This course is different to all of the other Prompt Engineering courses. In this course, you will learn then AI skills that you will need if you need if you are working as a software engineer, data scientist, data analyst, or as a real, highly paid, prompt engineer.

What is prompt engineering?

Prompt Engineering is the skill of finding the right prompt to get the right results from your LLM. With expert level prompt engineering skills, you can implement a commercially profitable LLM solution.

On the other hand. A prompt written by someone with average skills, might not lead to a working solution at all.

I predict that prompt engineering will become the most demanded skill in the analytics industry within 12 - 24 months. As companies start to take up LLM use cases,  you have an important choice to make. You can either learn these new skills today, and be well placed for the upcoming AI roles. Or you can sit on your hands while other people step into newly created AI roles.

How is it different to just using ChatGPT?

The bulk of this course teaches you to use the OpenAI Python API to query state of the art LLMs like GPT  3.5 and GPT 4.

Do I need to know Python to do this course?

No you don't. Because at the start of the course, you will learn to prompt ChatGPT to teach you Python.

So if you don't know Python, and you are comfortable with the idea of having "a machine teach you how to program a machine", then go ahead an enroll in this course.

What is covered?

After learning from our personalised ChatGPT coach, we will start querying GPT with the Python API. You will be able to use either GPT 3.5 Turbo or GPT 4. It's a matter of changing a single parameter.

You will learn how to get better answers from LLMs than your untrained competitors. You will also learn the famous "Chain-Of-Thought" prompting technique.

Next, you will learn how to have multi-turn conversations with GPT models in Python. The course will also introduce you to prompt hacking. You will see examples of prompt hacking. You will learn how to defend against prompt hacking. And you will see how OpenAI is patching the security holes in its models.

Next you will learn how to use the LLM to extract data from text. Then you will learn to properly test the results of your LLM data extraction. This workflow could be a component in a data pipeline.