Who should attend

AI for Text Analysis is designed for professionals from all backgrounds who work with large quantities of language data and need to draw insights and understanding from their data. The course content focuses on practical knowledge and know-how, helping you to quickly translate theoretical understanding into technical skills applicable in the real world. We have carefully layered the course to suit learners with different levels of experience, including those who have no prior programming knowledge nor experience working with AI models .

What you will learn

Our formal learning objectives are as follows:

• Understand how to utilise Large Language Models by leveraging their strengths and avoiding their weaknesses.
• Design a workflow that incorporates a Large Language Model to perform text analysis.
• Apply your knowledge about Large Language Models to real challenges, and to do so efficiently and at scale.
• Critically evaluate the performance of your model to ensure the validity of your work.
• Communicate about your work with Large Language Models in a fair, transparent, ethical and rigorous manner.

Program structure

Our course consists of the following topics:

• What Large Language Models (LLMs) are and how they operate.
• Ethical considerations when using LLMs for text analysis.
• How to select the right model for your text analysis task.
• Prompt engineering for better communication with an LLM.
• Controlling an LLM with code to process large quantities of data.
• Using an LLM to perform higher-order thinking such as Thematic Analysis.
• Measuring the performance of an LLM on your data.
• Presenting your work with LLMs to a wider audience.

We use short videos to explain concepts and build a theoretical foundation for each topic. These are usually followed by quizzes to test your understanding, and tasks that allow you to apply your theoretical understanding to solve a real challenge. Additional resources will be provided throughout the course for those who would like a deeper dive into the relevant topics. There are no formal assessments—you are in charge of your own learning journey.

Titus Tang

Titus Tang, Ph.D., is the Lead AI Engineer on the Monash University Data Matters team. His work focuses around the development and implementation of real world AI systems. He also has an interest in teaching and education, having being a lecturer / instructor with Monash University, Nvidia, and other institutions.

Do I need a prior understanding of AI before joining this course?

No. This is an introductory course. We will explain how AI works from a practical point of view.

Do I need to know how to write computer code?

No. We will be interacting with an AI model mostly via a regular chat interface. There is a topic or two that shows you how to interact with an AI model using code. It is not compulsory to code along.

Are there any compulsory examinations or assignments I need to complete and pass?

No. There are various tasks and quizzes scattered throughout the course that you are encouraged to complete. These are not graded and there is no minimum mark you need to complete the course.

Do I need to follow the learning schedule provided?

No. All content is available to you right from the start. You are in total control of your own learning journey. The learning schedule is provided to you as a guide – we do not recommend anyone rushing through the learning process.

Are there any prerequisites for this course?

No – This course does not require any prerequisite knowledge. However, to get the most out of the content and activities, participants should have reading and language proficiency in English. All course content is delivered in English.

What payment methods are accepted?

The platform supports multiple payment methods via Credit Card and Invoice. You have the option to pay individually or request an invoice to register multiple participants.

Will I receive a certificate or digital badge after the course?

Upon completion of your course, you will be issued with a formal certificate of completion.

How will this course benefit my career or professional development?

Outside of the specific use case of text analysis, this course teaches you how to interact effectively with modern AI (Large Language Models). This skill is valuable in an increasingly AI-integrated workplace and transferable across multiple professions and disciplines.

Are there any technical requirements that I need to be aware of?

You will need access to a computer and internet connection to complete this course. You will need access to a large language model should you wish to follow along with the exercises available throughout the course. Many large language models can be accessed for free online (e.g., ChatGPT). We will show you how to access them in the course.