Introduction to Generative AI

Javier Ideami

55 Minutes
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"Introduction to Generative AI" is a meticulously crafted course designed to navigate the fascinating world of artificial intelligence that creates: Generative AI. Starting with the fundamentals, this course lays the foundation for understanding how machines learn and evolve. You'll explore the intricate workings of machine learning and neural networks, leading to a deep dive into the key generative AI models that are revolutionizing industries. Whether you're a budding enthusiast or a professional aiming to integrate AI into your work, this course promises to equip you with the knowledge and insights needed to navigate the evolving landscape of Generative AI confidently. Join us to embark on this enlightening journey into the future of technology.

Explore the Course Plan
Module 1: Fundamentals of Generative AI

Introduce the concept of Generative AI, differentiating it from discriminative models. Explore its evolution from GANs to large language models and multimodal systems, illustrating its diverse applications in various fields.

Module 2: Machine Learning and Neural Networks

Delve into the types of machine learning (supervised, unsupervised, reinforcement) and the structure of neural networks. Understand how neural networks function as a 'magical factory' transforming inputs into outputs, and the basics of deep learning.

Module 3: Key Generative AI Models

Explore essential generative AI models like GANs, autoregressive models, variational autoencoders, diffusion models, and flow-based models. Understand their unique functionalities, advantages, and typical applications.

Module 4: Generative AI in Creative Tools and Storytelling

Discover how Generative AI is revolutionizing creative industries. Learn its applications in Photoshop, movie storytelling, and music production, enhancing creative processes and output.

Module 5: Ethical Considerations in Generative AI

Address the ethical implications of Generative AI, including copyright, transparency, bias, impact on employment, and societal impact. Emphasize the importance of responsible AI and ethical data use.

Module 6: Deep Dive into Machine Learning Types

Further explore the nuances of machine learning types and the intricacies of neural network training. Discuss the challenges of overfitting and underfitting, and the role of regularization techniques.

Module 7: Recap and Future of Generative AI

Summarize key takeaways from Generative AI, revisiting its architectures and potential applications. Envision the future impact of this technology in various domains and its role in augmenting human creativity.

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