Our hands-on, robust training programmes embed AI and GenAI in traditional technical subjects, empowering our graduates with the necessary skills to realise a marked competitive edge in a world defined by thinking machines.
ENROL NOWOur flagship suite of computational training programmes works to equip tomorrow’s professionals with the skills to transform data into impact. Soon, you’ll be able to dive into Computational Commercial Ecosystem Activation, where you’ll learn to architect and optimize AI‑driven market strategies, or Data Science for Healthcare Optimisation, which will teach you to harness patient and population data for smarter care delivery.
To kick off this series, we’re proud to present our inaugural 5‑day Computational Spatial Informatics course - your hands‑on gateway to mapping, analysing, AI integration, and visualising spatial data to solve real‑world challenges.
Computational Spatial informatics blends geography, data science, and visualisation to reveal patterns that drive decisions in urban planning, public health, disaster response and more. Over five days, you’ll learn foundational mapping concepts, master industry‑standard tools (QGIS, Google Earth, OpenStreetMap, Mapillary), analyse spatial patterns, and complete end‑to‑end projects - from density maps to photorealistic 3D city models.
ENROL NOWYou only need to bring a laptop and a smartphone and the knowledge to operate it. Prior technical knowledge in QGIS, Mapillary, Google Earth, Sentinel EOS or Python, is not required.
Training will be held on-premise, at Acme AI's production HQ located at Level 4, House 385, Road 6, Avenue 3, Mirpur DOHS, Dhaka 1216, Bangladesh. Session duration per day vary between 3-4 hours. Maximum size of each batch is 15 members to ensure one-to-one mentoring and to cultivate rich engagement.
Climate, water governance, and informatics expert spearheading research, advocacy and governance to integrate resilient climate policy across South Asia.
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Toriqul leads Acme AI's spatial informatics and aerial enterprise systems working with a wide swath of local and global entities to drive next generation and AI-powered information systems. He will be the primary coordinator for the course.
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Sadhli founded Acme AI and is a creative technologist who works to monetise frontier technology skills and knowledge. He will engage with students on developing capstone projects.
LinkedInThe course is structured in a moduled curricula enabling learning to progressively unlock skills in spatial informatics and understanding of tools such as Mapillary, QGIS, and a set of complex plug-in sets. The training is held for 05 calendar days. Descriptions of each module and subsequent learning outcomes are as followed:
You’ll begin by immersing yourself in core map literacy—learning why spatial informatics matters, exploring a variety of map types (optical, multispectral, LIDAR, heatmaps, and more), and mastering the fundamentals of cartography: legends, scales, grids and compass usage. By day’s end, you’ll apply these concepts in a guided slum‑mapping exercise and test your new skills with a short quiz.
Master core map literacy by identifying diverse map types and applying cartographic fundamentals—legends, scales, grids and compass use.
Building on those foundations, you’ll dive into QGIS—navigating its interface, modules and data layers—while also collecting and importing geospatial data from OpenAerialMap, Google Maps/Earth and OpenStreetMap. You’ll learn to distinguish field‑survey versus existing dataset methods, identify common spatial patterns (clustered, uniform, radial, etc.) and solidify your understanding through hands‑on classification and a follow‑up quiz.
Navigate the QGIS interface to import, visualize and analyze geospatial data, distinguishing field‑survey from existing datasets and recognizing spatial patterns.
Shifting to street‑level insight, you’ll harness Mapillary to capture, geotag and organize imagery for real‑world mapping workflows. A guest expert will share best practices for urban data collection, after which you’ll integrate those insights into your project and present preliminary findings—culminating in a targeted quiz to reinforce your new toolkit.
Capture, geotag and organize street‑level imagery with Mapillary, integrating expert insights into a real‑world mapping workflow.
You’ll then explore satellite imagery—comparing high‑resolution versus low‑resolution data—before crafting thematic population density maps and dynamic heatmaps in QGIS. Pushing further, you’ll use 3D ray‑tracing techniques to render spatial movement and volume, troubleshooting common visualization challenges along the way and validating your progress with a dedicated quiz.
Compare high‑ versus low‑resolution satellite imagery and create thematic population density maps, dynamic heatmaps and 3D renders in QGIS.
On the final day, you’ll synthesize every skill learned by building a fully textured, photorealistic 3D city model complete with dynamic lighting and shadows. You’ll optimize performance, iterate based on peer and instructor feedback, and deliver a concise project presentation that highlights your end‑to‑end spatial analysis expertise—and leaves you ready to tackle real‑world mapping challenges.
Build, optimize and present a fully textured, photorealistic 3D city model—demonstrating your end‑to‑end spatial analysis expertise.
In order to be certified, enrollees must complete all assignments and quizzes in satisfaction - ending with development of a cohesive spatial informatic portfolio for external demonstration.
Assignments include developing siloed spatial system components and outputs - both individually and as a group.
Quizzes are MCQs organised in-class surrounding course curriculum, in addition to national and global industry lore in spatial informatics.
The most important takeaway from this course is the development of a spatial informatics portfolio document for securing earning avenues.
Formal tuition for the course and scholarship details are as followed:
The tuition fee covers 5-days training, 3-4 hrs. each day, logistics and venue costs, tea-break and food. You will be invited to pay the course fee upon completing registration for the course.
Scholarships, if opted for in the registration form, are awarded based on merit of the candidate and quality of responses on the scholarship section in the enrolment/registration form.
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3D ray-traced density maps based on dataset.
Land Use and Land Cover temporal comparison.
Urban Building Segmentation using predictive algorithms.
Street mapping and nav-point visualisation.
We are working with partners to develop two new programmes:
Learn how to harness AI, market data, and systems thinking to design, activate, and scale commercial ecosystems. This course equips you with tools to model consumer behavior, optimise market flows, and build data-driven strategies for sustainable growth.
Discover how to apply data science to enhance healthcare delivery, patient outcomes, and system efficiency. This course covers predictive modeling, health data visualisation, and real-world use cases in diagnostics, disease prevention, and resource optimisation.
Due to high volume of application, we allocate seats at a first-come-first-serve basis. Please fill out the application form and make payments at your earliest convenience to be in que for enrolment in our training programmes.
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