This one is for learning Japanese.

This one is for learning how to make better YouTube videos.

And last but not least, this one is for learning personal finances.

These are the four topics, the four study plans that I'm currently following.

They're all custom designed to fit my specific goals.

Like for the Japanese one, I don't care about how to like speak Japanese or read Japanese.

I just want to learn how to understand Japanese so that I can watch anime without subtitles.

I know it's pretty specific.

But yeah, they're all custom made at my study level, my skill set, my preferred resources, and my preferred study schedule.

Before Chachipiti, each of these study plans would have taken me days, if not weeks, to get to this level.

But with Chachipiti, I was able to do each of them in less than 10 minutes.

After I got the prompt right though, the prompt itself did take me weeks to actually figure out.

But luckily for you, in this video, I'm going to just show you guys this prompt to make a really optimized custom study plan using Chachipiti.

That works for any subject.

Plus, I'm going to give you some bonus prompts and tips and tricks on how to use Chachipiti to make the actual studying process faster and also more fun.

All right, let's have that start running while I explain the prompt.

So for this example, I'm going to make a study plan for learning AI.

You can change that for any other topic that you want as well.

All right, so the prompt.

You are an expert learning tutor who is well versed in Scott Young's book, Ultra Learning.

So that is from this book over here.

I have tried a lot of different frameworks from a lot of different books and resources, and by far the best one for how to create a good study plan using Chachipiti.

This framework in this book works the best.

So I actually covered this book in detail.

You can check it out on this link over here.

So I'm not going to go into much of it now, but just trust me on this one.

OK, all right.

So moving on.

So right now I want to make a study plan for ultra learning AI based on the principle of meta learning and the why, what, how framework.

So that is the framework from the book.

Why is why I want to learn it.

What is what I will learn?

This is divided into concepts, facts and procedures.

How is how will I learn it?

This is based on techniques of benchmarking and emphasize, exclude.

Benchmarking means to find common ways people learn it by doing research.

Emphasize, exclude means for making modifications to align with the goal.

My why for learning AI is because I want to build simple web applications using LMS and other AI products.

The why is extremely important.

Make sure to think carefully about why it is that you want to learn this topic and tell ChachiBT.

The more specific you are, the better.

Like my Japanese one is specific for learning how to understand anime Japanese, so I don't have to read subtitles.

My personal finance one has specific goals about buying land and property.

And for making YouTube videos, I say specifically it's for making video essays to maximize for views.

I already know how to code in Python and know how to build a Python applications with Django.

So I understand the components of a web application and how they work, etc.

This is where you tell ChachiBT what you already know about that topic, so it's able to adjust its skill level for you.

So let's create a study plan using this framework.

Let's start with the what.

For the what in your study plan, we'll break it down into concepts, facts and procedures.

So it tells me the concepts that I need to learn, such as AI and machine learning basics, natural language processing, pre-trained models and APIs, web application architecture for AI apps and ethics and bias in AI.

And for facts, key libraries and frameworks, data formats, pre-trained model specs and performance metrics.

And for procedures, the actual steps I need to take.

So all of this is very specific to my goal and looks very reasonable.

By the way, the reason why I didn't give you like one massive prompt and I said to start with the what is that this way it offers you flexibility.

Like, for example, maybe I don't care about ethics and bias.

I should care about ethics and bias, but I could say something like, I don't care about ethics and bias.

Please remove that.

But yeah, so yeah, this is how you can kind of iterate on top of it so that you get the concepts, facts and the procedures that you want to have.

All right, let's actually add it back in.

OK, so let's now move on to the how of the framework.

All right, we asked ChachiBT to do benchmarking, which is to research common methods of learning.

So you and I are not the first people who want to learn how to use AI to build applications.

So instead of trying to come up with something from scratch, we can actually ask ChachiBT to research the collective knowledge of people who have come before us and what they figured out is the best way to learn.

And based on that, we're doing emphasis slash exclude.

So we're emphasizing things that are targeted towards my goals and excluding things that are not useful towards my goal.

So in this case, from doing that research, we know that people use beginner friendly courses such as Anjanine's course on Coursera or Fast.ai.

People use APIs and library documentation.

Project based learning is really important.

Online communities and GitHub and for ethics and bias, looking at case studies and ethical guidelines.

So we're emphasizing project based learning and API integration of web applications because we want to build a web app using LLMs and AI models through APIs.

We need to have AI fundamentals with a focus on large language models specifically and for bias, identification and mitigation.

What we're excluding is in-depth theoretical ML slash deep learning knowledge.

Since I said that I wanted to be applied, I just want to build these applications, not like build my own models and deeply understand them.

That's why we're excluding this.

And also we're excluding data set creation and fine tuning.

These are things that we might want to do later on.

But since I just want to build an application right now using the APIs, we can keep things simple and exclude that in this current study plan.

All right.

Now we want to combine together the why, when, how and come up with a comprehensive study plan that also has resources and timelines.

So I said combine these things together and make a week by week study plan with specific deliverables.

For these deliverables, I said make specific assignments and projects with rubrics and specs that you can grade and provide feedback for.

This is going to be really helpful so that it doesn't just tell you to like learn something very vague.

We wanted to give you specific assignments that have objectives.

