It’s a hot new role that’s only going to grow in prominence: prompt engineer. Someone who can effectively prompt AI programs to output the right information. Whether that’s requiring ChatGPT to prolifically produce SEO-optimized content, or improving systems and processes with AI-driven data insights, entrepreneurs need this person by their side to maximize their output and keep their business in the game.
As AI advances, the requirements of a prompt engineer will change. AI models will become more self-sufficient in generating their own prompts, meaning less manual intervention is required. However, the array of tools available and their complexity will likely increase. Every business will have a chief AI officer, and teams will be transformed. Whatever happens, fundamentally understanding the systems and how they work will set you up well to advance with the times.
AI prompt engineer roles are offering salaries over $300k, including this one at Anthropic. Here are five free courses that can help you or a team member deepen their knowledge of AI and prompting.
How to learn prompt engineering
1. GPT Best Practices by Open AI
To date, the most popular and influential tool of the AI era is Open AI’s ChatGPT. The tool opens up opportunities for entrepreneurs to increase productivity and improve output. The sky is the limit with large language models (LLMs), but only if you know how to prompt them effectively.
This guide shares strategies and tactics for getting better results from GPTs. OpenAI, the guide creator, encourages experimentation to find the methods that work best for you. Within the guide there are six strategies for getting the best results from language models, as well as tips and tactics for effective prompting.
2. Introduction to Artificial Intelligence by Stanford University
If you joined the AI train in late 2023, it would be easy to think ChatGPT (or “Chad”) represented AI in its entirety. But it’s just a small part. Knowing how LLMs fit within the entire landscape of artificial intelligence will open your eyes to brand new use cases that could be relevant to your business. It will make you a better prompt engineer as well as better placed to hire one.
This beginner’s course provides a comprehensive introduction to a range of AI concepts beyond LLMs. It includes machine learning, neural networks, natural language processing, and robotics. To date, over 200,000 people have enrolled on this course, which takes around 2 months to complete with 10 hours of work per week.
3. Deep Learning Specialization by DeepLearningAI
Perhaps you want to dive deep into AI to one day take a role at a tech giant. Maybe you want to build your own tools, or maybe you just want to learn about the field so you can secure your place in the future. Any reason, commercial or otherwise, is sufficient to enroll and see what you can discover. Prompting is a key skill beyond LLMs, and this course will widen your knowledge.
Follow up your beginners’ course with one for intermediates. This course, created by DeepLearningAI’s Andrew Ng, Kian Katanforoosh and Younes Bensouda Mourri, covers neural networks, convolutional networks, recurrent networks, and generative models. Over 750,000 people have enrolled and you’ll be finished in 3 months of 10 hours per week.
4. Natural Language Processing with Deep Learning by Stanford University
Another course by Deep Learning, this time available for free on YouTube, delves into the foundations and applications of natural language processing (NLP) using deep learning techniques. NLP is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data.
Essentially, this course will explain how computer systems are able to understand and create human-like speech. The 23 course videos, split into lectures of around 90 minutes, have been viewed over 640,000 times and are delivered by various AI experts.
5. Practical Deep Learning for Coders by FastAI
This free course is for those who want to learn how to apply deep learning and machine learning to practical problems, designed for individuals with some coding experience. It focuses on practical aspects of deep learning and covers topics such as image classification, natural language processing, and collaborative filtering.
Here, you’re not just understanding and implementing prompts, you’re building logic within tools of your own. Within the course you’ll learn how to turn your models into web applications and deploy them. If you’ve powered through options 1-4 and you’re ready to get practical, this might be the course for you.
These courses offer a solid foundation and practical insights into AI and prompting, to equip you with the skills you need to implement AI in your business or role. Check the course descriptions and structure to find the ones that align best with your interests and learning goals.