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Building Integrated AI Applications | AISV.805
This course provides developers a hands-on, practical, and industry-oriented training on how to integrate artificial intelligence (AI) into enterprise application development. You will learn to apply your skills to cutting edge AI applications using deep learning and widely used deep learning frameworks during hands-on classroom sessions.
We’ll start with an introduction to AI and neural networks, focusing on convolutional neural networks and how they work, then perform training and inference using Tensorflow/Keras for image detection, recognition and segmentation. The end of the course culminates in a final project encompassing the new technologies you’ve learned such as:
- Advanced python and applying data science libraries—SciPy, SciKit-Learn, Numpy, Pandas, Pillow—for pre and post model processing
- DNN and how it fits in AI and traditional ML techniques
- Concepts of supervised deep learning models
- Deep learning models
- Training and performing inference on a CNN
- Application building with a deep learning model
- Various use cases for classification, segmentation and detection
Python knowledge and programming experience. Recommended courses include: “Python for Programmers” and “Python Programming for Beginners”
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