Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The Data Science for Smart Cities training is a 16-week course and requires the effort of six to nine hours every week. Purdue University has designed a programme that falls under the engineering category. Prof Satish Ukkusuri and Eunhan Ka will teach the intermediate level course. Language of the training and video transcripts are in English.
The focus of the Data Science for Smart Cities online programme is how to utilise scientific tools and techniques to analyse, infer, and predict large-scale data. Data present in city networks and collected from various sources such as social media, GPS vehicular data, mobile phones, social network, etc. will be used. The Data Science for Smart Cities syllabus will introduce basic data science methods for the analysis of these datasets. The Data Science for Smart Cities training will deal with these methods as well as applying those using Python for smart city issues.
Candidates can enrol for the Data Science for Smart Cities certification without paying any fee. However, the ones interested in acquiring a verified certificate can do so by purchasing it. Additionally, the Data Science for Smart Cities certificate will be signed by the instructor and have the university logo printed, making it a valuable addition to resumes or CVs.
The Highlights
- Intermediate-level
- 16 weeks to complete
- 6-9 hours of study every week
- Instructor-led course
- Free enrolment
- Engineering category
- Lectures in English
- Video lectures with transcript
- Designed by Purdue University
- Instructed by Satish Ukkusuri
- Instructed by Eunhan Ka
- Verified certification
Programme Offerings
- free enrollment
- project assessments
- Virtual exam
- Online Course
- Intermediate-level
- 16 weeks course
- Engineering category
- Instructed In English
- Video lectures with transcript
- Verified certificate
Courses and Certificate Fees
| Fees Informations | Certificate Availability | Certificate Providing Authority |
|---|---|---|
| INR 186972 | yes | Purdue University, West Lafayette |
Data Science for Smart Cities fee structure
Course | Total fee |
Data Science for Smart Cities(Audit Only) | Free |
Data Science for Smart Cities Certification(Verified Track) | Rs. 186,972 |
Eligibility Criteria
Candidates who wish to participate in the Data Science for Smart Cities online certification need to have an undergraduate-level education in Calculus and a basic understanding of statistical analysis.
What you will learn
With the Data Science for Smart Cities online intermediate-level course, candidates will perform well in the following domains:
- Basic concepts of optimisation, problem formulation, algorithms, types of datasets, data and measurement, data pre-processing, and identifying a task
- Optimisation, data mining, data pre-processing using Python
- Regression models, analysis, and application to smart cities
- Applications and approaches of association rule mining to urban systems
- Classification problems, Naïve Bayes classifier, logistic regression, and Bayesian network classifier
- Decision tree algorithms and practical issues
- Support vector machines, evaluation of classifier performance, and ensemble classifiers
- Data clustering algorithms, similarity/dissimilarity measures, types of algorithms, and hierarchical and partitional clustering
- Neural networks, ANN and neuron model, land use prediction with ANN
- Deep learning concerning smart cities
Who it is for
Any of the candidates are welcome to join the Data Science for Smart Cities online course except the residents from Cuba, Iran, and the Crimea region of Ukraine.
Admission Details
Step 1. To enrol for the Data Science for Smart Cities intermediate-level course, visit the official website link edX: https://www.edx.org/..
Step 2. Go to the menu bar and select the ‘sign-in’ option or ‘Register’ option.
Step 3. Google, Apple, Microsoft, and Facebook accounts may be used to create an account or candidates can fill in the required information such as the name, email, username, password, and country of residence, to create one.
Step 4. After getting that done, enter the course title in the search bar and locate the course
Step 5. Tap on the ‘Enroll’ option to enrol for free or choose to pay a fee for a verified certificate.
Application Details
To enrol for the Data Science for Smart Cities intermediate-level training, candidates do not have to fill in any application forms. Simply create an account and join the course.
The Syllabus
Unit 1: Introduction to Data Mining
Unit 1: Introduction to Data Mining
Unit 1: Introduction to Data Mining
Unit 2: Data Mining Tasks
Unit 2: Data Mining Tasks
Unit 2: Data Mining Tasks
Unit 2: Data Mining Tasks
Unit 2: Data Mining Tasks
Unit 3: Advanced Data Mining Techniques
Unit 3: Advanced Data Mining Techniques
Unit 3: Advanced Data Mining Techniques
Unit 3: Advanced Data Mining Techniques
Instructors
Purdue University, West Lafayette Frequently Asked Questions (FAQ's)
Yes.
Yes. Satish Ukkusuri is a professor at Purdue University, and Eunhan Ka is a Ph.D. student at the same university as well.
Yes. Candidates can add the certificate to their resumes or CVs and also directly attach it to their LinkedIn profiles.
Yes. Candidates can share this course via their Facebook, Email, Twitter, or LinkedIn accounts.