Generative AI Models and Transformer Networks Certification
About this course
This specialization provides a hands-on pathway to mastering Generative AI techniques from foundational architectures to cutting-edge deployment strategies. Learn to build and train Autoencoders, VAEs, and GANs using TensorFlow to generate synthetic data and realistic outputs. Dive into attention mechanisms and Transformer models powering GPT and BERT. Apply RAG for improved accuracy and analyze emerging GenAI trends to create industry-ready solutions. By the end of this program, you will be able to: - Train Generative Models: Build and evaluate VAEs and GANs using real-world data - Generate Synthetic Data: Use VAEs and GANs to create images and other outputs - Apply Transformer Models: Leverage attention mechanisms in models like GPT and BERT - Improve Output Accuracy: Use Retrieval Augmented Generation (RAG) for enhanced results - Deploy GenAI Solutions: Translate emerging model trends into industry-ready applications Ideal for developers, ML engineers, and AI enthusiasts exploring next-gen model development.
75/100
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- Who stands behind it
- 20/35
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- 16/20
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What you'll learn
- Build and evaluate VAEs and GANs using real-world data
- Generate images and other outputs with VAEs and GANs
- Leverage attention mechanisms in Transformer models
Course objectives
- Train Generative Models
- Generate Synthetic Data
- Apply Transformer Models
- Improve Output Accuracy
- Deploy GenAI Solutions
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