Total Data Quality Specialization
from 56 reviews of courses in this program
What you'll learn
Explore the Total Data Quality framework.
Learn how to integrate data quality assessments as a critical component in all your projects.
Understand on the initial steps of data science, emphasizing data collection, data source evaluation, and techniques for ensuring high-quality data.
Skills you'll gain
- Data Access
- Data Analysis
- Data Collection
- Data Governance
- Data Integrity
- Data Management
- Data Preprocessing
- Data Processing
- Data Quality
- Data Strategy
- Data Validation
- Design Strategies
- Model Evaluation
- Quality Assurance
- Quantitative Research
- Sampling (Statistics)
- Statistical Analysis
- Threat Detection
- Verification And Validation
Details to know
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Frequently asked questions
There are 3 courses in this specialization, and each course is 4 weeks long. Learners should expect to spend anywhere from 1.5 to 4 hours/week on the lectures, interviews, demonstrations, readings and quizzes. There is also a peer-reviewed assignment at the end of Course 3 (Design Strategies for Maximizing Total Data Quality).
Learners, especially those who may not have had sufficient training in the initial steps of the data science process that focus on data collection and evaluation of data, with an interest in any one of the following will benefit from this specialization: data science, total data quality, data quality and control, research and survey methodologies, research and statistical design, applied statistics, quantitative social sicence, computational social science and big data.
Yes, we strongly recommend that the specialization is completed in the following order of courses:
The Total Data Quality Framework
Measuring Total Data Quality
Design Strategies for Maximizing Total Data Quality
More questions
Financial aid available,