Certified Generative AI expert course

This course covers below mentioed topics to be complete generative AI skills:• Machine learning basics. Supervised and Unsupervised learning. Generative Adversarial Network (GAN) and its application. Variational Autoencoders, Transformers and its application. Convolutional Neural Network , Expert systems, Recurrent neural networks. Generative AI tools (Alphacode, DALL E2, DUET AI, GIThub Copiolet, ChatGPT4 etc.)•Gen-AI basics •Gen- AI and Non Gen- AI•Gen-AI applications•Text Data•Gen-AT text Intro•Chatgpt Overview•Chatgpt - Text generation•Google bard - Text generation•Diffusion AI models•Dream studio platform•Generating Images with Stable Diffusion•Editing Images with Stable Diffusion•Prompt Engineering for Image Generation•Mitigating Data Leakage using Data Masking•Using Private Generative AI Models•Role of Privacy by Design in AIAsideGen AI use in Healthcare, Education, Tourism covered•Potential Risks to Data Privacy in AI•Mitigating Data Leakage using Data Masking•Using Private Generative AI Models•Role of Privacy by Design in AI•Implementing a Data Privacy CultureGenertive  experts have good skills  to  create, innovate, and generate content. They have a deep understanding of generative models, neural networks, machine learning algorithms, and other advanced techniques that enable the creation of novel and creative outputs.Generative AI creates new content, like text or images, based on patterns in data. Large Language Models (LLMs) are a powerful form of this AI, generating human-like text, while Small Language Models (SLMs) focus on specialized tasks with less data. Retrieval-Augmented Generation (RAG) enhances these models by pulling in external information for more accurate results.