Prompt Engineering in Python, with GPT, and the OpenAI API
What you'll learn
- Mitigate Hallucination in LLMs
- Use emotional stimuli to get better answers from LLMs
- Become aware of prompt hacking and learn how to mitigate it
- Turn ChatGPT into a personalised coach
- How to get the best quality answers from LLMs, and how to iteratively improve your prompts
- Use the OpenAI Python API to query Large Language Models (LLMs)
- Have multi-turn chats with LLMs via the OpenAI Python API
- Extract numeric values from text data
- Test your prompts to make sure that they are robust and reliable
- Option 1: The first chapter of this course uses ChatGPT to teach you Python. So you don't need to know Python if you are comfortable with the idea of learning it from ChatGPT.
- Option 2: You may wish to try a dedicated Python course first. However, I would try the ChatGPT option first. Strictly speaking, you should be comfortable using Python in Jupyter notebooks. But you can always enrol in an additional Python course on Udemy.
This course is different to all of the other Prompt Engineering courses. In this course, you will learn the LLM prompting skills that you will need highly paid, prompt engineering role.
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 6 - 18 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.
The opportunity presented during this transitional time
A growing number of employers are starting up LLM projects. It's still only the early-ish adopters, there will be many more GenAI projects launching in the next 6 - 18 months. But people with prompt engineering skills are few and far between. So you have a rare opportunity to progress your career and boost your income.
If you are new to the tech industry, then these rare transitional times are the opportunity to break in. Because you will be uniquely qualified.
If you are already working as a software engineer, data analyst, data scientist, or data engineer, then this is the opportunity to significantly increase your income. Because employers will pay more for prompt engineering skills while there is a skills shortage.
How is it different to just using ChatGPT?
The bulk of the work in this course uses the OpenAI Python API. This is the same setup as real LLM use cases in the workplace. The course uses OpenAI, but the skills that you learn will be applicable to any LLM.
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 any OpenAI LLM. 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 how to stop LLMs from hallucinating.
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.
At the end of the course, you will be well on your journey to becoming a professional prompt engineer.
What else is unique about this course?
There are lots of opportunities to learn on the internet. But when you dig deeper, you will often notice that the presenter lacks commercial experience. The internet is full of training material compiled by recent graduates, undergrad students, sales and marketing teams, and professors who have spent their whole career in academia. The best education however, comes from someone who has real industry experience.
You need an experienced professional in your corner. You need someone to show you alternative perspectives that you have never seen before. You need someone to teach you how to “get it”.
Who is the instructor and what are his credentials?
Hi! My name is Slava Razbash, I have worked in AI and Machine Learning roles since 2011. My current role is mostly prompt engineering. I am one of the few instructors, if not the only instructor, who currently gets paid to prompt in his day job.
You might want to check out my LinkedIn profile. You might want to see where I’ve worked. (You're welcome to connect with me as well.) My past projects have had names like “Forecasting”, “Predictive Analytics”, “Prescriptive Analytics”, and of course, “Data Science”. My current job title is "Data Scientist", but my actual work is prompting LLMs.
Large Language Models are the next step in the evolution of the data and analytics industry. LLMs are already offering career opportunities to people with the right skill set. And the number of opportunities will grow as more companies start adopting LLM use cases.
I broke into the data science career track during another transitional time. I learnt the data science skill set when it was not being taught in universities. And I got my first few jobs by being the only suitably qualified applicant. It was a rare transitional time. But now we are in another rare transitional time. Now you have the opportunity to break into the prompt engineering career track.
I’m sharing my experience and knowledge with you - to help you become a highly paid prompt engineer.
Is this course for me?
In the realm of career decisions, you hold the reins to your own destiny. The choices that you make today have the potential to shape your future for many years. In terms of learning prompt engineering skills at the professional level, I see four distinct choices.
First Choice: Do nothing. Watch the AI boom pass by. If you choose the “do nothing” option, then you will miss out on the career boost from the AI boom. I estimate that the AI boom has the potential to boost your career by five years.
Second Choice: Completely switch industries away from anything to do with AI. Maybe you always wanted to become a pilot?
Third Choice: Learn Prompt Engineering elsewhere. From instructors who have much less (if any) commercial experience. It will take longer. The courses and books will not be tailored to commercial use cases. You will spend lots of time writing prompts about counting apples and other trivial applications. You will have to figure out how to transfer your new generic knowledge to the corporate setting. You also won’t learn my secret techniques.
Fourth Choice: Take this course, and give yourself a career boost. Because this is the fastest path to LLM mastery.
You’re not confined to a single path. The choice is in your hands!
Who this course is for:
- People who wish to pursue a career as a professional Prompt Engineer
- People analyse data in a corporate role
- People who wish to pursue a career in data analytics, data science, or any other field that analyses data
Slava has worked in data science roles since 2011. His resume includes Commonwealth Bank of Australia (Australia’s largest bank), Sportsbet (Flutter Entertainment), Tabcorp (multinational gambling business), Coles (one of Australia’s two largest supermarket chains) and AGL (one of Australia’s largest energy companies).
He’s solved a lot of data science and machine learning engineering problems. He’s also mastered a lot of new technologies along the way. On Udemy, we will follow Slava’s step-by-step approach to mastering another new technology, LLMs.