Special Offer:

AI Maker
Course

Minimum 5 student accounts

HKD200(USD30)/student
10 Core Modules (10 hours in total)
Microsoft AI-900 self-study materials with videos (8 hours in total)
2 hours teacher training
Priority technical support

What you will learn

Hardware Requirement:

  • Learn with WebApp, or learn by using hardware like Raspberry Pi and Sensors (with extra payment)

Course Modules

Explore where AI is used in daily life and experience AI

  • Learn the basic concept of AI
  • Understand what is machine learning
  • Find out AI applications in daily life

Make an smart object recognition device with Computer Vision

  • Learn the basic concept and usage on computer vision
  • Learn how to use Una to connect Microsoft Azure Cognitive Services, Raspberry Pi devices and sensors
  • Through experiment, find out the relationship between different image effect and the accuracy of the AI analysis
  • Understand AI bias and learn how to use and protect data properly with focus on inclusiveness, privacy and security

Make smart face detection system to recognize facial appearance, distinguish boy and girl

  • Learn the principle and applications of face detection
  • Understand the JSON data result about the gender information
  • Learn how to count total number of boys and girls from AI result
  • Reflect and discuss the ethical problems in fairness, reliability and safety of face detection

Make a smart system to detect and recognize facial expressions, identify people’s inner feelings and outer feelings

  • Learn about facial expression recognition and detect the facial expression recognized
  • Understand facial expressions include multiple expressions, and each expression will display a confidence level
  • Write and assemble an AI system for calculating how many people in the image are happy
  • Learn that AI cannot truly recognize the inner feelings by facial expressions. AI results are based on the training data

Through face recognition experiment, analyse human’s facial feature and determine the similarity of two faces

  • Learn the principles and applications of face recognition, understand the JSON data result about similarity
  • Write a program that can analyze the similarity between two people
  • Understand the accountability of AI

Learn the characteristics of JSON data format, analyse the weather conditions

  • Learn different data types related to JSON data format
  • Learn how to read and use JSON data

Train an AI classification model by Google Teachable Machine and make a smart system to detect specific type of animal

  • Learn the fundamental of machine learning
  • Learn the fundamental of image classification
  • Use Google Teachable Machine to train an AI model and export the trained model to Raspberry Pi

Train an AI classification model by Google Teachable Machine and make a smart system to detect whether a human sit straight

  • Learn the fundamental of human pose detection
  • Learn how to use Google Teachable Machine to train the AI with photos in order to recognize poses
  • Understand the limitation of AI model

Train a smart recycling model by Google Teachable Machine

  • Learn the fundamental of supervised learning and how to prepare training data properly
  • Learn the concept of supervised learning
  • Learn how to improve the accuracy of the model

Train a better smart recycling model by Google Teachable Machine

  • Understand the requirements of training data
  • Learn advanced concept on supervised learning
  • Understand the difference between training data, testing data, and data inputted from the device

Explore where AI is used in daily life and experience AI

  • Learn the basic concept of AI
  • Understand what is machine learning
  • Find out AI applications in daily life

Make an smart object recognition device with Computer Vision

  • Learn the basic concept and usage on computer vision
  • Learn how to use Una to connect Microsoft Azure Cognitive Services, Raspberry Pi devices and sensors
  • Through experiment, find out the relationship between different image effect and the accuracy of the AI analysis
  • Understand AI bias and learn how to use and protect data properly with focus on inclusiveness, privacy and security

Make smart face detection system to recognize facial appearance, distinguish boy and girl

  • Learn the principle and applications of face detection
  • Understand the JSON data result about the gender information
  • Learn how to count total number of boys and girls from AI result
  • Reflect and discuss the ethical problems in fairness, reliability and safety of face detection

Make a smart system to detect and recognize facial expressions, identify people’s inner feelings and outer feelings

