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February 14, 2025
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Launch Your Career in Data Science. Learners will develop expertise in advanced data structures, efficient data analysis, and professional-grade data visualization using Python's most powerful tools.
Instructor: Di Wu
Included with
Recommended experience
Intermediate level
Learners should have basic understanding of Python. If you have no background, please take BiteSize Python for Absolute Beginners first.
Recommended experience
Intermediate level
Learners should have basic understanding of Python. If you have no background, please take BiteSize Python for Absolute Beginners first.
Use advanced data analysis techniques with NumPy and Pandas.
Create visually impactful and interactive visualizations using Matplotlib, Seaborn, and Plotly.
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This specialization dives deep into advanced Python capabilities, including object-oriented programming, high-performance data structures with NumPy and Pandas, and visually impactful data visualization techniques using Matplotlib, Seaborn, and Plotly. Learners will become proficient in managing and analyzing large datasets, crafting interactive visualizations, and presenting insights effectively. These skills align with industry needs in data science, analytics, and reporting roles, preparing learners for professional success.
Applied Learning Project
Through a series of real-world projects, learners will apply their skills to solve authentic problems such as designing efficient data workflows, analyzing business trends, and creating compelling visual stories to communicate findings. Each project reinforces hands-on experience with Python's powerful libraries and frameworks.
Explore Object Oriented Programming in Python
Understand and apply inheritance, polymorphism, encapsulation, and abstraction
Prepare professional documentations for classes and methods
Understanding and utilizing the ndarray from the NumPy library.
Exploring the Series and DataFrame structures in the Pandas library.
Practical applications of advanced data structures in data analysis and manipulation.
Identify the strengths and differences between Matplotlib, Seaborn, and Plotly for various visualization needs.
Create a wide range of plots, including line, bar, scatter, and pie charts, using each of the three packages.
Apply data visualization techniques to real-world data, gaining deeper insights into how to use these tools for storytelling and communication.
CU Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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3 months if you spend 3-4 hours per week
Learners should have basic understanding of Python. If you have no background, please take BiteSize Python for Absolute Beginners first.
Yes. You should take OOP first, then NumPy and Pandas, lastly, Data Visualization.
You can further learn how to use Python for data science, like Data Wrangling and Data Analysis specializations.
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.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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, or you can audit it to view the course materials for free. 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.
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.
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 only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
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.