X

Urban Informatics

By Prof. Debapratim Pandit   |   IIT Kharagpur
Learners enrolled: 1316   |  Exam registration: 272
ABOUT THE COURSE:

Urban Informatics is an interdisciplinary course that integrates data science, programming, machine learning, and IoT to address complex urban challenges. The course begins with foundational concepts in data types, database systems, and data access methodologies, followed by object-oriented programming in Python. It delves into advanced analytics through supervised, unsupervised, neural network, and reinforcement learning approaches. Core IoT principles are explored, including sensor data acquisition, Arduino-based prototyping, and basic firmware development. These components are synthesized through real-world urban applications and smart mobility platforms—emphasizing end-to-end system design involving data storage, processing, analytics, and visualization

INTENDED AUDIENCE: Bachelor in Architecture, Bachelor in Planning, Bachelor in Technology(Civil. Computer Science, Information Technology), Bachelor in Social Science, Master in (City/Urban Planning, Urban Engineering, Transportation Planning, Spatial Data Science, Social science, Technology)

PREREQUISITES: Basic knowledge in Computers and Urban Planning

INDUSTRY SUPPORT: All Architecture, Urban Planning, Infrastructure, IT/ITeS and Consultancy Services firms providing solutions for urban areas
Summary
Course Status : Ongoing
Course Type : Elective
Language for course content : English
Duration : 12 weeks
Category :
  • Architecture and Planning
  • Urban Infrastructure Planning and Management
Credit Points : 3
Level : Undergraduate/Postgraduate
Start Date : 19 Jan 2026
End Date : 10 Apr 2026
Enrollment Ends : 02 Feb 2026
Exam Registration Ends : 20 Feb 2026
Exam Date : 19 Apr 2026 IST
NCrF Level   : 4.5 — 8.0

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.


Page Visits



Course layout

Week 1:  Introduction to Urban Informatics Topics: Smart cities, urban systems, data-driven governance, digital infrastructure, Case studies, Open data portals

Week 2: Types of Urban Data and Databases Topics: Types of data and data format, Types of databases, Relational databases, Database normalization, NoSQL

Week 3: Data Access and Management Topics: SQL, APIs, web scraping, data cleaning, cloud storage

Week 4: Programming Fundamentals with Python Topics: Python syntax, control structures, functions, file I/O, object-oriented programming and examples

Week 5: Data Analysis and Visualization with Python Topics: Python data structures and data access, Introduction to Pandas, Matplotlib, dashboards, exploratory data analysis

Week 6: Introduction to Machine Learning Topics: Machine learning Basics, Foundational theories, Model building, Model training/testing, Model evaluation

Week 7: Supervised Learning for Urban Prediction Topics: Classification, regression, decision trees, support vector machines (SVM) etc. Case studies

Week 8: Unsupervised and Association Learning Topics: K-means, hierarchical clustering, PCA, dimensionality reduction, Apriori algorithm, Frequent pattern mining etc., Case studies

Week 9: Deep Learning and Neural Networks Topics: Neural architectures, activation functions, backpropagation, CNN, time series modeling (LSTM) etc., Case studies

Week 10: Internet of Things (IoT) Fundamentals Topics: IoT architecture, protocols (MQTT/HTTP), sensors, actuator, Microcontrollers, Firmware, cloud integration,Case studies

Week 11: Arduino and Arduino projects Topics: Arduino IDE, serial communication, firmware basics, Arduino projects for urban context

Week 12: Integrated Urban Systems and Data platforms
 Topics: Geospatial analysis and dashboards, real-time analytics, PostGIS, Tableau, urban simulation, Case studies Agent based simulation, Bus service optimization, Bicycle sharing systems, Opportunities, challenge and limitations, Summary Session

Books and references

An Introduction to relational database theory By Hugh Darwen,
Urban Informatics and Big Data By Michael Batty,
Smart cities : big data, civic hackers, and the quest for a new utopia By Townsend, Anthony M.
Python in a Nutshell: The definitive reference By Alex Martelli, Anna Ravenscroft & Steve Holden
Machine Learning By Tom Mitchell
Python for Data Analysis By Wes McKinney Machine Learning: A Probabilistic Perspective By Kevin P. Murphy,
Internet of Things: A Hands-On-Approach By Arshdeep Bahga and Vijay Madisetti

Instructor bio

Prof. Debapratim Pandit

IIT Kharagpur
Prof. Debapratim Pandit is serving as a Professor at the Department of Architecture and Regional Planning, Indian Institute of Technology Kharagpur. He has completed his PhD from the Department of Urban Engineering, University of Tokyo in the area of landuse transportation modeling and has more than 16 years of teaching and professional experience. Prof. Pandit teaches Advance Transportation Planning, Urban informatics and Urban utilities and Services for Post Graduate and Research students. Prof. Pandit’s research group City future lab (https://arp.iitkgp.ac.in/) is quite well known and he has completed guidance of 70 post graduate and 10 doctoral students. Prof. Pandit has published several books, book chapters and papers in top international journals and has undertaken a wide array of consultancy and research projects on urban landuse planning, simulation studies, transport infrastructure development and urban mobility plans. He has developed several products including hardware, firmware and software for bicycle sharing systems(www.pubbs.in) and software for urban bus transit planning and operations using artificial intelligence (www.pubbs.co.in) for the Government of India.


Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: April 19, 2026 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

Please note that assignments encompass all types (including quizzes, programming tasks, and essay submissions) available in the specific week.

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team
MHRD logo Swayam logo

DOWNLOAD APP

Goto google play store

FOLLOW US