-like. You can ask questions and they will answer you. You can phrase things in really human terms and write them down and you'll get answers back that are pretty good. Okay, So how does the chat GPT work? It's quite complicated, but it uses something called a neural network architecture known as the transformer. This architecture allows the model to understand the context of the input text and generate appropriate responses to each question. This Models pre-trained on a massive data set of internet text. It allows it to understand a wide range of topics and language patterns. What are some of the capabilities of TBT? This software can be used for a wide variety of natural language generation tasks like language translation, text summarization, texts completion, content creation. It can also be fine tune for specific tasks like question answering, text classification, and dialogue generation. The power of this software is madness. So how do you access it? To access or use chat to beauty? It's really easy. You can access it through Open AI API, which allows you to send requests to the model and receive, generate texts and return. In order to use that model, you have to sign up for an API key on OpenAI website. There's also open source implementations of the model available on GitHub, and those can be finally tuned and use locally. Once you have access to that model, you can input a prompt and receive regenerative response. The prompt can be any texts at all, but it's best to provide some context to help them model generate a more appropriate response. But the easiest way to access chat GBT is by going to You have to sign up. You can sign up with a Google account. Then you can start asking questions to the software. You can play around with it. The raw power of this free tool is absolutely amazing. In the next lesson, we'll dive deeper into how to input and format data for the model. 3. INPUTTING AND FORMATING DATA: This lesson is called inputting and formatting data. In this lesson, we're going to discuss the different ways to input data into chat, to beauty and the proper formatting for different types of tasks. We're going to cover topics like context, prompt, and temperature. One of the most interesting things about chat UP T is the way that you input data. You inputted a thing exact same way you speak. You can just write questions in and it will give you answers back in relatively human-like form. Data can be inputted into this model and a variety of ways. Use Open AI's API, use open-source implementation, the model, or you can go to the website. But the most common way to input data is by providing a prompt. And a prompt is the text that the model uses degenerated response. The prompt can be any text at all. But it's best to provide some context to help them model generate a more appropriate response. Additionally, you can provide a context, which is a string of texts that allows you to provide additional information to the model. This context allows the model to understand the context, the prompt, and generate a more appropriate response. It's really important to format your information properly. For your input, you want to make sure you're being as clear as possible. The clearer you are, the better the model will be generated in response to that meets the criteria. So proper former dean is really important for ensuring that the model generates response. It's relevant to the prompt. It's important to use proper grammar and spelling when I'm putting this data. The model is trained on clean and well formatted text. For certain tasks like texts completion, It's important to format the prompt as specific way. E.g. you want to provide a specific number of words, there'll be completed. You can say, generate a ten word lists of synonyms for raccoon. I find it very difficult to find synonyms for RecA. And then there's temperature. Temperature is the most interesting part of this because temperature is a parameter that controls the randomness of the model's output. A higher temperature generates more diverse and creative responses, but a lower temperature generates more conservative and predictable responses. So you can play around with this quite a bit. You can experiment with different temperatures to try to help you find a sweet spot that best suits the task you're trying to do. By understanding the various ways to input data and understanding temperature parameter. You can fine-tune chat to PT and then the model to generate more accurate and relevant responses to your specific tasks. In the next lesson, we'll cover how to fine tune and train chat to PT on specific tasks and datasets. 