Generative AI is being rapidly adopted by organizations of all sizes and varying missions. Successful project managers must learn how this technology can best be put to use in achieving their goals. This course will help you do just that.

Explore the ethics, issues, and limitations of generative AI. Gain insights into AI models, examine case studies on ethical dilemmas, and learn about data bias, IP rights, deepfakes, and the impact on work and creativity.

In this fast-paced, pragmatic introduction, quickly ramp up on the current state of generative AI, including how to get better results from tools like ChatGPT, Anthropic Claude, and Google Bard.

Master the art of crafting effective prompts for chatbots and generative AI. Learn techniques to get better results by tailoring prompts using attributes like length, style, perspective and examples to guide any model.

Explore the core concepts of generative AI, including types, models, and use cases in various domains.

Explore the foundational concepts of generative AI and how to implement them with Google Cloud tools.

Dive into AI with Generative Adversarial Networks (GANs). Learn to use PyTorch for model creation and training, and Deep Convolutional GANs for image optimization.

Master VAEs for image generation: Learn probabilistic encoders and decoders. Train models on multichannel color images using Python in Colab.

Dive into unsupervised learning with autoencoders. Train models to reconstruct high-dimensional images and denoise corrupted images using PyTorch in colab.

Unlock Amazon Bedrock's potential for GenAI. Learn core concepts, model design, project evaluation, and innovative GenAI business application development.

Build cutting-edge generative AI models with Amazon SageMaker. Explore GANs, VAEs, optimization, transfer learning, deployment, and monitoring techniques.

Learn to create intelligent chatbots using Amazon Lex and Polly. Dive into context-aware conversations, sentiment analysis, and integration with high-security standards.