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Now that you’ve taken several courses on data science and machine learning, it’s time to put your learning to work on a data problem involving a real life scenario. Employers really care about how well you can apply your knowledge and skills to solve real world problems, and the work you do in this capstone project will make you stand out in the job market.
In this capstone project, you’ll explore data sets in New York’s 311 system, which is used by New Yorkers to report complaints for the non-emergency problems they face. Upon being reported, various agencies in New York get assigned to resolve these problems. The data related to these complaints is available in the New York City Open Dataset. On investigation, one can see that in the last few years the 311 complaints coming to the Department of Housing Preservation and Development in New York City have increased significantly.
Your task is to find out the answers to some of the questions that would help the Department of Housing Preservation and Development in New York City effectively tackle the 311 complaints coming to them. You will need to use the techniques you learned in your previous Python, data science, and machine learning courses, including data ingestion, data exploration, data visualization, feature engineering, probabilistic modeling, model validation, and more.
By the end of this course, you will have used real world data science tools to create a showcase project and demonstrate to employers that you are job ready and a worthy candidate in the field of data science.
- Apply your knowledge of data science and machine learning to a real life scenario
- Analyze and visualize data using Python
- Perform a feature engineering exercise using Python
- Build and validate a predictive machine learning model using Python
- Create and share actionable insights to real life data problems
- Lectures 0
- Quizzes 0
- Duration 6 weeks
- Skill level All levels
- Language English
- Students 0
- Assessments Yes