Applied AI Lab: Deep Learning for Computer Vision

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Completely Online | 100% Free of Cost | Rigorous Focus on Applied Learning

Computer vision is a powerful application of deep learning, leveraging neural networks to interpret complex visual data. It’s a gateway to mastering AI and is increasingly valuable in industries like healthcare, agriculture, and security. This lab focuses on practical applications of computer vision, empowering students to develop the skills needed to tackle real-world challenges. Through hands-on projects, students will gain experience in cleaning and transforming visual data, training custom models, and applying techniques such as transfer learning.

Program Highlights:

• Cost: Free

• Duration: 10-16 Weeks

• Next Deadline: Rolling Admissions

• Lab Start Date: Upon Acceptance

• Commitment: Self-paced, 10-15 Hours/Week

• Credential Awarded: Sharable Credly Certification

What You Will Learn:
In this self-paced lab, students will gain hands-on experience with six real-world projects, such as:

• Tracking wildlife in Côte d'Ivoire.

• Building and training a convolutional neural network to classify crop disease in Uganda.

• Creating an object detection model to monitor traffic flow in Dhaka, Bangladesh.

• Performing face detection and recognition in a video interview with Mary Kom.

• Generating medical images using neural networks.

• Deploying a meme generator app using a stable diffusion model for social media marketing in the US.

Lab Outcomes:

1. Mapping Challenges to Tasks: Translate real-world challenges into machine learning tasks.

2. Dataset Preparation: Assess and prepare datasets for model training.

3. Neural Networks: Understand model components, optimizers, loss functions, and performance metrics.

4. Model Building: Build, train, and evaluate deep neural networks for computer vision.

5. Model Deployment: Deploy models in real-world AI applications.

6. Debugging: Use strategies and resources to debug AI projects effectively.

7. AI Ethics: Understand the ethical and environmental challenges in deep learning and promote fairness and sustainability.

8. Community of Practice: Learn from a collaborative community of AI practitioners.

How to Apply:
Visit Applied AI Lab: Deep Learning for Computer Vision at WQU to apply.

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