Monthly Subscription Starting at AED 99 + VAT

Data Processing and Manipulation
  • Level Professional
  • Duration 29 hours
  • Course by University of Colorado Boulder
  • Offered by

About

The "Data Processing and Manipulation" course provides students with a comprehensive understanding of various data processing and manipulation concepts and tools. Participants will learn how to handle missing values, detect outliers, perform sampling and dimension reduction, apply scaling and discretization techniques, and explore data cube and pivot table operations. This course equips students with essential skills for efficiently preparing and transforming data for analysis and decision-making. Learning Objectives: 1. Understand the importance of data processing and manipulation in the data analysis pipeline. 2. Learn techniques to handle missing values in datasets, including imputation and exclusion strategies. 3. Identify and detect outliers to assess their impact on data analysis and decision-making. 4. Explore sampling methods and dimension reduction techniques for large datasets and high-dimensional data. 5. Apply data scaling techniques to normalize and standardize variables for meaningful comparisons. 6. Utilize discretization to transform continuous data into categorical representations, simplifying analysis. 7. Understand the concept of data cube and perform multidimensional aggregation for exploratory analysis. 8. Create pivot tables to summarize and reshape data, gaining valuable insights from complex datasets. Throughout the course, students will actively engage in practical exercises and projects, allowing them to apply data processing and manipulation techniques to real-world datasets. By the end of the course, participants will be well-equipped to effectively prepare, clean, and transform data for subsequent analysis tasks and data-driven decision-making.

Modules

Missing Values

    • 1 Videos
    • 3 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Missing Values Quiz

1 Videos

  • Missing Values

3 Readings

  • Assessment Strategy
  • Activity Strategy
  • Missing Values Demo

Outliers Detection using Statistics

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Outliers Detection using Statistics

1 Readings

  • Outliers Detection using Statistics Demo

Outliers Detection using IQR

    • 1 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Outliers Detection Quiz

1 Discussions

  • Missing Value and Outliers Detection Exploration Exercise

1 Videos

  • Outliers Detection using IQR

1 Readings

  • Outliers Detection using IQR

Dimension Elimination

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Dimension Elimination

1 Readings

  • Dimension Elimination Demo

Sampling

    • 1 Videos
    • 2 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Data Reduction Quiz

1 Discussions

  • Data Reduction Exploration Exercise

1 Videos

  • Sampling

2 Readings

  • Sampling Demo
  • Data Reduction Case Study

Data Scaling

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Data Scaling

1 Readings

  • Data Scaling Demo

Data Discretization

    • 1 Videos
    • 2 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Scaling and Discretization Quiz

1 Discussions

  • Scaling and Discretization Exploration Exercise

1 Videos

  • Data Discretization

2 Readings

  • Data Discretization Demo
  • Scaling and Discretization Case Study

Pivot Table

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Pivot Table

1 Readings

  • Pivot Table Demo

Data Cube

    • 1 Videos
    • 2 Readings
    • 1 Discussion
    • 2 Assignment
Show info about module content

2 Assignment

  • Data Warehouse Quiz
  • Self Reflection

1 Discussions

  • Data Warehouse Exploration Exercise

1 Videos

  • Data Cube

2 Readings

  • Data Cube Demo
  • Data Warehouse Case Study

Auto Summary

The "Data Processing and Manipulation" course, offered by Coursera, focuses on essential data handling techniques within Data Science & AI. Led by expert instructors, it covers handling missing values, detecting outliers, sampling, dimension reduction, scaling, discretization, data cubes, and pivot tables. With a duration of 1740 minutes, it includes practical exercises and projects. Suitable for professionals, subscription options include Starter and Professional plans. Ideal for those aiming to efficiently prepare, clean, and transform data for analysis and decision-making.

Di Wu
Instructor

Di Wu