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30-Day Money-Back Guarantee

This course includes:

  • 9 hours on-demand video
  • 9 articles
  • 39 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Mobile Development Machine Learning

Machine Learning and Artificial Intelligence Using Swift

Learn Image Classifications, Turi Create, Sound Classification, Regression, Core ML, Create ML, Face Detection and more!
Rating: 4.6 out of 54.6 (70 ratings)
786 students
Created by Mohammad Azam
Last updated 10/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Machine Learning and Artificial Intelligence Using Swift
  • Training Models Using Create ML
  • Training Models Using Turi Create with Python
  • Utilizing User Interfaces Implemented in SwiftUI
  • Text Generation and Answer Predictions Using BERT and GPT2 Models
  • Augmented Reality Integration Using ARKit
  • Text and Barcode Detection
  • Face Detection
  • Sentiment Analysis
Curated for the Udemy for Business collection

Course content

20 sections • 102 lectures • 8h 54m total length

  • Preview03:53
  • Preview02:49
  • Exercise Files
    02:10
  • Credit: Practical Artificial Intelligence with Swift
    00:50
  • Resource: Practical Artificial Intelligence with Swift
    00:05

  • What is Artificial Intelligence?
    04:15
  • What is Machine Learning?
    05:45
  • Why Swift?
    03:22
  • Why Machine Learning and AI?
    03:38
  • On-Device Machine Learning vs Remote Machine Learning
    04:49
  • What is Deep Learning?
    02:22
  • Resources: Neural Networks
    00:05

  • Preview05:07
  • Preview06:53
  • Preview04:24
  • Review
    00:43
  • Preview09:43
  • Optional: Displaying Classification Details
    07:01

  • What we will be building?
    01:48
  • Understanding the Steps
    02:08
  • Downloading the Dataset
    05:38
  • Training Model Using CreateML
    09:42
  • What is Vision Framework?
    03:48
  • Implementing Vision Classifier
    08:11
  • Implementing the Classify Function for Vision Classifier
    03:02
  • Performing Image Classification and Displaying Results
    06:42

  • What we will be building?
    01:34
  • Downloading and Structuring the Dataset
    08:42
  • Training Sound Classification Using Create ML
    05:07
  • Integrating Sound Classifier with iOS App
    18:06
  • Resource: Sound Classification Using Turi Create
    00:03

  • What is Face Detection?
    07:51
  • Detecting Number of Faces in an Image
    10:53
  • Highlighting Faces Using Face Detection
    10:21
  • Recognizing Facial Landmarks Using Vision
    14:55

  • What is Text and Barcode Detection?
    02:02
  • Implementing Text Detection
    11:19
  • Implementing Barcode Detection
    10:58
  • Resource: Generating Barcodes
    00:05

  • What we will be building?
    00:47
  • Understanding the Steps
    02:27
  • Downloading and Setting Up Python Using Anaconda
    06:57
  • Understanding the Dataset
    05:25
  • Implementing Python Script for Downloading Images
    16:04
  • Training Model Using Turi Create
    08:51
  • Integrating Model with iOS App
    07:52

  • Understanding Machine Learning and AI in Text and Language
    02:57
  • Language Identification
    12:50
  • Named Entity Recognition
    08:11
  • Assignment - Language Identification Using NSLinguisticTagger
    01:31
  • Solution - Language Identification Using NSLinguisticTagger
    03:06

  • What is Sentiment Analysis?
    01:10
  • Downloading the Dataset
    02:36
  • Understanding the Steps
    03:01
  • Performing Data Analysis Using Pandas
    12:06
  • Training Model Using Create ML
    05:29
  • Training Model Using Playgrounds
    07:26
  • Importing Model and Displaying Classification
    07:04

Requirements

  • Knowledge of Swift Language
  • macOS Catalina
  • Xcode 11.3.1 or above
  • SwiftUI experience is recommended but not required

Description

Are you ready to add Artificial Intelligence and Machine Learning to your iOS Apps?

In this course you will learn how to use the power of Swift Language to integrate machine learning into your applications. Developers with AI & Machine Learning experience get paid around $120,000 yearly salary. This course is over 100 video lectures, which covers every aspect of AI and Machine Learning with Swift Language. All the lectures are accompanied with downloadable source code files.

This course is targeted for developers of all levels of experience. After completing this course, you will be able to successfully add machine learning to your iOS apps.


Check out the contents of the course:

  1. Understanding Machine Learning and Artificial Intelligence

  2. Image Classification Using Pre-existing Models

  3. Image Classification Training Models

  4. Audio Classification

  5. Face Detection

  6. Text and Barcode Detection

  7. Image Classification Using Turi Create

  8. Text and Language

  9. Sentiment Analysis

  10. Sentiment Analysis - Custom Text Classifiers

  11. Drawing Recognition

  12. Activity Recognition Using Core Motion Framework

  13. Style Transfer Using Turi Create

  14. Sentence Generation Using GPT2 Model

  15. Questions and Answers Using BERT

  16. Performing Recommendations

  17. Predicting Prices Using Regression

  18. Augmented Reality Using Artificial Intelligence


What are the prerequisites for this course?

This course requires knowledge of Swift language. SwiftUI framework knowledge is recommended but not required.


Who should take this course?

This course is intended for all iOS developers, who want to power their apps using artificial intelligence and machine learning using Swift language.


What students are saying?

There are a lot of Swift courses that show you how to make twitter or instagram, etc ... but Almost all of them don't pay attention to software engineering best practices. What Mohammad has done here is creating rather small projects that have very high quality and actually teach you how to write good code.


BY FAR THE BEST SwiftUI course. I own/watched all of them. This course has both the most relevant content and the best practices to achieve the end result. I have been programming iOS since the App Store opened. My apps have been featured by Apple many times. But I have learned a great deal from this course. HIGHLY RECOMMENDED.


Learning advanced concepts is hard, but Azam makes it easy to understand. and I'm a person who can't understand without making an app, this course is so helpful and an investment for me.


I hope you enjoy the course!

Who this course is for:

  • Developers who wants to learn about Machine Learning and AI using Swift Language
  • Developers who wants to take their skills to the next level
  • Developers who wants to become a Data Scientist

Featured review

Gilles Poirot
Gilles Poirot
26 courses
8 reviews
Rating: 4.5 out of 59 months ago
I really enjoyed this course. All is well explained, easy to understand even for non native English speaker as me, a lot of resources that helped to focus on what is important and not writing useless code. Thank you Mohammad

Instructor

Mohammad Azam
Apple Featured iOS Developer and iOS Instructor
Mohammad Azam
  • 4.5 Instructor Rating
  • 6,770 Reviews
  • 52,249 Students
  • 28 Courses

My name is Mohammad Azam and I have been programming in iOS for the last 10+ years. Currently, I am teaching Full Stack Development at DigitalCrafts. Before joining DigitalCrafts I worked as a lead mobile developer for many large companies including Schlumberger, Baker Hughes, AIG and Valic. Currently, I am a senior developer at Blinds Dot Com, a Home Depot company. Before iPhone development I was leading projects in Microsoft ASP technology. I was also awarded the Microsoft MVP award five years in a row due to my contributions in the community.

I have also published several of my personal apps to the App Store including Vegetable Tree which was featured by Apple as the most beautiful gardening app on the App Store. I am a frequent speaker at local and national conferences and have authored many articles for many different development magazines.

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