Artificial Intelligence
Showing 433–444 of 689 results
Introduction to Image Generation with Google Cloud
Discover how to create images using generative AI techniques on Google Cloud platforms.
Introduction to Intelligent Virtual Agents (IVAs) with IBM watsonx Assistant
This course introduces the IBM watsonx Assistant that focuses on actions and steps to build an AI Assistant.
Introduction to JAX and Deep Learning
Introduction to JAX and its ecosystem of libraries.
Introduction to LangChain for Data Professionals
LangChain is an open-source framework that makes building applications with large language models easy. This course teaches you how to leverage LLMs like GPT for natural language tasks like summarization, chatbots, and code generation.
Introduction to Large Language Models with Google Cloud
Understand large language models and how to leverage Google Cloud for their deployment and use cases.
Introduction to LLMs in Python
Learn the nuts and bolts of LLMs and the revolutionary transformer architecture they are based on!
Introduction to Machine Learning
Learn the basics of machine learning, including algorithms, model evaluation, and real-world applications.
Introduction to machine learning
A high-level overview of machine learning for people with little or no knowledge of computer science and statistics. You'll learn some essential concepts, explore data, and interactively go through the machine learning lifecycle, using Python to train, save, and use a machine learning model, just like in the real world.
Introduction to Machine Learning in Hindi
Learn to build projects by leveraging your ML skills in Hindi
Introduction to Machine Learning with TensorFlow
Explore machine learning concepts and applications using the TensorFlow framework.
Introduction to Microsoft Copilot
Artificial intelligence will change the future of productivity. This course will teach you how Microsoft plans to do it with Microsoft Copilot.
Introduction to MLOps for IoT Edge
Analyze the significance of MLOps in the development and deployment of machine learning models for IoT Edge. Describe the components of the MLOps pipeline and show how you can combine them to create models that can be retrained automatically for IoT Edge devices.