Augmented Reality (AR) in Data Visualization Training Course

Augmented Reality (AR) in Data Visualization Training Course

Introduction

Augmented Reality (AR) is rapidly transforming data visualization by overlaying interactive, real-time, and spatial data onto the physical world. By combining immersive analytics, 3D data modeling, computer vision, and human-computer interaction, AR enables users to explore complex datasets beyond traditional 2D dashboards. This paradigm enhances situational awareness, decision intelligence, and data storytelling across industries such as healthcare, manufacturing, finance, smart cities, and geospatial analytics.

Augmented Reality (AR) in Data Visualization Training Course provides a hands-on and conceptual foundation in AR-driven data visualization, focusing on immersive dashboards, spatial analytics, real-time data overlays, and extended reality (XR) ecosystems. Learners will gain practical experience using AR development frameworks, data pipelines, and visual analytics techniques to design scalable, user-centric AR visualization solutions aligned with Industry 4.0, AI-driven insights, and digital transformation strategies.

Course Duration

5 days

Course Objectives

1. Understand Augmented Reality fundamentals and visualization paradigms
2. Apply immersive analytics for complex data interpretation
3. Design 3D and spatial data visualizations
4. Integrate real-time data streaming into AR environments
5. Use AR SDKs and frameworks
6. Develop interactive AR dashboards
7. Implement human-centered visualization design principles
8. Combine AI, ML, and predictive analytics with AR
9. Visualize geospatial and IoT data in AR
10. Optimize performance, usability, and scalability
11. Analyze industry use cases and case studies
12. Address ethical, privacy, and security challenges
13. Prepare for future trends in XR and metaverse analytics

Target Audience

1. Data Scientists and Data Analysts
2. Business Intelligence Professionals
3. AR/VR Developers and XR Engineers
4. UI/UX and Visualization Designers
5. Industry 4.0 and Digital Transformation Leaders
6. Researchers and Academicians
7. Product Managers and Innovation Strategists
8. Smart City, Healthcare, and Industrial Analytics Professionals

Course Modules

Module 1: Foundations of AR and Data Visualization

• AR concepts, types, and architectures
• Evolution of data visualization techniques
• 2D vs 3D vs immersive visualization
• Visualization perception and cognition
• Case Study: AR dashboards for executive decision-making

Module 2: AR Technologies and Development Frameworks

• ARCore, ARKit, Unity, Unreal Engine
• Sensors, SLAM, and spatial mapping
• Device ecosystems
• AR content pipelines
• Case Study: Retail analytics using mobile AR

Module 3: Immersive Analytics and Interaction Design

• Gesture, gaze, and voice interactions
• Spatial UI/UX principles
• User experience evaluation in AR
• Accessibility and usability considerations
• Case Study: AR interaction models in healthcare diagnostics

Module 4: 3D and Spatial Data Visualization

• Volumetric and spatial data representation
• 3D charts, heatmaps, and networks
• Geospatial and location-based visualization
• Digital twins and spatial analytics
• Case Study: Smart city traffic visualization using AR

Module 5: Real-Time and Big Data Integration

• IoT and sensor data visualization
• Streaming data pipelines
• Cloud-based AR analytics
• Performance optimization for large datasets
• Case Study: Industrial IoT monitoring with AR overlays

Module 6: AI-Driven AR Visual Analytics

• Machine learning for insight generation
• Predictive and prescriptive analytics
• Computer vision integration
• Intelligent data filtering in AR
• Case Study: Predictive maintenance using AR + AI

Module 7: Industry Applications and Advanced Use Cases

• Healthcare and medical imaging
• Finance and risk visualization
• Manufacturing and supply chain analytics
• Education and training simulations
• Case Study: AR-based financial risk visualization

Module 8: Ethics, Security, and Future Trends

• Data privacy and ethical visualization
• Security challenges in AR systems
• AR governance and compliance
• Metaverse and XR analytics trends
• Case Study: Ethical challenges in AR-based surveillance

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.