As 2023 drew to a close, one of the most hotly discussed subjects was the advent of readily accessible large-language artificial intelligence models such as Chat GPT, Gemini, and Microsoft’s Copilot.

As someone who has worked in code for the past two decades, I began to test Chat GPT’s ability to produce code with the correct prompts, and realized very quickly that while the current model (GPT 3.5 at the time) had some difficulties, the potential was there for the next models to produce code well enough to greatly impact, if not replace, the role of professional coders in the spaces I have worked in for most of my career.

As luck would have it, the second most prestigious Aritificial Intelligence post-graduate course was right here in Austin at the University of Texas McCombs Business School. I invested in the course and embarked on a career changing and intensely competitive challenge to give myself a competitive edge in the tech industry.

The class consisted in 6 modules, each building on the previous module, starting with basic Python programming, moving towards various machine learning models, exploring computer vision, and ending in building a Llama LLM.

For each project we were required to produce a Python notebook containing all of our code, and given the option to submit our work as part of a presentation (as if we were sharing the project with an executive in our company.)

Rather than use the bare-bones powerpoint template the course offered, I chose to leverage my design background and experience to format the information in ways that I knew would make sense to my current boss, making the outputs valuable not only as coursework, but as a contribution to SHI to demonstrate methodologies we could use to leverage AI in our own marketing process.