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January 2027 batch · Live online · Weekends

Advanced Urban Analytics

Turn city data into decisions, in eight weekends.

Pick a city question in week one. Work it through data, maps, workflows and machine learning, and present it as a capstone to an industry panel.

Apply for the January batch Watch the 60-sec overview
Starts
9 Jan 2027
Duration
8 weekends
Live
16 sessions
Hours
32 live
Programme overview

See how the eight weekends work.

A short film on what you learn, how the four phases run and what you leave with.

Who it is for

Built-environment people who want to work with data.

Architects & urban designers Planners & policy teams Geographers & GIS analysts Civil & environmental engineers Researchers & students Civic-tech & consulting professionals
Curriculum

Four phases. One city question.

Two live sessions every weekend. Each phase ends with something you have built on your own city. Open a phase to see every session.

Alumni work: urban heat patterns in Google Earth EngineAlumni work · Urban heat patterns · Earth Engine
LEARNWEEKS 1–2 · 9–17 JAN · 8 LIVE HRS

See the city as data

  • 01Urban Analytics 101
  • 02Dashboard Building
  • 03The Software Stack
  • 04Masterclass: data-driven planning

You'll produceA city question, a published starter dashboard, a working QGIS / Colab / Earth Engine toolkit and a reference set of planning cases.

See all 4 sessions
S01Urban Analytics 101Sat 9 Jan · Parshav Sheth & Yohan Wadia · discussion-ledLeave with a city question of your own and a capstone site.
S02Dashboard BuildingSun 10 Jan · Vandana DiwediA published starter dashboard for your city. Looker Studio
S03The Software StackSat 16 Jan · Parshav Sheth & Yohan WadiaA reproducible notebook and an NDVI / LST time series of your city. QGISGoogle ColabGeoPandasEarth Engine
S04MasterclassSun 17 Jan · Guest expert · discussion-ledData-driven planning cases from the world and India.
Alumni work: building-level map of Manhattan and BrooklynAlumni work · Building-level mapping, New York
APPLYWEEKS 3–4 · 23–31 JAN · 8 LIVE HRS

Work the data

  • 05Creating, cleaning & structuring data
  • 06Analysis & cartographic communication
  • 07Open data, networks & web scraping
  • 08AI agents inside your GIS

You'll produceA dataset you built, raster and thematic maps, a walking-accessibility map and an AI-agent workflow in QGIS.

See all 4 sessions
S05Creating, Cleaning & Structuring Urban DataSat 23 Jan · Kriti NirmalA clean, attributed neighbourhood dataset you can query with SQL. QGIS
S06Analysis & Cartographic CommunicationSun 24 Jan · Kriti NirmalTerrain analysis plus thematic and hotspot maps of your city. QGIS
S07Open Data, Networks & Web ScrapingSat 30 Jan · Kriti NirmalAn isochrone map and a geocoded dataset from open and scraped sources. QuickOSMValhallaCrawler
S08AI-AugmentationSun 31 Jan · Kriti NirmalCharts from your map data, a policy layer and a first AI-agent QGIS workflow. ChatGPTClaudeGeoGPTRAWGraphs
Alumni work: population density in 3D, BarcelonaAlumni work · Population density in 3D, Barcelona
BUILDWEEKS 5–6 · 6–14 FEB · 8 LIVE HRS

Turn analysis into workflows

  • 09Reading the landscape from satellites
  • 10Connecting the evidence
  • 11Designing the workflow
  • 12From model to decision

You'll produceA wetland change map across four cities, a validated evidence brief, a documented workflow and a deployed prototype tool.

See all 4 sessions
S09Reading the LandscapeSat 6 Feb · Sutirtha Das GuptaA multi-temporal wetland change map compared across four cities. QGISGoogle Colab
S10Connecting the EvidenceSun 7 Feb · Sutirtha Das GuptaAn evidence brief with one validated claim on ecological loss. QGISGoogle Colab
S11Designing the WorkflowSat 13 Feb · Avi SharmaA documented workflow and a landslide susceptibility map. QGISGoogle Colab
S12From Model to DecisionSun 14 Feb · Avi SharmaA catchment and flood-risk map and a first deployed tool. QGIS2WebLeafletStreamlit
Alumni work: Ontario Line displacement audit dashboardAlumni work · Ontario Line displacement audit · AI dashboard
SCALEWEEKS 7–8 · 20–28 FEB · 8 LIVE HRS

Model, interpret, take it into the world

  • 13Machine learning for cities
  • 14Prediction & computer vision
  • 15Explainability & storytelling
  • 16Industry roundtable & capstone

You'll produceTypology and land-use maps, a tested predictive model, and a capstone presented to an industry panel.

