Apple Foundation Models: On-Device AI Session Management

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

7 weeks, 1 hour a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

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Overview

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Develop a Text Summary app using Apple Foundation Models, focusing on session management, transcript handling, and error recovery. Build a Travel Assistant chatbot while mastering single-turn vs multi-turn conversations and AI integration techniques. In this course, you will learn to build a Text Summary app with Apple Foundation Models, focusing on core concepts like session management, handling exceptions, and transcript management. The course starts by teaching you how to set up Views and ViewModels to structure your app before diving into the integration of Apple's Foundation Model for efficient text summarization. You'll also learn how to handle both single-turn and multi-turn conversations, a crucial aspect when building AI-driven applications. As you progress, you’ll explore deeper features like error recovery, where you'll master techniques to handle exceeded context size exceptions and ensure seamless user interactions. You will gain hands-on experience with building a Travel Assistant chatbot that incorporates advanced UI elements like Liquid Glass and Markdown support. This will give you the tools to tackle real-world app development challenges and implement intelligent, responsive systems. The course’s structure ensures a gradual learning curve, providing ample opportunities to apply each concept in practical scenarios. By the end, you will have a fully functional app ready to be showcased, with solid knowledge of Apple Foundation Models and their real-world applications in AI development. This course is ideal for developers and technical professionals who wish to deepen their understanding of Apple's Foundation Models and on-device AI integration. A background in Swift programming and iOS/macOS app development is recommended. This course will particularly benefit those interested in building AI-powered applications, working with text summarization models, and mastering session management for dynamic user interactions. In this course, you will develop a Text Summary app using Apple Foundation Models, focusing on building essential components like View and ViewModel. Along the way, you'll master key AI concepts such as session management, transcript handling, and handling errors in real-world scenarios. You will also learn the difference between single-turn and multi-turn conversations. This course is based on Apple Foundation Models in Action - Session Management for On-Device AI, by DevTechie.com DevTechie.com. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

Course Introduction
- This module provides an overview of the course structure and introduces the fundamental concepts of Apple Foundation Models, focusing on their role in session management for on-device AI. Learners will gain a clear understanding of how these models are applied in real-world scenarios.
Text Summary App with Apple Foundation Models
- This module covers the development of a text summary app using Apple Foundation Models, focusing on implementing View and ViewModel architecture, integrating machine learning models, and applying best practices for on-device LLM usage.
Single Turn vs Multi Turn Conversations with Apple Foundation Models
- This module explores the distinctions between single-turn and multi-turn conversations in Apple Foundation Models, focusing on session management, context handling, and practical implementation strategies. Learners will gain insight into how to design effective conversation flows and manage state in language model interactions.
Session Management and Transcript: Deep Dive
- This module explores session management techniques and strategies for handling context limits in Apple Foundation Models. Learners will gain insights into managing session transcripts and recovering from exceptions to maintain effective conversational AI interactions.
Prompts vs Instructions
- This module explores the distinctions between prompts and instructions in AI models, their influence on model outputs, and strategies for crafting effective prompts to improve response quality and consistency.
Respond Function
- This module explores the functionality and application of the 'Respond' function in session management for Apple Foundation Models. Learners will gain an understanding of how it interacts with on-device large language models and how to customize its behavior for specific use cases.
Travel Assistant Chatbot
- This module guides learners through the development and design of a travel assistant chatbot, covering key aspects such as conversation management, user interface implementation, and integration of advanced features like Liquid Glass UI and markdown support.