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Analyzing Crime in Los Angeles
0.75 hours
14.8K
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Solve real-world problemsProjects let you apply your skills using tools like data Notebooks and complete a data analysis from start to finish.
- Learn to code on your own
- Build your own portfolio
- Get real-world experience
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Find out when and where crime is most likely to occur, along with the types of crimes commonly committed in LA.
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8 projects
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Exploring Londons Travel Network
- BeginnerSkill Level
- 4.2+
- 1.5K
Use SQL to analyze a database containing information about Transport for London journeys over 12 years!
Data Engineering, Exploratory Data Analysis, Data Warehouse
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Building a Retail Data Pipeline
- IntermediateSkill Level
- 3.8+
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Test your Data engineering skills by creating a data pipeline to analyze E-commerce business of Walmart!
Python Programming, Data Manipulation, Data Engineering
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Performing a Code Review
- IntermediateSkill Level
- 4.1+
- 985
Review a data analysis workflow for adherence to Python standards and best-practices.
Software Development, Data Engineering
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Factors that Fuel Student Performance
- IntermediateSkill Level
- 3.9+
- 693
Use SQL to analyze a database containing information about Student performance!
Exploratory Data Analysis, Data Engineering
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Cleaning an Orders Dataset with PySpark
- AdvancedSkill Level
- 4.2+
- 536
Step into a data engineers shoes and master data cleaning with PySpark on an e-commerce orders dataset!
Data Engineering, Data Preparation
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Exploring Londons Travel Network
- BeginnerSkill Level
- 4.3+
- 370
Use SQL to analyze a database containing information about Transport for London journeys over 12 years!
Data Engineering, Data Warehouse, Exploratory Data Analysis
project
Exploring Londons Travel Network
- BeginnerSkill Level
- 4.3+
- 366
Use SQL to analyze a database containing information about Transport for London journeys over 12 years!
Data Engineering, Data Warehouse
project
Exploring Londons Travel Network
- BeginnerSkill Level
- 4.3+
- 184
Use SQL to analyze a database containing information about Transport for London journeys over 12 years!
Data Engineering, Data Warehouse
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