Explore GPT models in the OpenAI Playground. Experiment with parameters to fine-tune responses and learn how to utilize multiple APIs, including chat completions and assistant APIs.

Explore fine-tuning AI models like GPT-3 and 4 with OpenAI APIs. Learn to utilize the Assistants API and understand the creation and comparison of text embeddings.

Explore OpenAI's DALL-E and Whisper models. Generate stunning images with text prompts, transcribe and translate multilingual audio with high accuracy.

This course demystifies convolutional neural network architectures using PyTorch for image classification and object detection.

Understand value-based methods in reinforcement learning for optimizing decision-making processes.

Explore large language models (LLMs) and vector databases, including ANN search, similarity methods, and practical skills using BERT and ChromaDB embeddings.

This course will teach you how to generate embeddings and use vector databases for semantic search apps, recommendations, and multimodal solutions.

This course introduces Vertex AI Vector Search and describes how it can be used to build a search application with large language model (LLM) APIs for embeddings. The course consists of conceptual lessons on vector search and text embeddings, practical demos on how to build vector search on Vertex AI, and a hands-on lab.

Discover the power of Retrieval-Augmented Generation (RAG) in modern NLP applications. This course will teach you how to implement a RAG-based chatbot using Python and TensorFlow, focusing on text embeddings and retrieval techniques.

Welcome to "Virtual Agent Development in Dialogflow CX for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations using Dialogflow CX. This is an intermediate course, intended for learners with the following types of roles: Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows. Citizen developers: Creates new business applications for consumption by others using high level development and runtime environments. Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API. Prerequisite: Before taking this course, learners should have completed the CCAI Conversational Design Fundamentals course.

Welcome to "Virtual Agent Development in Dialogflow CX for Software Devs", the third course in the "Customer Experiences with Contact Center AI" series.

Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series.