Data Mining and Decision Making: Data Preparation & Predictive Analytics
Data Science 2021
| Intermediate
- 12 Videos | 41m 6s
- Includes Assessment
- Earns a Badge
Data preparation transforms raw data into datasets with stable structures suitable for predictive analytics. This course shows you how to produce clean datasets with valid data to ensure accurate insights for sound business decision-making. Examine the role data sources, systems, and storage play in descriptive analytics. Explore best practices used for data preparation, including data collection, validation, and cleaning. Additionally, investigate some more advanced data exploration and visualization techniques, including the use of different chart types, summary statistics, and feature engineering. Upon completing this course, you'll know how to gather, store, and analyze data to make reliable predictions and smart business decisions.
WHAT YOU WILL LEARN
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discover the key concepts covered in this courserecognize the primary industrial and commercial data sources around us and use this knowledge to select a suitable data source for your business processesdefine key characteristics and requirements for a reliable data collection pipelinedescribe the purpose of the data validation process and name the major steps involved in itoutline several ways to clean a dataset and describe why data cleaning is necessaryspecify how summary statistics can be used to explore and prepare a dataset and define what's meant by measures of frequency and central tendency
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specify how summary statistics can be used to explore and prepare a dataset and describe measures of dispersion and statisticsidentify how data visualization done correctly can become a key business drivername advanced visualization techniques and describe their use casesoutline how feature generation can be used to facilitate business decision-makingoutline how feature reduction can be useful when producing business analyticssummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 13sUP NEXT
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2.Common Industrial and Commercial Data Sources7m 20s
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3.Data Collection Skills and Methods5m 31s
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4.Data Validation Best Practices3m 9s
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5.Data Cleaning Techniques2m 59s
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6.Data Exploration: Summary Statistics2m 54s
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7.Data Exploration: Summary Statistics II4m 19s
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8.Data Exploration: The Power of Visualization3m 47s
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9.Data Exploration: Advanced Visualization2m 55s
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10.Feature Engineering: Feature Generation3m 10s
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11.Feature Engineering: Feature Reduction3m 3s
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12.Course Summary47s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion of this course, which can be shared on any social network or business platform
Digital badges are yours to keep, forever.