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Machine Learning for Apps
Learn the basics of how to use Python for machine learning and iOS app development with this free online course.
Description
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.
Start Course NowModules
Essential Software
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Essential Software - Learning Outcomes
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Introduction to the Course
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What is Machine Learning?
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Machine Learning Basics
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Installing Anaconda
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Atom and Plugins
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Essential Software - Lesson Summary
Python Basics
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Python Basics - Learning Outcomes
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Variables in Python
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Python Functions, Conditionals and Loops
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Python Arrays and Tuples
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Modules in Python
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Python Basics - Lesson Summary
Classification Modelling
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Classification Modelling - Learning Outcomes
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About Scikit-Learn
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Installing Scikit-Learn
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Iris Flower Dataset
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Dataset Features and Labels
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Preparing Data
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Training a Classifier
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Testing Prediction Accuracy
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Building a Classifier
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Classification Modelling - Lesson Summary
Convolutional Neural Network
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Convolutional Neural Network - Learning Outcomes
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Introduction to Keras
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Convolutional Neural Networks
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Installing Keras and PIP
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Preparing the Dataset
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Using Sequential
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Sequential Process
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Training the Data
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Core ML Model
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Convolutional Neural Network - Lesson Summary
Building the App
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Building the App - Learning Outcomes
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Introduction to the Module
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Building the Interface
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Drawing On Screen
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Core ML Import
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Utilizing Core ML
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Displaying Prediction Results
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Building the App - Lesson Summary
Core ML Basics
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Core ML Basics - Learning Outcomes
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About Core ML
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Core ML Photo Analysis
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New Xcode Project
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Building the ImageVC
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ImageCell and Subclass
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Food Items Helper File
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Custom Grid
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Importing Core ML Model
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Passing In Images
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Handling Prediction Results
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Core ML Photo Challenge
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Core ML Basics - Lesson Summary
Course assessment
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
Certification
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 an official Certificate, which is a great way to share your achievement with the world. Your Alison Certificate 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 Certificates for completed Certificate courses:
Digital Certificate - a downloadable Certificate in PDF format, immediately available to you when you complete your purchase
Certificate - a physical version of your officially branded and security-marked Certificate, posted to you with FREE shipping
Framed Certificate - a physical version of your officially branded and security-marked Certificate in a stylish frame, posted to you with FREE shipping
All Certificates are available to purchase through the Alison Shop. For more information on purchasing Alison Certificates, please visit our FAQs. If you decide not to purchase your Alison Certificate, you can still demonstrate your achievement by sharing your Learner Record or Learner Achievement Verification, both of which are accessible from your Dashboard. For more details on our Certificate pricing, please visit our Pricing Page.
