Internet of things (IoT) has become a significant component of urban life, giving rise to “smart cities.” These smart cities aim to transform present-day urban conglomerates into citizen-friendly and environmentally sustainable living spaces. The digital infrastructure of smart cities generates a huge amount of data that could help us better understand operations and other significant aspects of city life.
Data Mining for Smart Cities
Give your career the gift of Coursera Plus with $160 off, billed annually. Save today.
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
62 hours to complete
3 weeks at 20 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Describe types of smart city-generated datasets, data mining techniques, and how to implement them using Python 3.
Explain how to read and preprocess data for data mining.
Apply data mining techniques to smart city-generated data and visualize and interpret the physical implications of the results.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
12 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 8 modules in this course
This module provides an overview of the course content and structure. In this module, you will learn about the different course elements. In this module, you will get acquainted with your instructor and get an opportunity to introduce yourself and interact with your peers.
What's included
2 videos1 reading1 discussion prompt
In this module, you will learn about data mining, why we need it, and the approach. The module also presents the basics of probability and statistics, which form the foundation for data mining. You will also gain insight into data preprocessing and data mining task identification.
What's included
12 videos4 readings2 assignments1 discussion prompt
In this module, you will learn about Python programming for data mining. The module also discusses important Python modules: NumPy , SciPy, and Matplotlib. You will learn to install Python using Anaconda and use the Jupyter notebook to write your code. The module also presents some examples demonstrating data preprocessing using Python.
What's included
6 videos4 readings2 assignments3 ungraded labs
In this module, you will learn about supervised learning (learning from examples). The module discusses two supervised learning tasks: regression and classification. You will also gain insights into several classification algorithms such as Bayesian classifiers, decision trees, support vector machines (SVM), and ensemble classifiers.
What's included
12 videos5 readings2 assignments1 discussion prompt9 ungraded labs
In this module, you will learn about unsupervised learning (learning from unlabelled data without any ground truth labels). The module also discusses frequent itemset mining. You will also gain an insight into several data clustering algorithms such as distribution-based, partitional, and hierarchical clustering.
What's included
11 videos5 readings2 assignments1 discussion prompt7 ungraded labs
In this module, you will learn about anomaly detection problems and algorithms. You will gain insight into anomaly detection techniques. You will learn to validate your results. When applying data mining to smart city data, you will also learn to avoid false discoveries using statistical significance testing and hypothesis testing.
What's included
5 videos2 readings2 assignments4 ungraded labs
In this module, you will learn about some advanced data mining algorithms such as artificial neural networks (ANN) and deep learning. You will develop an understanding of the applications of these algorithms. The module also analyzes hidden Markov models (HMMs) for modeling time series (sequential) data.
What's included
10 videos3 readings1 assignment1 discussion prompt4 ungraded labs
In this module, you are provided with your term-end project, instructions to complete the project, and the criteria for how your instructor will grade your submission.
What's included
1 video2 readings1 assignment1 ungraded lab1 plugin
Instructor
Offered by
Recommended if you're interested in Data Analysis
University of Illinois Urbana-Champaign
École Polytechnique Fédérale de Lausanne
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.