Building Intelligent iOS Apps with Core ML — PickAClass
⏱ 2h 42m 📚 27 lessons 🎧 Audio version

Building Intelligent iOS Apps with Core ML

Integrate powerful machine learning models into your iOS applications to build smart, privacy-first features like real-time image and text analysis using Swift.

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About this course

Mobile apps are no longer just static interfaces; modern users expect intelligent, context-aware experiences that run seamlessly on their devices. By leveraging Core ML, you can integrate powerful machine learning models directly into your iOS apps without relying on slow and costly cloud APIs. In this text-based course, you will transition from a standard iOS developer to one capable of implementing on-device artificial intelligence. You will learn how to integrate pre-trained models, handle real-time data streams, and design intuitive, smart user interfaces that respect user privacy by processing data entirely on-device. What you'll learn: - Understand the foundational concepts of machine learning on mobile devices and how Core ML operates within the iOS ecosystem. - Integrate pre-trained machine learning models into Swift applications for instant classification and prediction. - Implement real-time image analysis and computer vision features using the Vision framework. - Apply natural language processing techniques to analyze and classify text input directly on-device. - Configure and optimize model performance to ensure smooth, battery-efficient execution on iOS devices. - Practice deploying and testing intelligent features through structured, step-by-step code walkthroughs. The course begins with core definitions and the architecture of on-device AI, then guides you through practical text and image processing scenarios, culminating in optimization strategies for responsive apps. Designed specifically for iOS developers and beginners curious about mobile AI, this course requires only a basic understanding of Swift and no prior machine learning experience. Start reading today to unlock the potential of on-device machine learning in your iOS projects.

What you'll get

  • 📜 Certificate of completion
    Add it to your LinkedIn profile
  • 💬 Personal AI tutor
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  • 🎧 Audio version included
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  • ♾️ Lifetime access
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  • 📱 Phone or computer
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  • 💸 14-day refund
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  • Short & focused
    2h 42m of practical content

Certificate of completion

Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.

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Certificate of Mastery
This certifies that
Name Surname
has successfully demonstrated mastery of
Building Intelligent iOS Apps with Core ML
Skills demonstrated
Behavioral pattern analysis
Foundational
1.2 hrs
Decision-architecture frameworks
Proficient
1.4 hrs
A/B test design
Proficient
1.7 hrs
Behavioral copywriting
Advanced
1.9 hrs
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PickAClass — Name Surname
Building Intelligent iOS Apps with Core ML
Page 2 of 2
Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
Verify this credential
pickaclass.com/certificates/PCC-2026-X4F7-AP19
Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

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Frequently asked

What do I need to take this course? +

Just a phone or computer with internet. No installs, no special hardware.

How do I pay? +

By card via Stripe. We don’t store card details — Stripe handles them securely.

Can I get a refund? +

Yes — full refund within 14 days, no questions asked.

How long will I have access? +

Forever. Once you purchase, the course is yours to revisit anytime.

Will I get a certificate? +

Yes. On completion you'll receive a certificate you can add to your LinkedIn profile.

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