Data Processing Using Python
Learn Python for data acquisition, analysis, and visualization. Master libraries like NumPy, Pandas, and SciPy.
Learn Python for data acquisition, analysis, and visualization. Master libraries like NumPy, Pandas, and SciPy.
This beginner-friendly course introduces Python for data processing, focusing on non-computer majors. Students learn Python basics, data acquisition techniques, powerful data structures, and popular libraries like NumPy and Pandas. The curriculum covers data statistics, mining, and visualization, with practical applications in finance, literature, sociology, and more. The course also introduces object-oriented programming and GUI development, providing a comprehensive foundation in Python for data analysis.
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What you'll learn
Master Python basics including syntax, data types, and control structures
Learn data acquisition techniques from local and network sources
Understand and utilize powerful data structures like dictionaries and sets
Gain proficiency in NumPy, Pandas, and SciPy for scientific computing
Apply data preprocessing, analysis, and visualization techniques
Develop skills in data mining and statistical analysis using Python
Skills you'll gain
This course includes:
11.9 Hours PreRecorded video
8 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This comprehensive course introduces Python for data processing, catering to non-computer majors. The curriculum is structured into six modules, covering a wide range of topics from basic Python syntax to advanced data analysis techniques. Students begin with Python fundamentals, including data types, control structures, and functions. The course then progresses to data acquisition methods, both from local sources and the internet. Learners explore powerful data structures and Python extension libraries, with a focus on NumPy, Pandas, and SciPy for scientific computing. The fourth module delves into data statistics and mining, teaching students how to preprocess, analyze, and visualize data using Python. The course also covers applications in various fields, including finance, literature, and sociology. The final modules introduce object-oriented programming concepts and GUI development, providing a well-rounded understanding of Python's capabilities in data processing.
Welcome to learn Data Processing Using Python!
Module 1 · 23 Minutes to complete
Basics of Python
Module 2 · 8 Hours to complete
Data Acquisition and Presentation
Module 3 · 3 Hours to complete
Powerful Data Structures and Python Extension Libraries
Module 4 · 3 Hours to complete
Python Data Statistics and Mining
Module 5 · 10 Hours to complete
Object Orientation and Graphical User Interface
Module 6 · 3 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Engaging Educator in Data Science
Zhang Li, affectionately known as Zhang Dazhuang or Teacher Dazhuang by her students, is an associate professor in the Department of Computer Science & Technology at Nanjing University. With a doctoral degree and a teaching style marked by amiable humor, she fosters a joyful learning environment. Her research expertise lies in data mining and natural language processing, and she has led and contributed to several nationally funded scientific research projects, as well as educational reform initiatives supported by the Ministry of Education.
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4.1 course rating
360 ratings
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