Machine Learning for Apps

Learn foundational Python for machine learning, how to build an iOS app and how to create a classification model capable of making predictions.

Mobile Apps
Free Course
This free online course covers foundational Python for machine learning. You'll learn how to build an iOS app and how to create a classification model capable of making predictions using neural networks. Your instructor is one of the leading iOS app developers, so start the course today and gain professional skills in machine learning.
  • Duration

    5-6 Hours
  • Assessment

  • Certification

  • Responsive

  • Publisher





View course modules


This free course covers foundational Python, the language most predominantly used in machine learning (ML). The course will show you how to build a classification model from scratch to make predictions, using a world-famous data set to train the model. You'll create a neural network, capable of classifying human handwriting, and then use your neural network to build an iOS app, that can classify handwritten digits drawn on the screen.

The course also shows you how to use an ML model to classify photos in a custom-built app in module six. By the end of this course, you'll be able to apply the concepts and tools learned, to create your own machine learning models and apps for making suggestions and predictions.

Machine learning skills are in high demand worldwide as they can be used in many different ways: doctors can use it to diagnose diseases; it can be used to match people for relationships; it can be used to analyse costly manufacturing procedures. The number one reason for using machine learning in an app, may be that it personalises the app for the user. So start the course today and by the end of the week you'll have gained valuable skills in machine learning and real-world programming skills for using machine learning to build apps.

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Learning Outcomes

Having completed this course you will be able to:

  • Explain what machine learning (ML) is and how it is applied
  • Declare and work with basic Python variables
  • Program basic arrays and tuples in Python
  • Define the two most important characteristics of data for machine learning
  • Describe how data is used to train and test the learning model
  • Discuss the benefits of using Keras rather than TensorFlow
  • Describe how convolutional neural networks classify images
  • Explain the role of max pooling layers, sequential and ReLU
  • Outline the function of dropout layers, nodes and softmax
  • Define how epochs measure accuracy and loss
  • Create an Xcode project and configure an input field, text label and button for an iOS app
  • Provide examples of how core machine learning can be used
  • Create a new Xcode project, including folders and assets


All Alison courses are free to enrol, study and complete. To successfully complete this Certificate course and become an Alison Graduate, you need to achieve 80% or higher in each course assessment. Once you have completed this Certificate course, you have the option to acquire official Certification, which is a great way to share your achievement with the world. Your Alison Certification is:

Ideal for sharing with potential employers - include it in your CV, professional social media profiles and job applications
An indication of your commitment to continuously learn, upskill and achieve high results
An incentive for you to continue empowering yourself through lifelong learning

Alison offers 3 types of Certification for completed Certificate courses:

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