See all 4 sessions
S13Learning from Urban DataSat 20 Feb · Pushkar RunwalA ward typology map and a classified land-use map with an accuracy report. Pythonscikit-learnEarth Engine
S14Predictive & Deep Learning ModelsSun 21 Feb · Pushkar RunwalA trained predictive model and a building-footprint extraction. PythonSegment Anything
S15Interpretation, Explainability & StorytellingSat 27 Feb · Pushkar RunwalAn explainability note and a capstone storyboard. SHAPLooker StudioFigma
S16Industry Roundtable & Capstone ShowcaseSun 28 Feb · Industry panelA presented capstone, panel feedback and your @LABS certificate.
SAT 7–9 PM ISTSUN 11 AM–1 PM ISTEVERY SESSION RECORDEDALL TOOLS FREE FOR LEARNERS
Benefits and outcomes

What this opens up for you.

Key benefits

  • Learn the tools practitioners use, on a city you choose
  • Live, small-cohort weekends with expert tutors
  • Mentor feedback at every phase
  • Recordings of every session to revisit

Expected outcomes

  • A portfolio of 16 outputs and one capstone
  • Clean datasets, maps, dashboards and models
  • Workflows and tools others can repeat
  • An @LABS certificate

Career growth

  • Move into GIS, urban data and AI roles
  • Bring evidence to design and planning work
  • Stronger applications for master's and PhD
  • An industry network and Global Connect
Your faculty

Practitioners, not just lecturers.

Each phase is taught by people who do this work, plus a guest masterclass and an industry roundtable.

Parshav Sheth
Parshav Sheth
Big data analyst · Academician
S1, S3
Yohan Wadia
Yohan Wadia
Geospatial analyst · AI specialist
S1, S3
Vandana Diwedi
Vandana Diwedi
Planner, Municipal Affairs & Housing, Toronto
S2
Kriti Nirmal
Kriti Nirmal
Urban policy analyst · formerly NIUA
S5–S8
Sutirtha Das Gupta
Sutirtha Das Gupta
Urban data technologist
S9, S10
Avi Sharma
Avi Sharma
Urban data technologist
S11, S12
Pushkar Runwal
Pushkar Runwal
Technology consultant
S13–S15
In their words

What our alumni say.

From a first-year planner to a practitioner with 35 years in the field.

Vandana Diwedi
Vandana DiwediUrban Planner · Office of the Minister of Housing, Toronto6+ YEARS EXPERIENCE

I feel I've learnt more through this program than I did during my two-year master's. It's been great applying these learnings to my projects and contributing to @LABS research projects. I was also honoured to be invited to deliver lectures on urban dashboards.

Dr. B. K. Patel
Dr. B. K. PatelUrban Planner · Design Point Programming Pvt. Ltd, Surat35+ YEARS EXPERIENCE

The program empowered me to integrate data-driven techniques into my ongoing projects, including the Greater Patna Expansion and spatial planning in Prayagraj. I believe every planning professional should develop the ability to use data in decision making.

Aradhana Paralikar
Aradhana ParalikarArchitect Planner · Academician and Professor, D. Y. Patil, Navi Mumbai10+ YEARS EXPERIENCE

The experience gave me a new perspective on how cities can be studied through data. The course helped me connect theory with practice, not just for my own research, but also for how I approach teaching and help students understand the future of urbanism.

Harish Murugan
Harish MuruganUrban Planner · Sponge Collaborative · Master's, CEPT University1 YEAR EXPERIENCE

What stood out was how AI could simplify workflows and take analysis beyond what I initially thought possible. The course strengthened my technical skills and supported my transition into a role at Sponge Collaborative.

Apply for the January batch

Tell us a little about yourself and we'll get back to you on WhatsApp.

Your details
Q1Which best describes you?
Q2How many years of professional experience do you have?
Q3Which university or college are you an alumnus of, or currently studying at?
Q4Name of your current organisation, and your association with it
Q5Please rate your current proficiency in data-driven technologies, big data and GIS as applied to urban planning.
Q6What do you want to get out of this course?Select all that apply.
Q7Live sessions are held every Saturday (2 hours) and Sunday (2 hours). Are you ready to invest this time in upskilling?
Q8The fee for this programme is ₹67,500. Are you ready to take the next step in your career?
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