Class Details
Data Analysis with AI Course
Course summary
Take your data analysis skills to the next level with AI. Building on foundational analytics knowledge, this intensive one-day course equips business professionals with practical techniques for integrating AI tools into every stage of the data analysis workflow – from designing smarter data collection plans and automating cleaning tasks, to extracting sentiment from text, building audience-specific dashboards, and communicating findings with clarity and impact.
The course is tool-agnostic: whether you work with ChatGPT, Claude, Microsoft Copilot, or another platform, the techniques and thinking frameworks you develop here will transfer. You will also build a critical understanding of where AI falls short, including accuracy risks, data bias, and the role of human oversight, so you can use these tools with confidence and judgement.
Aims
You will develop a practical, hands-on understanding of how AI can accelerate and enhance every stage of the data analysis process. By the end of this course, you will be equipped to use AI tools confidently for data preparation, exploration, visualisation, and communication in your professional context, leaving you ready to work faster, think more critically, and present data insights that drive real decisions.
Learning outcomes
By the end of this course, you should be able to:
- apply AI-driven techniques for data collection and preparation across a range of tools and platforms
- perform data exploration and produce meaningful visualisations using AI-assisted methods
- use AI tools to automate and streamline data cleaning and transformation tasks
- design and evaluate dashboards with interactive, multi-layered visualisations suited to different audiences
- draft narratives and reports that communicate data insights clearly and persuasively to stakeholders
- evaluate the limitations of AI in data analysis, including accuracy, bias, and the role of human judgement.
Content
From analytics to AI: bridging the gap
- Recap of core analytics concepts and where AI fits in the modern data workflow
- The spectrum of AI in analytics: from assistance to automation
- Overview of today's AI landscape for data work: large language models and emerging tools (ChatGPT, Claude, Gemini, Copilot and others)
- AI accuracy, hallucinations, and data bias: what every analyst needs to know
- Key considerations: data privacy, blind spots, and the role of human oversight
AI-powered data collection and preparation
- A five-question framework for AI-assisted data collection planning
- AI-assisted data auditing: using AI to assess data quality and identify gaps across structural and content issues
- Prompt engineering for data wrangling
Smarter data cleaning and transformation
- Handling messy, inconsistent, and incomplete data at scale
- Documenting AI-assisted cleaning steps for reproducibility and audit purposes
AI-assisted data exploration and pattern recognition
- Using AI tools to surface trends, anomalies, and correlations in datasets
- Text analysis with AI: extracting sentiment and themes from unstructured data
- Testing scenarios safely using AI-generated synthetic data
- Forecasting and comparing datasets with AI
Visualisation and dashboards with AI
- Exploratory visualisation
- Planning a visual narrative
- Generating one-off visuals and writing insight-led titles and annotations with AI
- Using AI to critique dashboards and refine design choices
Automating insights and workflows
- Using AI to generate automated summaries and flag key changes in data
- Planning and designing automated reporting workflows: scheduling, triggers, and alerts
- Using AI projects to maintain consistent context for recurring reporting
- Introduction to AI agents: the future of automated analysis
- Human oversight in automated reporting: transparency, accountability, and when to intervene
Communicating data insights to stakeholders
- Framing AI-assisted insights for non-technical stakeholders
- Data storytelling with AI: applying the context-conflict-resolution framework to draft and edit executive summaries and data narratives
- Structuring reports and presentations for maximum impact
Prerequisites
Completion of the Business Analytics Course: Data-Driven Decision-Making is recommended prior to attending this course. Participants with equivalent experience working with data analysis tools such as Excel, Power BI, or SQL are also welcome. Participants should be comfortable interpreting data and have some familiarity with at least one data analysis tool.
Who this course is for
This course is designed for business professionals who already have a grounding in data analytics and are ready to integrate AI into their analysis workflow. It suits analysts, managers, and decision-makers who want to work faster, think more critically about data, and communicate insights with greater impact.
Delivery style
This is a hands-on, practice-led course. Participants work with a real dataset throughout the day, applying AI tools across four modules. Each module combines brief conceptual grounding with guided AI tasks and practical exercises, so participants leave with transferable habits they can apply the following day.
Delivery mode
- Face-to-face, presenter taught workshop using your own device
- Online workshop via the platform Zoom
Materials
Course materials are shared electronically using Dropbox.
What you need to do before the course
To participate in this course, you will need an account with at least one paid AI platform of your choice (such as ChatGPT, Claude, or Microsoft Copilot) and access to Microsoft Excel or another spreadsheet tool for working with the course dataset.
Face-to-face classes: Please bring your own laptop with all required accounts already set up.
Online classes: For the best experience, we recommend using a computer with a large monitor or dual screens/devices.
Sessions
Location
Face-to-face (Venue TBA, Sydney)
Other information
If your upcoming class is Face-to-face (Venue TBA, Sydney), the class is located at the Camperdown/Darlington campus but the exact classroom and building has not been assigned.
The exact location on campus is confirmed approximately five business days from a class start date and you will then receive a course preparation email with this information.
Meet the facilitators
John Le Mesurier
John brings a wealth of business, management, IT, consultancy and training experience to many of the professional development courses on offer at CCE. This experience has included senior corporate and general management roles in American, British and Chinese multinationals, as well as consultancies for several leading UK and Irish management firms. His consulting projects have covered advanced practice studies in leadership, sales & customer service processes, strategic sourcing, human resource models and organisational issues. These projects have been undertaken in North & South America, Europe and China. His international client list includes Procter & Gamble, Red Bull, Johnson & Johnson, SC Johnson, Eli Lilly, Roche, Mitsubishi, Vodafone/ Hutchison Telecoms, Danone, Heineken, BOC/ Linde, Boehringer Ingelheim, British Government and Qantas. John also works for an Australian consulting firm, Newfocus, conducting projects in the government and Not-For-Profit sectors. John has been involved in projects at PwC and Macquarie University.
John is currently undertaking a M. Phil/ PhD and holds a Master of Business Administration (with Distinction), Bachelor of Arts (with Distinction), majors in Psychology and Statistics, sub-majors in Accounting and Economics; Diplomas in Management, Change Management, Risk Management, Project Management; Digital Badge in Advanced Analytics, Graduate Certificate in Learning & Teaching, and Certificate IVs in Competitive Manufacturing (Lean) and Training and Assessment. John has been awarded the highest qualification by The Australian Research Society, namely Qualified Professional Researcher. John is an accredited Sydney Lifeline counsellor, where he also trained counsellors for more than 20 years.
John has lectured in Bachelor of Business at Torrens University, Master of Business Analytics at Kaplan Business School and Master of Community Development offered through Southern Cross University (SCBIT Sydney campus). John has been an Executive Coach at UNSW, where he has also been a guest lecturer in marketing and change management. He has taught 1st year statistics at UTS (Insearch) and Macquarie University (Navitas) and delivered IT training in corporate settings for 30 years.
