Swift Data & CoreML

Integrate Machine Learning into iOS apps. Master CoreML for on-device vision and text models, and SwiftData for modern persistence.

Smart apps run ML on the edge. This course teaches you to integrate Machine Learning directly into iOS applications using CoreML. You will learn to use pre-trained models for image classification and text analysis, and even train simple models using Create ML. We also dive deep into SwiftData, Apple's modern persistence framework, to store complex model results and user data efficiently. This is the intersection of modern iOS engineering and AI.

✅ 100% Free & Lifetime Access

⏱️ 5-Minute Lessons (Bite-sized learning)

🚀 21-Lesson Path (Independent modules)

📱 Mobile Friendly (Learn anywhere)

Apple ML

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Complete Course Syllabus

1

CoreML Basics

Importing and using .mlmodel files in apps.
2

Vision Framework

Detecting faces, text, and barcodes in live video.
3

Create ML

Training custom classifiers without Python code.
4

SwiftData Core

Defining models and saving data with the new framework.
5

Performance

Running inference efficiently on the Neural Engine.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary

$130k - $180k

Career Paths

iOS ML Engineer $140k-$190k

Mobile AI Architect $150k-$200k

Senior iOS Engineer $130k-$175k

What You Will Learn

Integrate CoreML models for offline image and text analysis

Train custom models using Apple's Create ML tool

Implement SwiftData for robust local data persistence

Optimize ML model performance on Apple Silicon Neural Engine

Build smart features like object detection and sentiment analysis

Skills You Will Gain

CoreML SwiftData Create ML Vision Framework iOS Performance

Who Is This For

Senior iOS Devs

ML Enthusiasts

Mobile Architects

Prerequisites

Intermediate Swift

iOS Basics