Summary

The undefined website discusses the concept of Prompt Engineering, detailing how individuals can enhance their AI prompts to maximize earnings, with insights into the salary potential of Prompt Engineers and the use of a custom GPT tool called Prompt Perfector.

Abstract

The website content introduces the field of Prompt Engineering, which has gained prominence with the rise of Large Language Models (LLMs). It emphasizes the importance of crafting effective prompts to improve task automation and outlines the financial benefits of this skill, citing Upwork job postings that offer $20 to$ 40 per hour for Prompt Engineers. The article calculates a yearly salary of $62,400 based on a$ 30 per hour rate. To achieve such earnings, the content suggests following specific guidelines and using a custom-built GPT named Prompt Perfector. The tool is demonstrated through iterations of a prompt, starting from a basic request to a more complex and specific one, showcasing the evolution of prompt quality. The article concludes by encouraging readers to develop their skills in this emerging field, offering resources and access to special GPT tools for paid subscribers.

Opinions

The author believes that with the right background and technical ability, one can easily secure a job in the nascent field of Prompt Engineering.
The use of AI to enhance AI applications is seen as an iterative process, with the Prompt Perfector tool being a valuable asset in refining prompts.
The article suggests that the demand for skilled Prompt Engineers is high, as evidenced by the attractive salary range and the existence of job postings on platforms like Upwork.
The author promotes the idea that continuous improvement of prompts leads to better outcomes when applying AI with tools like sci-kit learn.
Access to specialized GPT tools and resources, such as those provided by the author's website, is presented as a key advantage for staying updated with AI advancements and securing employment opportunities.

Prompt Perfector GPT: Here is How You Can Make Your Prompt Perfect!

Maximize Your Earnings with Prompt Engineering: A Guide to Perfecting AI Prompts

Created with Abidin Dino AI, available for paid subscribers on substack, here

The “Prompt Engineering” term, comes to our lives, after LLM’s became so famous.

To automate our prompts, all of us have our methods, to automate our tasks. But by using special prompts, you can enhance this process. But let’ see how much Prompt Engineer earns.

Prompt Engineering

Image by Author — Here you can read more details from above.

This SS below is taken from Upwork. It shows that they offer between $20 and $40 per hour. Let’s consider $30 per hour as an example.

Upwork job description, here is the link.

Yearly Salary Calculation:

If we consider 52 weeks in a year and 40 working hours per week, the yearly salary would be:

$30 x 52 weeks x 40 hours = $62,400
This equates to an average of $5,000 per month, which is quite attractive.

Achieving This:

But how can you attain such earnings?

There are specific guidelines to follow if you want to build better prompts like this.

To do that, we built a custom GPT, name prompt perfecter. Let’s see it on the action.

Prompt Perfecter

I like using ChatGPT, to develop machine learning model, because the irony is using AI to apply AI. it is like all AI circle. So let’s craft a perfect prompt to do that. You can start with really simple like this prompt ;

Iteration 1

I want to apply ai with Python

As you can see, the model wants to to specify the things, which should be ultimate goal for you. Let’s improve our prompt.

Iterate 2

Applying more then one model, would be better to find the best so let’s add this.

I want to create a prompt to apply multiple ai model with python

Now, our prompt become to this ;

I am looking to integrate multiple AI models in a Python environment. 
Specifically, I want to understand how to effectively combine different 
types of AI models, such as neural networks, decision trees, and NLP models, 
in a single application. Can you provide guidance on the best practices 
for integrating these models, managing data flow between them, 
and optimizing their performance in a cohesive system?

Here, let’s improve our prompt by answering the questions below. This process will make your prompt better.

Iterate 3

I want to apply 4 different regression models. 
The complexity is intermediate. 
I want to apply this with sci-kit learn

Final Notes

As you can see how our prompt evolves, in different iteration. With a little bit of background, and technical ability, I think you can easily land a job like these, because these positions are too young yet.

So you don’t need to have a business experiences to land a job. To reach our special GPT’s like prompt perfecter, be noticed by Weekly AI news and reach next generation projects, consider being paid subscriber to us from here ; https://www.learnwithmeai.com/

Also, here is our website below, to see our Special GPT’s details; https://learnaiwithme.net/projects

Free GPT’s and Resources

Here are our free GPT’s and projects files you can take advantage.

Staying Updated With Daily AI News- https://chat.openai.com/g/g-35enG4y1L-ai-news
Staying Updated With ChatGPT News — https://chat.openai.com/g/g-VQMLTd4SE-gpt-news
To write articles ; https://chat.openai.com/g/g-GJdH0BxMk-phoneixink
To correct your articles vocabulary ; https://chat.openai.com/g/g-KddNRhCNe-vocabulary-correcter

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Here is my NumPy cheat sheet.

Here is the source code of the “How to be a Billionaire” data project.

Here is the source code of the “Classification Task with 6 Different Algorithms using Python” data project.

Here is the source code of the “Decision Tree in Energy Efficiency Analysis” data project.

Here is the source code of the “DataDrivenInvestor 2022 Articles Analysis” data project.

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