Generative AI

COURSES / GENERATIVE AI

Generative AI Posted on: Jun 27, 2024   Share

Topics - Introduction to Generative AI, Fundamentals of Machine Learning, Deep Learning Basics, Introduction to Neural Networks, Generative Models: Overview, Autoencoders and Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), Transformers and Language Models, Fine-tuning Pre-trained Models, Project and Application Development

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Generative AI    
     
     
     
Day Topics Activities
Day 1 Introduction to Generative AI Overview of Generative AI applications and use cases. Study key concepts and terminologies.
Day 2 Fundamentals of Machine Learning Learn about supervised, unsupervised, and reinforcement learning. Explore key ML algorithms.
Day 3 Deep Learning Basics Introduction to deep learning frameworks (TensorFlow, PyTorch). Understand the basics of deep learning.
Day 4 Introduction to Neural Networks Build and train simple neural networks. Understand activation functions, loss functions, and optimizers.
Day 5 Generative Models: Overview Study different types of generative models (VAEs, GANs, Transformers). Understand their use cases.
Day 6 Autoencoders and Variational Autoencoders (VAEs) Implement basic autoencoders and VAEs. Explore their applications in data generation and reconstruction.
Day 7 Generative Adversarial Networks (GANs) Understand the architecture of GANs. Implement a simple GAN for image generation.
Day 8 Transformers and Language Models Learn about Transformers and their applications in NLP. Study models like GPT and BERT.
Day 9 Fine-tuning Pre-trained Models Fine-tune pre-trained models for specific tasks. Understand transfer learning and its applications.
Day 10 Project and Application Development Develop a project using generative models. Present findings and applications of the developed model.



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Emilly Blunt

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Elsie Cunningham

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Maria Luna

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Maria Luna

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