Course Dates: Sept 03, 2024 - Nov 10, 2024
Live Classes: All Classes will meet at 9.00 pm IST on Zoom
Research is the core of modern professional internal security issues today. Criminal justice is increasingly a data-driven function and CJ organizations process substantial data that reflect the social, political, economic factors impacting Indian society. Vast amount of criminal justice data is being collected throughout India. The nation-wide Crime and Criminal Tracking Network and Systems (CCTNS), as well sixty years of Crime in India data, new sources such as ‘Dial 100’ system across the country are providing big data to practitioners, researchers and policy makers. Combined with additional social, political and economic data and geographic information systems that provide spatial maps and allow incorporation of temporal phase, significant new heights can be scaled for effective crime control with data analytics and visualization.
The major objective of this course will be to train security personnel in analytic tools for study of crime and its control in India. Big Data analytics is among today’s fastest-growing professions and this course seeks to build skills in applying its techniques for internal security of the country. The course will incorporate subject matter from the disciplines of criminology, computing science, mathematics, geography, economics, psychology, management, philosophy, and ethics, with special emphasis upon gender, race and ethnic studies. Topics will cover Big Data Analytics comprising machine learning and AI applications as well as qualitative methods. Students will study ways of understanding and modeling of the complex social & political environment, and with these models better understand how to improve approaches to crime reduction and the use of analytics in criminal justice issue.
For more details, please visit the CCJR website by clicking here.
Student feedback for the course CJDA-1
Other Course evaluations [CJDA 2-5] may be seen from the Registration page
Module 1 Week 1
| Criminological Perspectives Readings Week 1: Path to Reform and Problem Oriented Policing | Sept 3-7
|
Class Meetings
| Tuesday: Introduction- Path to Reform Thursday: POP/ COP/ Situational Prevention Friday: Guest lecture Suhail Conquering Everest | |
Assignment | Application of POP in district policing | |
Module 2 Week 2
| Qualitative Analysis and Historiographic Readings Week 2: Notes from Police Station | Sept 9-14
|
Class Meetings
| Tuesday: Geography of Crime Thursday: Content Analysis and Survey Design Friday: Guest lecture | |
Assignment | Content Analysis of NPC Report 1 | |
Module 3 Week 3
| Model building through Regression Readings Week 3: Reading of Regression article | Sept 16-21
|
Class Meetings
| Tuesday: Introduction to Statistics Thursday: Regression Analysis Friday: Guest lecture | |
Assignment | Reading results of Regression - Winfree article using OLS | |
Module 4 Week 4
| Machine Learning & Agent Based Modeling Readings Week 4: ML Articles/ HART project | Sept 23-28
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Class Meetings
| Tuesday: Introduction to ML Thursday Precautions in applying ML Friday: Guest lecture | |
Assignment | Assignment on Machine Learning | |
Module 5 Week 5
| Network Analysis Readings Week 5: Network articles | |
Class Meetings
| Tuesday: Introduction to Networks Wednesday: Gephi application | |
Assignment | Assignment on Network Analysis | |
NO CLASS OCT 3-13 WEEK
| ||
Module 6 Week 6
| Data Visualization Readings Week 6: Tufte readings | Oct 14-19
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Class Meetings
| Tuesday: Introduction to Visualization Thursday Principles of Good and Bad colors Friday: Guest lecture | |
Assignment: | Assignment on Data Visualization |
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Module7 Week 7
| Conceptualization of research project.Students work on developing research question and design. | Oct 21-26 |
Class Meetings
| Tuesday: Developing Research Questions Thursday: Data collection and analysis Friday: Guest Lecture |
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Module 8 Week 8 | Project Presentations by students | Oct 28-Nov 8 |
- Theories of crime that suggest why people commit crime.
- Building Criminal Justice Data Sources.
- Criminal Justice Data Visualization.
- Model Building, Big data analytics, simulation, machine learning, network analysis,survey design in criminal justice issues, Data Security.
- Formulating crime control questions that can be tested using various methods.
- Using CJ data to test policy outcome.
- Structuring a draft publishable research article.
The course is designed for officers of Indian police, private security managers, senior officers of defense services, internal security policy analyst, CJ practitioners, and researchers. In particular, this course is designed for those seeking to enhance their skills and capabilities in crime prevention techniques. Graduate students of political science, sociology, criminology, computer science, mathematics, and management will also benefit from this course.
Educational Requirements:
The minimum educational requirement is a bachelor’s degree and experience of working with computers. In this course, you’ll learn quantitative and qualitative methods for data analysis through hands-on exercises and video instruction from IIT Kanpur faculty and guest faculty from other institutions around the globe.
Time Frame:
You can complete all course requirements in this course and earn your certificate in 10 weeks, spending 5-7 hours per week.
Evaluation:
Weekly Assignments/ Exercises/ Quizzes: | 90% |
Presentations: | 10% |
Certificates:
After completion of all the assignments and successful presentation, the students will be awarded a Certificate in Criminal Justice Data Analysis by IIT Kanpur.
Dr. Arvind Verma
(arvindcjus@cse.iitk.ac.in)
And Several Guest Instructors