4. FINE TUNING AND TRAINING: Okay, so let's talk about the benefits of fine tuning. Fine tuning, fine tunes, the process of training and retrain model on a new task or data set. Fine-tune it allows you to take advantage of the models. Pre-trained knowledge will also adapting it to your specific task. It leads to improved performance on your tasks. The model already learned many of the language patterns and common phrases that are relevant to your task. So how do you do it? The process of fine-tuning, fine-tune chat, too pretty neat to have a labeled set of data for input and output pairs that are relevant to your task. And the labeled data set will be used to train the model on your specific tasks. So once the fine tuning is complete, you can use the model to generate output from new input. There's a lot of guessing to this. You try things out and see if they work. It's important to have a large and diverse set of data for training. Also, you don't just want to throw in ideas and numbers. You want to preprocess the data to ensure that it's clean and well formatted so that when you input into chat GBT, It's able to understand it pretty clearly. Experimentation is key. When fine-tuning, it's important to experiment with different hyperparameters, like the learning rate or batch size, number of training steps. It's also good to use GPU to speed up the process of training by understanding and benefits and processes of fine-tuning, as well as following best practices for training, you become able to really improve the performance of charge CPT on your specific tasks. The next lesson we'll cover some of the advanced features of chat to beauty that can be used to improve performance. 5. ADVANCED FEATURES: Let's talk about some of the advanced features of chat to beauty. In this lesson, we're going to cover some of the advanced features of chats you could do that could be used to improve performance. We'll also discuss how to use these features to improve the performance of your model. Number one, controlling the length of output. By default, chat GPT generates texts, that's a variable length. But you can control this. You can control the length of gender texts by specifying the maximum number of tokens to be generated. It can be done through the OpenAI API or by using an open source implementation of the model. Controlling the length of output can be useful for tasks that are things like text summarization. You can say things like make a one paragraph long summarization of this piece of data. Number two. Generating multiple responses. By default, church, if you teach, generates only one response for each prompt. But you can actually change that around. You can generate multiple responses by specifying the number of responses to be generated. You can say, give me a five-point list, build a civics lesson class, generated multiple responses can be actually very useful for tasks like dialogue generation, where multiple responses are needed for a single prompt. Number three, you can use conditional inputs. So conditional inputs allow you to provide additional information to model, to control the output. E.g. you can provide on label or category to the model that will control the topic of the output. This feature becomes useful for things like text classification, where the output needs to be in a specific topic. So when having chatted me to write a document, you can specify what the classification that document's going to be odd number for using beam search. Beam search is this algorithm that generates multiple output sequences, each with a probability. And the algorithm generates multiple outputs and keeps the best one a coordinate specific criteria. Beam search also helps improve the quality of the output. By understanding these four advanced features, you're able to improve the performance of Chad GPT on specific tasks. In the next lesson, we're going to explore some of the most common use cases for chat to beauty, including language translation, text summarization, and texts completion will also discuss how to adapt chat GPT for other use cases. 6. USE CASES: This lesson is all about use cases for church GPT. What have people not use chat GPT for nowadays? Everything from recipe designed to song creation, to writing emails. In this lesson, we're going to explore some of the most common use cases for chat GPT, including things like language translation, text summarization texts completion will also discuss how to adapt using chat GPT for other use cases. And it's not an exhaustive list. This is an AI that you can use for an unimaginable number of things. Here are some language translation. Chat GPT can be used for language translation. You can find in the model on a data set of bilingual texts. You can fine tune this model to them to use to translate text from one language to another. This use case requires a large data set of bilingual texts and fine-tune the model for a specific pair of languages, but it works. And it's an interesting way of doing that type of thing. You can use chat to PT for text summarization. Text summarization is incredibly interested in. You can take a huge amount of texts like a large thing, cut and paste it, put it into chat to PT and say, summarize it in three paragraphs are in two lines, and it does pretty well. Chat GPT is used for text summarization by fine-tune the model on a data set of texts and summaries. You can also how to summarize the text in the voice of a character or a song. The fine-tuned model can then be used to generate a summary of the given text. And this use case also requires a large datas that have texted summaries. And you can fine tune that model for specific tasks of summarization. But it's a pretty incredible use. It's something that we haven't seen before, at least not on the commercial level. Chat to critique can be used for texts completion. You can give a little bit of a text. You can tell chart UP te, here's the beginning of a song, right? Another verse. Chat to be taking these for task completion by providing a partially completed texts as a prompt. And then the model generates remaining test. I don't really know how it does this, but it