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.
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.

Coursera

University of Colorado Boulder

Data Collection and Integration (Coursera)

Statistics & Data Analysis Data Science

Embark on a journey to become proficient in collecting and integrating various types of data with the 'Data Collection and Integration' course. This course is designed to equip you with essential skills for extracting information from files, databases, web pages, and APIs, using powerful tools such as Pandas, Beautiful Soup, and SQL. Whether you're new to data science or looking to enhance your current skill set, this course will provide you with the practical knowledge needed to tackle real-world data integration challenges.

Jun 8th 2026

5-12 Weeks

Python SQL Data Collection

Coursera

University of Colorado Boulder

Data Processing and Manipulation (Coursera)

Statistics & Data Analysis Data Science

Discover how to efficiently process and manipulate data with our comprehensive 'Data Processing and Manipulation' course. Designed for beginners and professionals alike, this course will teach you the fundamental skills needed to handle raw data effectively, ensuring it is ready for analysis and decision-making processes.

Jun 8th 2026

4 Weeks

Python Data Warehousing Data Manipulation

Coursera

University of Colorado Boulder

Fundamental Tools of Data Wrangling (Coursera)

Statistics & Data Analysis Data Science

Discover the art and science of data preparation with 'Fundamental Tools of Data Wrangling'. This course equips you with the necessary skills to effectively clean, manipulate, and analyze your data using powerful tools like Python, NumPy, pandas, and more. Whether you're new to data wrangling or looking to refine your existing skills, this course offers a practical approach to mastering the fundamentals.

Jun 8th 2026

5-12 Weeks

Python Data Structures IPython

Coursera

University of Colorado Boulder

Data Understanding and Visualization (Coursera)

Statistics & Data Analysis Data Science

Discover the secrets to making sense of your data with 'Data Understanding and Visualization'. Learn key statistical principles and transform raw data into clear, insightful visuals that tell a story. Perfect for beginners and professionals alike, this course equips you with the skills to analyze and present data effectively.

Jun 8th 2026

4 Weeks

Python Data Visualization Python Programming

Coursera

University of Colorado Boulder

Data Wrangling with Python Project (Coursera)

Statistics & Data Analysis Data Science

Embark on a comprehensive journey through data wrangling with our hands-on 'Data Wrangling with Python Project' course. This course is designed to equip you with the essential skills needed to navigate the complex world of data processing. By following a real-life project, you'll learn how to identify and source data, clean it, integrate various datasets, and prepare them for analysis using Python. Whether you're new to data science or looking to refine your existing skills, this course offers practical experience that's crucial in today's data-driven world.

Jun 8th 2026

5-12 Weeks

Python Data Mining Data Wrangling

Coursera

University of Colorado Boulder

Classification Analysis (Coursera)

Statistics & Data Analysis Data Science

Dive into the 'Classification Analysis' course and unlock a deep understanding of how to classify data using various powerful algorithms. This comprehensive course on Coursera will guide you through key classifiers like K-Nearest Neighbors (KNN), Decision Trees, Support Vector Machines (SVM), Naive Bayes, and Logistic Regression. You'll gain practical experience by applying these techniques to actual datasets, enhancing your ability to perform data analysis effectively.

Jun 8th 2026

5-12 Weeks

Classification Logistic Regression Support Vector Machines

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