This specialization covers various essential topics such as fundamental tools, data collection, data understanding, and data preprocessing. This specialization is designed for beginners, with a focus on practical exercises and case studies to reinforce learning. By mastering the skills and techniques covered in these courses, students will be better equipped to handle the challenges of real-world data analysis. The final project will give students an opportunity to apply what they have learned and demonstrate their mastery of the subject.
What's inside
Five courses
Fundamental Tools of Data Wrangling
(5 hours)
Fundamental Tools of Data Wrangling
(5 hours)
Data Collection and Integration
(0 hours)
Data Collection and Integration
(0 hours)
Data Understanding and Visualization
(0 hours)
Data Understanding and Visualization
(0 hours)
Data Processing and Manipulation
(0 hours)
Data Processing and Manipulation
(0 hours)
Data Wrangling with Python Project
(0 hours)
Data Wrangling with Python Project
(0 hours)Learning objectives
- Define techniques and methods for collecting data from various sources including files, web, databases, etc.
- Identify statistical analysis and visualization techniques that can be used to gain insights into the data.
- Calculate and apply techniques for data preprocessing such as dealing with missing values, outliers, sampling, normalization, and discretization.
- Define techniques and methods for collecting data from various sources including files, web, databases, etc.
- Identify statistical analysis and visualization techniques that can be used to gain insights into the data.
- Calculate and apply techniques for data preprocessing such as dealing with missing values, outliers, sampling, normalization, and discretization.
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