Build an Object Detection App with TensorFlow and Flask — PickAClass
3.2 (5) ⏱ 2h 42m 📚 27 lessons

Build an Object Detection App with TensorFlow and Flask

Learn to build and deploy a computer vision model as an interactive web application using Python, TensorFlow, and OpenCV.

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About this course

Ever wondered how computers can find and identify objects in images? This course takes you beyond the theory and guides you through building a practical web application that brings computer vision to life. You will create a complete object detection service from the ground up. You'll learn to use powerful libraries like TensorFlow and OpenCV to process images, and then wrap your machine learning model in a web interface with Flask, making it accessible to anyone with a browser. What you'll learn: - Understand the fundamental concepts of computer vision and object detection. - Apply pre-trained deep learning models using TensorFlow for efficient object recognition. - Process and manipulate images with OpenCV to draw bounding boxes and display labels. - Build a functional web application from scratch using the Flask framework. - Create a user-friendly interface to handle image uploads and display the results. - Integrate your TensorFlow model into a Flask backend to create a complete ML service. - Practice setting up a clean Python environment for reproducible project development. The course starts with core terminology and concepts, then moves step-by-step through model integration and web development, culminating in a finished, interactive application. This course is designed for beginners. A basic understanding of Python is all you need to get started. No prior experience with machine learning or web development is required. Start building your first computer vision project today.

What you'll get

  • 📜 Certificate of completion
    Add it to your LinkedIn profile
  • 💬 Personal AI tutor
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  • ♾️ Lifetime access
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  • 📱 Phone or computer
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  • 💸 14-day refund
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  • Short & focused
    2h 42m of practical content

Certificate of completion

Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.

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Certificate of Mastery
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Name Surname
has successfully demonstrated mastery of
Build an Object Detection App with TensorFlow and Flask
Skills demonstrated
Behavioral pattern analysis
Foundational
1.2 hrs
Decision-architecture frameworks
Proficient
1.4 hrs
A/B test design
Proficient
1.7 hrs
Behavioral copywriting
Advanced
1.9 hrs
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PickAClass — Name Surname
Build an Object Detection App with TensorFlow and Flask
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Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
Verify this credential
pickaclass.com/certificates/PCC-2026-X4F7-AP19
Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

Reviews (5)

Oliver Wilson NZ
★ 3 · July 4, 2026

It's a decent introduction. Could benefit from more diverse examples and a slightly better flow between modules.

Astrid Larsen NO Verified learner
★ 4 · July 4, 2026

Good introduction. I appreciated the clear steps, although some of the later modules could have used more examples.

George Green NZ Verified learner
★ 3 · June 30, 2026

Found it useful for a refresher. Not sure it would be the best starting point for a complete beginner, tbh.

Olivia Reed GB
★ 3 · June 17, 2026

Hmm, I'm not sure this is for absolute beginners. It assumes a bit of prior knowledge that wasn't explicitly taught. Some examples were confusing.

রেহানা বেগম BD Verified learner
★ 3 · June 13, 2026

It was a pretty good course overall. Some parts moved a little fast for me, but the examples were generally helpful. Worth the time investment.

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Just a phone or computer with internet. No installs, no special hardware.

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