does. And this use case doesn't require a fine tuning right out of the box. It works. And you can try it and it gets it pretty well, learns the rhyme, the cadence, the alliteration. Chat GPT can also be used for other cases like answering questions test. And again, it does it quite well. And you can say answered this question in the voice of Shakespeare, or as if it was a Seinfeld episode. Those are the things people have commonly been using as ways of showing you how smart this software can be. Chat to be taken with adaptive also for dialogue generation, create a script and you can fine tune the model on a data set is relevant to the task. The larger and more diverse your data set is, and the more you find a model of better it gets at it. The number of use cases for chat UP T is, in my opinion limitless. You can adapt chat GPT for your specific task. And it gets better over time, which is kind of crazy. In the final lesson, we're going to talk about some of the best practices for using chat too busy right now, and some tips for avoiding common mistakes. We'll also discuss some limitations of the model and look at the future of AI. Text generation. 7. BEST PRACTICES: In this final lesson, we're going to provide some best practices for using chats you beauty and tips for avoiding common mistakes. We'll also discuss some limitations of the model and the future of AI powered text generation. Best practices always use proper grammar and spelling when inputting data. The smallest mistake can fool the system. The models trained on clean and well formatted text, I recommend use bare metal at different temperatures because then you can find that sweet spot that best suits your task. What you're using chat to P24. And you can play around with it a bit and you can also say to it, I mean, it doesn't have feelings. You can say, no, make this more funny. No, make this more serious. Know, make this more alliterative. Use a large and diverse data set when fine-tune the model for specific tasks. The more information you feed into it, the better it is. Feeding, use them in back out preprocess the data to ensure that it's clean and well formatted. You can use a GPU to speed up the process of training. There are lots of common mistakes. Here are some tips you can use to avoid making these mistakes. Number one, you want to be careful using chat GBT for anything that's sensitive or high-stakes. Because occasionally it generated things that are pretty offensive or harmful. Even though it's been trained to limit certain categories of thought and anything that's violent or racist or offensive. It's still couldn't get it wrong. You have to be aware of the model is not perfect and it may make mistakes or generate irrelevant or nonsensical text. I've been playing around and chat to take quite a bit and occasionally produces things that are complete mumbo jumbo gobbledygook. You also have to be aware that the model is not able to understand the meaning of words. It only associates them with a probability of appearing in certain contexts. So occasionally words will pop up out of nowhere and you're like, why is this here? It's a big limitation. Chat GBT as a language model, it's not able to understand the meanings of words. It only associates them with probability, um, and so it's not perfect. It may make mistakes and may generate things that are irrelevant and may repeat itself. So you have to be careful around certain topics. This is a very active field of research. There's so many new advancements and techniques being developed. Even chat to PT every couple of days it will give you a new version, a new model. The version that was most recent that I'm using words from my day or two ago. But that will change in three or four days in the future. We can expect to see much more sophisticated models with improved performance capabilities. But it's still going to be ai is still not going to understand meaning. It's just gonna be able to give you things that things will be there based on all the things that seen before. There's lots of ongoing research into the field of ethical AI. Making sure that the results that are communicated from an AI system are safe, pair, and reliable by understanding the capabilities and limitations of the model and by following best practices, you're able to really effectively use chat to PT for your specific tasks. Try it out. Sleigh with a whole bunch of variables. Try to figure out how you would respond. If you will respond to that question. It's software that is amazing and will only keep getting amazing. It's a limitless sandbox where you can play with things in a variety of ways. Some of which are quite useful, and it's only gonna get better. You have to keep in mind, this is a rapidly evolving field and new advancements and techniques are being developed all the time. 8. CLASS PROJECT: Okay, Now it's time to do an experiment. I would like you to use chat GPT to create an original song in the style of your favorite artist. And make the song about something that you wouldn't think the song would be about naturally. E.g. write a song about chocolate and unicorns in a style of Depeche Mode. Write the lyrics to the song about Disneyland in the style of Metallica. And then once that song is written, have chat GPT, add additional versus what chords to the song. Be as creative as possible. I'm really interested to see what you've come back with.