It’s a hot new role that’s only going to get bigger: that of a one-time engineer. Someone who can effectively nudge AI programs into producing the right information. Whether it’s demanding that ChatGPT prolifically produce SEO optimized contentor improve systems and processes with AI-powered 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 fast engineer will change. AI models will become more autonomous in generating their own prompts, which means less manual intervention will be required. However, the range of tools available and their complexity will likely increase. Each business will have a AI director, and the teams will be transformed. Whatever happens, fundamentally understanding the systems and how they work will allow you to move forward over time.
AI guest engineer roles offer salaries in excess of $300,000, including this one at Anthropic. Here are five free courses that can help you or a team member learn more about AI and incentivization.
How to learn engineering fast
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 production. The sky is the limit with large language models (LLMs), but only if you know how to incentivize them effectively.
This guide shares strategies and tactics for getting better results with GPTs. OpenAI, the creator of the guide, encourages experimentation to find the methods that work best for you. In the guide, there are six strategies for getting the best results from language models, along with tips and tactics for effective prompting.
2. Introduction to artificial intelligence by Stanford University
If you joined the AI train at the end of 2023, it would be easy to think ChatGPT (or “Chad”) represented AI in its entirety. But this is only a small part. Knowing how LLMs fit into the larger AI landscape will open your eyes to new use cases that may be relevant to your business. This will make you a better engineer faster and in a better position to hire one.
This beginners course provides a comprehensive introduction to a range of AI concepts beyond LLMs. This includes machine learning, neural networks, natural language processing, and robotics. To date, more than 200,000 people have registered for this course, which lasts approximately 2 months with 10 hours of work per week.
3. Deep Learning Specialization by DeepLearningAI
Maybe you want to dive deep into AI to one day play a role at a tech giant. Maybe you want build your own tools, or maybe you just want to learn more about the area so you can secure your place in the future. Any reason, business or otherwise, is enough to sign up and see what you can find out. Inspiration is a key skill beyond LLMs, and this course will expand your knowledge.
Follow your beginners course with an intermediate course. This course, created by Andrew Ng, Kian Katanforoosh, and Younes Bensouda Mourri of DeepLearningAI, covers neural networks, convolutional networks, recurrent networks, and generative models. Over 750,000 people have signed up and you’ll be done in 3 months of 10 hours per week.
4. Natural Language Processing with Deep Learning by Stanford University
Another Deep Learning course, this time available for free on YouTube, dives 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 data in natural language.
Essentially, this course will explain how computer systems are able to understand and create human-like speech. The 23 lesson videos, broken down into approximately 90-minute lectures, have been viewed over 640,000 times and are hosted by various AI experts.
5. Hands-on deep learning for coders by Fast AI
This free course is for those who want to learn how to apply deep learning and machine learning to practical problems, designed for people with some coding experience. It focuses on the practical aspects of deep learning and covers topics such as image classification, natural language processing, and collaborative filtering.
Here you don’t just understand and implement prompts, you build logic into your own tools. In the course, you will learn how to turn your models into web applications and deploy them. If you’ve gone through options 1-4 and are ready to get hands-on, this course may be for you.
These courses provide a solid foundation and practical information about AI and incentivization, 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 best match your interests and learning goals.