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Descriptive Analysis on Accident Data for Autonomous Vehicle Safety Planning
This project is designed for learners to understand different strategies of Data management & visualization functions to enhance public safety.
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Difficulty: BeginnerNo prior knowledge or experience with data required.
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Duration: Approximately 3 hours
Case Overview
- Descriptive analysis is a unique way of using data to understand it in a better manner.
- Road accidents is a major issue faced by millions of people all over the world. This raises the need for an overall road safety system that can be implemented by automobile companies.
- To devise a better road safety system, companies need to understand the various factors influencing such incidents and then create a safer, well rounded and a smart driving system.
- Learn how EDA can be used to analyze major factors affecting vehicle collision along with visualizing the collateral damage involved.
What’s included
Flexible Scheduling
Start learning online immediately, at your own pace
Desktop Only
We recommend completing this project on a desktop
Skills You Will Learn
Associated Learning Tracks
- Global data shows that millions of people die because of road accidents. This accounts for an urgent need for a road safety system that can be devised by automobile companies to prevent such losses.
- Automated intelligent transportation is very important because it is smart, safe and more than capable of handling driving functions.
- It is also essential to analyze vehicle and collateral damage so that companies can determine major factors that influence them.
- Exploratory data analysis was performed to summarize the data and its main characteristics.
- Monthly and weekly vehicles collisions and collateral damages were also plotted graphically using data visualization techniques.
- A summary about injured and deceased people in road accidents was also provided for better understanding of accident susceptibilities.
- This analysis can help in preventing injuries, deaths and collateral damage caused due to road accidents.
- It can also benefit companies that are working on self-driving cars and technologies for AI-programmed vehicles to understand the on-road challenges.
- The analysis can also be used by government officials to devise a better security regime for the nation to avoid unnecessary accidents.
How it Works
Learn new skills that will boost your career by enrolling in courses across data analytics, data science, ML and AI. These courses will utilize readings, videos, quizzes, data cases, and even coding exercises to teach you skills and concepts in a way that will solidify your new knowledge for hands-on application.
With our hands-on projects, you will take your newly learned skills along with our 750+ low-code/no-code functions and embedded coding console to complete milestone-based projects. Once completed, you will have effectively applied new skills and concepts to real-world data cases that can be translated directly into your career.
Complete assessments and track your progress in real-time to benchmark your proficiency in relation to key functional areas. As you progress through your courses, our patented platform will utilize ML and AI to record and analyze your inputs and output to provide active feedback and recommendations that will help you learn more effectively than the standard Letter Grade system used today.
Complete courses to earn sharable certificates and badges. These awarded items will be look great in your portfolio as you showcase your skills and project experience to employers and colleagues.
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Our courses include readings, videos, quizzes, and hands-on data cases that are completed using our virtual lab; give learners an applied learning experience.
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