  • Learn about facial expression recognition and detect the facial expression recognized
  • Understand facial expressions include multiple expressions, and each expression will display a confidence level
  • Write and assemble an AI system for calculating how many people in the image are happy
  • Learn that AI cannot truly recognize the inner feelings by facial expressions. AI results are based on the training data

Through face recognition experiment, analyse human’s facial feature and determine the similarity of two faces

  • Learn the principles and applications of face recognition, understand the JSON data result about similarity
  • Write a program that can analyze the similarity between two people
  • Understand the accountability of AI

Learn the characteristics of JSON data format, analyse the weather conditions

  • Learn different data types related to JSON data format
  • Learn how to read and use JSON data

Train an AI classification model by Google Teachable Machine and make a smart system to detect specific type of animal

  • Learn the fundamental of machine learning
  • Learn the fundamental of image classification
  • Use Google Teachable Machine to train an AI model and export the trained model to Raspberry Pi

Train an AI classification model by Google Teachable Machine and make a smart system to detect whether a human sit straight

  • Learn the fundamental of human pose detection
  • Learn how to use Google Teachable Machine to train the AI with photos in order to recognize poses
  • Understand the limitation of AI model

Train a smart recycling model by Google Teachable Machine

  • Learn the fundamental of supervised learning and how to prepare training data properly
  • Learn the concept of supervised learning
  • Learn how to improve the accuracy of the model

Train a better smart recycling model by Google Teachable Machine

  • Understand the requirements of training data
  • Learn advanced concept on supervised learning
  • Understand the difference between training data, testing data, and data inputted from the device

Microsoft AI-900 Materials

Describe Artificial Intelligence General Usage and Workloads

  • Introduction of Microsoft AI-900 Certificate
  • What is AI?
  • Understand machine learning
  • Understand anomaly detection
  • Understand computer vision
  • Understand natural language processing
  • Understand conversation AI

Describe fundamental principles of machine learning

  • Machine Learning
  • Regression Model
  • Classification Model
  • Clustering Model

Describe features of computer vision workloads on Azure

  • Computer vision
  • Image analysis
  • Image classification
  • Object detection
  • Face analysis
  • Optical character recognition (OCR)
  • Receipt analysis

Describe features of Natural Language Processing (NLP) workloads on Azure

  • Natural Language Processing and its applications
  • Overview of Text Analytics
  • Language detection
  • Sentiment analysis
  • Key phrase extraction
  • Entity recognition
  • Overview of Speech Recognition and Synthesis
  • Speech-to-text
  • Text-to-speech
  • Translation
  • Language Understanding Intelligent Service (LUIS)

Describe features of Conversational AI workloads on Azure

  • Conversational AI Concepts
  • QnA Maker Service
  • Azure Bot Service

Describe Artificial Intelligence considerations

  • Challenges and Risks with AI
  • Principles of Responsible AI

Describe Artificial Intelligence General Usage and Workloads

  • Introduction of Microsoft AI-900 Certificate
  • What is AI?
  • Understand machine learning
  • Understand anomaly detection
  • Understand computer vision
  • Understand natural language processing
  • Understand conversation AI

Describe fundamental principles of machine learning

  • Machine Learning
  • Regression Model
  • Classification Model
  • Clustering Model

Describe features of computer vision workloads on Azure

  • Computer vision
  • Image analysis
  • Image classification
  • Object detection
  • Face analysis
  • Optical character recognition (OCR)
  • Receipt analysis

Describe features of Natural Language Processing (NLP) workloads on Azure

  • Natural Language Processing and its applications
  • Overview of Text Analytics
  • Language detection
  • Sentiment analysis
  • Key phrase extraction
  • Entity recognition
  • Overview of Speech Recognition and Synthesis
  • Speech-to-text
  • Text-to-speech
  • Translation
  • Language Understanding Intelligent Service (LUIS)

Describe features of Conversational AI workloads on Azure

  • Conversational AI Concepts
  • QnA Maker Service
  • Azure Bot Service

Describe Artificial Intelligence considerations

  • Challenges and Risks with AI
  • Principles of Responsible AI