Description
Cleaning Data for Effective Data Science. The first and most critical step in the data science process, creating useful data, is taught. This step is often the most time-consuming part of the job. In this course, participants will learn how to differentiate between different data formats, work with tabular and hierarchical data, extract data from reconstructed sources, and detect anomalies. They will also learn how to assess data quality, correct missing or problematic data, identify and manage outliers, and replace unreliable data with acceptable values. Finally, the principles of sampling are covered. The prerequisite for the course is proficiency in a programming language used in data processing and machine learning. Course topics include ingesting data from tabular (e.g., CSV, spreadsheets) and hierarchical (e.g., XML, JSON, NoSQL databases) formats, as well as extracting data from sources such as web pages and PDF documents. Other courses cover anomaly detection, systematic assessment of data quality by considering biases and normalization techniques, and finally, value substitution using methods such as normalization, trend reflection, and sampling techniques. This course provides the tools necessary to create a comprehensive dataset ready for the next steps in the data science pipeline.
What you will learn
- Distinguish between different types of data formats.
- Working with tabular and hierarchical data formats.
- Extract and receive data from sources that have been reconstructed.
- Detecting and marking anomalous data.
- Data quality assessment.
- Correcting missing or problematic data.
- Identify and handle outliers.
- Substituting acceptable values for missing or unreliable data.
- Using sampling principles.
This course is suitable for people who:
- Developers, data scientists, and engineers interested in improving the quality of datasets.
Course details for Cleaning Data for Effective Data Science
- Publisher: Oreilly
- Instructor: David Mertz
- Education level: Intermediate
- Training duration: 4 hours and 49 minutes
Course topics
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 720p
Download link
File(s) password: www.downloadly.ir
File size
1.1 GB
