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Building Integrated AI Applications | AISV.805
This course provides developers a practical, industry-oriented training on how to develop integrated artificial intelligence (AI) applications for enterprises. Leveraging knowledge acquired through various elective courses, you will learn to apply your skills to cutting-edge AI applications during hands-on classroom sessions using machine learning frameworks.
Prerequisites:
One of the following courses or equivalent coursework or industry experience: "Deep Reinforcement Learning," "GANs for Data Synthesis," "Natural Language Processing," or "Artificial Intelligence for Robotics."
In the classroom, we’ll focus on convolutional neural networks and how they work, and perform training and inference using Tensorflow/Keras for image detection, recognition and segmentation. You’ll learn various aspects of designing and deploying applications in the real world and work on a final project encompassing the new technologies you’ve learned.
Learning Outcomes
At the conclusion of the course, you should be able to
- Describe the technical and non-technical aspects of planning, designing and deploying an AI-based enterprise application
- Train and fine-tune a deep learning model on the cloud with existing datasets
- End-to-end application services design and considerations, deployment, and support
- Develop and deploy an enterprise cloud based application
- Explain what federated learning and continuous learning are and why they are needed
- Describe and demonstrate AI techniques
Topics Include
- DNN and how it fits in AI and traditional ML techniques
- Concepts of supervised deep learning models
- End-to-end application services design and considerations, deployment, and support
- Understanding of various AI cloud services and their deployment models
- Scoping a project, setting requirements, timelines, and deliverables
- MLOps overview
- Federated learning and on-device learning
Skills Needed
A working knowledge of AWS.Prerequisites:
One of the following courses or equivalent coursework or industry experience: "Deep Reinforcement Learning," "GANs for Data Synthesis," "Natural Language Processing," or "Artificial Intelligence for Robotics."
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Estimated Cost: $795
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