BiteSize Python for Intermediate Learners

Overview

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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.

Syllabus

Course 1: BiteSize Python: Object Oriented Programming
- Offered by University of Colorado Boulder. This course introduces the fundamentals of Object-Oriented Programming (OOP) in Python, a ... Enroll for free.

Course 2: BiteSize Python: NumPy and Pandas
- Offered by University of Colorado Boulder. This course delves into advanced data structures in Python, focusing on the powerful capabilities ... Enroll for free.

Course 3: BiteSize Python: Data Visualization
- Offered by University of Colorado Boulder. This course focuses on data visualization, an essential skill for effectively communicating ... Enroll for free.

Courses

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17 hours 15 minutes
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This course focuses on data visualization, an essential skill for effectively communicating insights derived from data. It introduces three widely used Python packages: Matplotlib, Seaborn, and Plotly, each known for its unique capabilities in data visualization. The course covers the basics of these libraries and demonstrates how to create a variety of visualizations, from simple plots to complex interactive graphics. Through hands-on practice and case studies, students will learn how to choose the right visualization for their data, customize their plots, and create compelling visuals that convey meaningful insights. Optional case studies will allow students to deepen their understanding by applying these tools in real-world scenarios.
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13 hours 15 minutes
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This course delves into advanced data structures in Python, focusing on the powerful capabilities of the NumPy and Pandas libraries. It introduces the ndarray, a multidimensional array object provided by NumPy, enabling efficient storage and manipulation of large datasets. Additionally, learners will explore the Series and DataFrame structures offered by Pandas, which facilitate data analysis and manipulation in a more user-friendly manner. Throughout the course, students will engage in practical exercises and case studies to reinforce their understanding of how these advanced data structures can be applied in real-world scenarios.
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16 hours 30 minutes
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This course introduces the fundamentals of Object-Oriented Programming (OOP) in Python, a paradigm widely adopted for structuring complex software. It begins with an explanation of what OOP is and why it is popular, followed by the core principles of OOP: inheritance, polymorphism, encapsulation, and abstraction. Students will also learn how to document classes and methods professionally. The course concludes with practical case studies, allowing learners to apply these concepts in real-world scenarios.