1/2 day course 
Supporting material 
Private This course is for marketing professionals who want to get more hands-on with the tech behind their use of GenAI. Using Python within Jupyter Notebooks to complete tasks, you’ll learn how to harness your code and take your tools to the next level.
During the session, we’ll introduce the Python language and Google Colaboratory, an open-source, collaborative and free web-based platform where you can run Python code and build various data services such as data ingestion, processing and visualizations.
We’ll then cover Python’s advanced capabilities, working in libraries like Pandas and NumPy, which are a key part of any toolset required by data analysts and scientists for complex modelling.
Towards the end of the session, we introduce Generative AI tools and resources. We present different ways to consume these services, focusing specifically on APIs. You’ll also be able to run code to interact with some of the most popular LLMs, (such as Gemini, Stable Diffusion, and Llama-2, among others) generating text, images and asking questions to these powerful models.
This Coding for AI course is available as a private training session that can be delivered via Virtual Classroom or at a location of your choice in Australia.
Course overview
Who should attend:
This course is ideal for:
- CMOs
- CTOs
- Creatives
- Marketing professionals
- Senior business leaders
- SMB owners who perform their own marketing
What you'll learn:
By the end of this course, you will be able to:
- Utilize basic Python language skills
- Create and use Jupyter Notebook services
- Interact with basic functions within the most popular Python libraries for data management
- Understand how LLMs and generative AI services work, and access them
- Interact with GenAI tools via API interfaces and services
Prerequisites
This lab is for participants who understand the fundamentals. If you don’t, you could get left behind. You might benefit from taking our GenAI for Marketers: Fundamentals course beforehand.
Course agenda
- The Python language
- Jupyter notebooks using Google Colaboratory
- Practice
- Data Science in Python
- Pandas, NumPy and other data libraries
- Practice
- Generative AI
- Large Language Models
- Gen APIs
- Using Jupyter Notebooks for GenAI
- Practice
Next Steps:
Consider taking the following courses to further your GenAI knowledge: