University of Colorado Boulder
Data Wrangling with Python Specialization
University of Colorado Boulder

Data Wrangling with Python Specialization

Launch your career in Data Science. By mastering the skills and techniques covered in these courses, students will be better equipped to handle the challenges of real-world data analysis.

Taught in English

Di Wu

Instructor: Di Wu

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Specialization - 5 course series

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4.5

(11 reviews)

Beginner level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • 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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Specialization - 5 course series

Get in-depth knowledge of a subject

4.5

(11 reviews)

Beginner level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 5 course series

What you'll learn

  • You will be able to describe the fundamentals of programming in Python.

  • You will be able to identify data structures for efficient organization and manipulation of data.

  • You will practice using NumPy and Pandas for numerical computing, data manipulation, and analysis.

Skills you'll gain

Category: Python Libraries
Category: Collect data from files
Category: Pandas
Category: Data Integration
Category: Web Scraping

What you'll learn

  • How to utilize Python and Python packages to collect data from various sources

  • How to integrate data collected from various sources to a unified dataset for further processing and analysis

Skills you'll gain

Category: Python Libraries
Category: Data Warehousing
Category: Pandas
Category: Scaling
Category: Pivot Table

What you'll learn

  • Understand and communicate the various statistical aspects of datasets, including measures of central tendency, variation, location, and correlation.

  • Utilize Pandas for data manipulation and preparation to set the foundation for data visualization.

  • Utilize Matplotlib and Seaborn to create accurate and meaningful data visualizations.

Skills you'll gain

Category: Seaborn
Category: Python Programming
Category: Pandas
Category: Data Visualization
Category: Matplotlib

What you'll learn

  • Understand the importance of data processing and manipulation in the data analysis pipeline.

  • Learn techniques to handle missing values and outliers, data reduction, and data scaling and discretization.

  • Understand the concept of data cube and perform multidimensional aggregation for exploratory analysis.

Skills you'll gain

Category: Data Wrangling
Category: Python Libraries
Category: Data Manipulation
Category: Data Visualization
Category: Data Mining

What you'll learn

  • Initiate and conduct a data wrangling project from raw data to a refined dataset for analysis.

  • Apply data wrangling techniques learned in the specialization to handle real-life data scenarios.

  • Utilize Python libraries and tools effectively for data wrangling tasks. Communicate and present data wrangling results effectively to stakeholders.

Skills you'll gain

Category: Data Structure
Category: Ipython
Category: Python Programming
Category: Numpy
Category: Pandas

Instructor

Di Wu
University of Colorado Boulder
15 Courses28,576 learners

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