University of Colorado Boulder
Data Wrangling with Python Specialization
1,689 enrolled
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.

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(28 reviews)

Beginner level

Recommended experience

Flexible schedule
2 months at 10 hours a week
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Get in-depth knowledge of a subject

(28 reviews)

Beginner level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Earn a career credential
Share your expertise with employers

Overview

  • 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.

What’s included

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Taught in English
32 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from University of Colorado Boulder

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 Programming
Category: Data Structures
Category: Data Wrangling
Category: Pandas (Python Package)
Category: Data Manipulation
Category: NumPy
Category: Data Integration
Category: Computer Programming
Category: Data Analysis
Category: Descriptive Statistics
Category: Data Cleansing
Category: Data Transformation
Category: Statistical Analysis

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: Data Integration
Category: Data Collection
Category: Pandas (Python Package)
Category: Databases
Category: SQL
Category: Web Scraping
Category: Application Programming Interface (API)
Category: Data Processing
Category: Data Quality
Category: Data Cleansing
Category: Scripting
Category: Data Wrangling
Category: Extensible Markup Language (XML)
Category: Data Manipulation

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: Scatter Plots
Category: Seaborn
Category: Pandas (Python Package)
Category: Histogram
Category: Box Plots
Category: Data Visualization Software
Category: Descriptive Statistics
Category: Correlation Analysis
Category: Matplotlib
Category: Data Analysis
Category: Exploratory Data Analysis
Category: Data Visualization
Category: Statistical Analysis
Category: Statistics
Category: Data Storytelling
Category: Python Programming
Category: Statistical Visualization

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: Pandas (Python Package)
Category: Data Warehousing
Category: Pivot Tables And Charts
Category: Sampling (Statistics)
Category: Anomaly Detection
Category: Data Transformation
Category: Data Manipulation
Category: Dimensionality Reduction
Category: Statistical Methods
Category: Exploratory Data Analysis
Category: Data Processing
Category: Data Cleansing

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 Wrangling
Category: Descriptive Statistics
Category: Data Transformation
Category: Data Integration
Category: Exploratory Data Analysis
Category: Data Collection
Category: Pivot Tables And Charts
Category: Data Cleansing
Category: Dimensionality Reduction
Category: Statistical Analysis
Category: Data Analysis
Category: Data Processing
Category: Data Visualization
Category: Statistical Visualization
Category: Data Mining
Category: Data Manipulation
Category: Data Quality

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Instructor

Di Wu
University of Colorado Boulder
21 Courses50,964 learners

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