Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Python for Business Data Science Specialization

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Python for Business Data Science Specialization

Master Python for Business Data Science.

Master core Python tools to analyze data and automate Excel reports.

Instructor: Madecraft

Included with Learn more

3 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Use Python's built-in functions, NumPy, SciPy, pandas, matplotlib, and seaborn to inspect, transform, and visualize real datasets.
Apply advanced pandas techniques to clean, combine, reshape, and summarize messy, multi-source data.
Build and automate polished Excel reports with openpyxl, including formatting, charts, and conditional formatting.

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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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 Madecraft

Specialization - 3 course series

This Specialization is intended for business professionals and analysts seeking to develop practical Python skills for real-world data work. Through three courses, you'll cover core Python data science tools (built-in functions, NumPy, SciPy, pandas, matplotlib, and seaborn), advanced pandas techniques for cleaning, combining, and reshaping messy datasets, and openpyxl for building and automating polished Excel reports. By the end, you'll be able to inspect, clean, analyze, and visualize real business data, and turn manual reporting work into fast, repeatable Python workflows.

Applied Learning Project

Learners in this specialization apply their skills through hands-on projects using real, messy datasets: cleaning and reshaping multi-source data in pandas, running statistical tests and array-based calculations with NumPy and SciPy, and building a fully automated Excel report (complete with formatting, charts, and conditional formatting) using openpyxl. Each project mirrors an authentic business analytics task, so learners leave with reusable workflows they can apply directly to their own reporting and analysis work.

Python Functions for Data Science

Course 1, 6 hours

What you'll learn

Inspect, aggregate, and transform data using Python's built-in functions and NumPy arrays.
Analyze data with SciPy's statistical tools and structure it for real analysis with pandas.
Visualize your findings clearly using matplotlib and seaborn.

Using Python With Excel

Course 2, 4 hours

What you'll learn

Load, inspect, and manipulate data of any size using Python's pandas library.
Use openpyxl to build, structure, and format Excel workbooks directly through code.
Create advanced graphs and automated, multi-source reports that combine pandas and openpyxl.

Advanced Pandas

Course 3, 5 hours

What you'll learn

Clean, convert, and prepare messy real-world data using pandas core DataFrame functions.
Combine and reshape multiple datasets through grouping, merging, and pivoting techniques.
Extend pandas with automated profiling, geospatial analysis, and big data frameworks like Dask.

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Madecraft

133 Courses11,937 learners

Offered by

Madecraft

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Frequently asked questions

Based on the module time estimates in each course outline, the hands-on content adds up to about 22 hours total: roughly 8.7 hours for Python Functions for Data Science, 6.2 hours for Using Python With Excel, and 7.2 hours for Advanced Pandas.

Basic familiarity with Excel and prior exposure to Python fundamentals (variables, loops, functions) is helpful.

Each course does include its own basic setup section, so a learner could technically start anywhere, but this order gives the smoothest skill progression.

Python Functions for Data Science — establishes the broad foundation (built-in functions, NumPy, SciPy, pandas basics, matplotlib/seaborn).
Using Python With Excel — applies pandas plus openpyxl to a business-facing deliverable (automated Excel reports).
Advanced Pandas — goes deep on the pandas skills only lightly touched in Python Functions for Data Science.

By the end of this Specialization, you'll be able to inspect, clean, and transform messy, multi-source datasets using Python's built-in functions, NumPy, SciPy, and pandas, apply advanced pandas techniques to reshape, merge, and summarize real-world data for analysis, and build fully automated, visually polished Excel reports with openpyxl, turning hours of manual reporting work into a repeatable Python workflow.