
Overview
This Data Wrangling with Python course offered by Coursera in partnership with University of Colorado Boulder 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.
Applied Learning Project
The final project provides students with an opportunity to apply the knowledge gained throughout the specialization in a real-life data wrangling project of their interest. Participants will follow the data wrangling pipeline step by step, from identifying data sources to processing and integrating data, to achieve a fine dataset ready for analysis. This course enables students to gain hands-on experience in the data wrangling process and prepares them to handle complex data challenges in real-world scenarios.
What You Will Learn:
- Define techniques and methods for collecting data from various sources including files, web, databases, etc.
- Calculate and apply techniques for data preprocessing such as dealing with missing values, outliers, sampling, normalization, and discretization.
- Identify statistical analysis and visualization techniques that can be used to gain insights into the data.
Skills You Will Gain:
- Data Wrangling
- Seaborn
- Python Libraries
- Python Programming
- Statistical Analysis
- Numpy
- Pandas
- Data Visualization
- Matplotlib
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Fundamental Tools of Data Wrangling
- Data Collection and Integration
- Data Understanding and Visualization
- Data Processing and Manipulation
- Data Wrangling with Python Project
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 2 months
- Flexible
Start dates & application deadlines
Language
Delivered
Disciplines
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Visit programme websiteWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Beginner level
- Recommended experience: Students are expected to know basic Python and statistics to be most comfortable.
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.