What you'll learn
- Understand the basics of demystifying data science using the AI-based platform Virtualitics
- How to visualise and interact with data in 3D using Virtualitics’ AI platform
- Identify variables, anomalies and relationships in data, and extracting key insights with ease
- Understand how 3D and VR data visualisations can enhance engagement and understanding of data
- How to solve the right problem and leverage data using scenario planning and trusted AI deployment in real-world implementation.
Course description
This course will empower you to learn how to demystify data science with VR using AI-based platform Virtualitics! Students will discover how to visualise the data in front of them in 3D, and interact with it. Virtualitics’ AI platform enables rapid transformation of complex data into powerful multi-dimensional graph visualisations, and prediction of future outcomes with clear, explainable no-code AI modelling.
With their Shared Virtual Office feature, there’s a possibility to turn VR systems into teleconferencing rooms where students can discuss insights from data while having it life-sized in front of them.
Course outline
Module I: Introduction to Virtualitics’ Intelligent Data Exploration
We discover and understand how 3D visualisations can offer new ways to view, manipulate and interact with complex data. Powerful 3D visuals illuminate the relationships, facts, and previously unseen insights the AI discovered
Module II: Meaningful observations of significant findings, using plain language
We continue our journey with identifying different variables, anomalies and relationships, extracting key insights with ease. Students have the opportunity to discover how to use machine learning models to quickly find and visualise relationships among hundreds of variables to understand the ones that drive your problem at hand.
Module III: Enhancing engagement and understanding with 3D and VR data visualisations
We discover and understand how to provide insights into and how best to approach problems. If this is new territory for students, it will empower them to make better decisions based on reliable data insights.
Module IV: Experience Data in 3D
We explore and discuss why the gap between the analytics teams and the business has prevented AI success. In this way, we learn how to improve collaboration by bringing business and data science teams together in a shared virtual space.
Module V: Solving the right problem and leveraging the data
We introduce the concept of why visualisations are critical to getting the business and the analytics teams aligned and to build trust. We’ll learn how to validate predictions with flexible scenario planning that lets users fine-tune inputs and action plans.
Module VI: Deploying trusted AI
We learn how the practical application of AI can be made easy for everyday people to trust and leverage. We go through use cases where teams collaborate across different geographic locations, interacting and analysing data together—which is much more effective than exchanging PDFs or screen sharing!
Module VII: Real-world implementation
We learn about the creation of predictive models that are incredibly accurate or accurate enough to make timely decisions. We’ll learn to identify critical business insights that generate real value seamlessly.
