What you would learn in Improving data quality in data analytics & machine learning course?
Every decision we make is dependent on data. Sensory organs are the ones that gather data, our memories contain data, and our gut instincts are also data. If you're planning to make informed decisions, you must be armed with high-quality information.
This class is focused on the quality of data: what it is, what it means, why it's crucial and how to enhance the accuracy and quality of data.
Through this class, you'll be taught:
High-level strategies to ensure high-quality data include terminology, data documentation, management, and the various research phases that can test and improve the quality of your data.
Quantitative and qualitative methods for measuring data quality, such as visual examination, accuracy rate, and outliers. Python code is included to learn how to create these scoring and visualization methods using NumPy, pandas seaborn, and matplotlib.
Particular data methods and algorithms to clean data and eliminate abnormal or unnatural data. Like the previous paragraph, Python code is provided to show how you can implement these processes with NumPy, pandas, seaborn, and matplotlib.
This course is intended for
Data specialists want to know the higher-level strategies and the lower-level processes to assess and improve the quality of data.
Clients, managers, and colleagues who wish to know the importance of quality data even though they're not directly working with data.
Content of the Course:
- Strategies to improve the quality of data
- Ways to assess data quality
- Visualization of data and its interpretation
- How do you identify problems in the data
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