Python Project: Software Engineering and Image Manipulation
Master practical Python programming through comprehensive image processing projects, utilizing PIL and Tesseract OCR for advanced application development.
Master practical Python programming through comprehensive image processing projects, utilizing PIL and Tesseract OCR for advanced application development.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Python 3 Programming Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.2
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English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Master Python imaging library for image manipulation
Implement optical character recognition with Tesseract
Work effectively with third-party APIs and libraries
Develop real-world Python applications
Apply software engineering principles in projects
Create portfolio-ready programming projects
Skills you'll gain
This course includes:
2.5 Hours PreRecorded video
3 programming assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This hands-on course focuses on practical Python programming through real-world image processing projects. Students learn to work with third-party APIs and libraries, including the Python Imaging Library (PIL) for image manipulation and Tesseract for optical character recognition. The curriculum combines software engineering principles with practical implementation, guiding students through creating portfolio-worthy projects that demonstrate their Python programming skills.
Introduction
Module 1 · 2 Hours to complete
The Python Imaging Library (PIL)
Module 2 · 1 Hours to complete
Optical Character Recognition (OCR) with Tesseract
Module 3 · 4 Hours to complete
Fee Structure
Instructor
Associate Professor at the University of Michigan
Christopher Brooks is an Associate Professor in the School of Information at the University of Michigan, where he specializes in designing tools to enhance teaching and learning experiences in higher education. His research focuses on the application of learning analytics within human-computer interaction, utilizing methods from educational data mining, machine learning, and information visualization. Brooks has published extensively in these areas and is actively involved in directing the Educational Technology Collective, which includes postdoctoral scholars and students collaborating on innovative projects. He teaches various courses related to applied data science and has contributed to online education platforms such as Coursera. His work aims to leverage data to improve educational outcomes and foster better learning environments.
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4.2 course rating
1,458 ratings
Frequently asked questions
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