And later on, I'll talk about this as one of the later prompts.

You also want ChatGBT to be able to provide you with feedback as you're completing the assignments and going through the study plan.

So we want to bake that in while we're making a study plan itself.

And we want corresponding relevant resources.

I said that I can study six hours a week with three hours on Monday and Wednesdays.

And I want resources that are primarily text or video courses because that's just how I learn best.

All right.

And here we go.

Week one, introduction to AI, APIs and LLMs.

The objective is to understand AI basics and how pre-trained models and APIs works.

Concepts are going to be AI and machine learning basics and natural language processing and LLMs.

The facts.

So it lists out what the facts are and what the procedure is going to be.

It has a deliverable.

So it says create a Python script that calls the OpenAI API to generate text based on the prompt.

It was very specific about what it is that I actually need to accomplish.

And this rubric is helpful because it gives you an understanding of what should be included in the deliverable.

And we have our little resources as well.

So week two is going to be integrating APIs into Django applications.

So week three is working with image recognition models, so not just LLMs.

And we have a deliverable to create a web app that accepts an image input of a plant and returns information about the species using a pre-trained image recognition API.

Very interesting.

I don't know why it's about a plant, but seems good.

Week four is your ethics and bias.

And week five is when we build our full stack AI application.

Very excited for that.

And week six is going to be for debugging, testing and refining.

Overall, it's going to be six weeks.

And by the end of it, it looks like we would have built a AI application just like how I want it to.

It tells you exactly what it is that you need to learn.

And it has a project-based deliverables that you can apply to skills that you learn.

And it even has a rubric so you know what are the components that make up that project.

And of course, the resources based upon what other people have used in the past and they found to be good.

Not to toot my own horn here, but I'm genuinely pretty proud of this prompting sequence to get to this point.

You have no idea how long it actually took me to get to this point.

So, yes, just let me have this one, OK?

But we're actually not done.

There is one more final step.

I hope this video has made you realize how useful ChatGPT is in terms of learning things.

But actually, that's just the beginning.

It's relevant to increasing your productivity across all aspects of your life.

HubSpot has a whole bundle of resources designed to help you understand and make the most out of ChatGPT.

It will make you super productive.

It's very well laid out and gives you lots of ideas on ways you can incorporate ChatGPT.

For example, using ChatGPT to consolidate research materials like different articles, tutorials and resources.

So you can directly ask questions instead of having to flip through all of them yourself or keeping you up to date with industry news and updates.

They also have this nice flowchart on when it's appropriate to use ChatGPT to solve a problem or streamline your workflow.

My favorite part is that it has over 100 prompts to start playing around with, which is great since, as you can see, prompting is extremely important to getting the most out of ChatGPT.

The best part is that it's completely free.

I highly recommend that you download it using this link over here, also linked in description.

Thank you so much, HubSpot, for providing free resources to help us leverage the power of AI.

And for sponsoring this portion of the video.

Now, back to the video.

Ideally, you want an expert, someone who already knows the content of your study plan, to look over your study plan and just sort of double check that things make sense.

You can do this if you actually know someone who already knows AI or knows Japanese or is really good at personal finances and they can look over your plan.

But assuming you don't know anybody, this final step is you're going to ask ChatGPT to now be an expert AI engineer that specializes in developing AI applications.

And we're asking this AI engineer to look at the study plan above as if it's for the first time and to provide feedback on what they think and also what they think should be changed.

So as an AI engineer, here are some strengths.

Project-based learning is good, balanced approach, API-centric, rubric for deliverables, ethics, and bias consideration.

So some suggestions for improvement.

Maybe you want to have more emphasis on debugging and error handling because building AI applications often involves dealing with unforeseen edge cases, especially when integrating multiple APIs.

And it gives you like specific changes, like increasing focus on error handling and then adding a mini project in week three where you intentionally introduce errors or unexpected inputs and learn to handle them.

This is actually very common practice when you're debugging an application.

So a very good point here.

Also introduce real world data earlier and more frequent iterations and refactoring.

So you can choose to incorporate some of this feedback or you can choose to ignore it.

So in this case, I'm going to choose to include some of this feedback.

Thank you.

These include suggestions one and two into the study plan.

And voila, there you have it.

We have created a custom study plan for learning how to build AI applications.

Don't worry if you didn't catch everything.

I'll leave a link in the description that has the prompt sequence in it.

So now that we have the study plan, the next step is that we actually have to study.

I also want to share with you guys some of the prompts and the little techniques that I use where I can get through the study plans so much faster and a lot more fun as well.

First, one of my favorite chat2BT study use cases is using chat2BT to create test questions.

A couple of months back, I had to take the knowledge section of my driver's exam, but I didn't really feel like reading the hundreds of pages of rules related to driving.

So instead, I just gave chat2BT those documents and told it to ask me questions.

If I don't know how to answer a question, I would just ask it to explain it to me.

And that was just a much more fun learning experience.

You can use this technique even if you're not actually studying for an exam.

But in this case, since I was studying for an exam, I also gave it samples of some of the exam questions from the test.

So this is even more effective because as I learned, I was also actually like practicing taking the test multiple times as well.

I'm happy to report that I did pass the exam and it took me two hours of studying.

I also like to use the Feynman technique with chat2BT.