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AI Maker 2.0 Online Training Course

By using blocks coding, this course introduces students to AI concepts, limitations and responsibilities. Students will apply different AI technologies and train AI models using Microsoft Azure cognitive service and Google Teachable Machine. 

  • 10 hours 1-on-1 real-time teaching by Una’s tutor
  • AI Maker Courses & Exercises (1-year)
  • AI Maker Student 1-year Subscription Plan
  • 1-year Priority Support
  1. Training fee: HKD 220 x 10 hours = HKD 2,200
  2. Subscription/ Teaching material fee: HKD 280 (yearly)
  3. Hardware fee: /

Total: HKD 2,480 

HKD 2,480
(USD 326)

Book Online Free Trial
Book Online Free Trial
Inquiry / Buy Now
Inquiry / Buy Now
Inquiry of face-to-face courses at SCHOOL

From this course, you will learn…

  • Learn AI concepts, limitations and responsibilities
  • Learn the basics of machine learning
  • Use Microsoft Azure Cognitive Service, apply various AI technologies and code with Una AI Web App
  • Use Google Teachable Machine, train multiple AI classification models and code with Una AI Web App

This course is suitable for…

  • Age 8+
  • No coding background needed

Remake:

  • No hardware requirement and learn with WebApp
  • All courses must be completed within one year 

Course Content

Understand the basic concept of AI

  • Understand what Artificial Intelligence is
  • Find out the AI in our daily lives
  • Introduce the idea of AI training

Hands-on: Play QuickDraw and AI image generator to experience learning capability of AI

Understand How AI detects objects

  • Introduce types of Computer Vision AI
  • Understand data augmentation and how different factors will affect confidence of AI

Hands-on: Experience Azure Object detection through Una Platform

Learn how to use AI to classify items

  • Try out the image classification of the GTM (Google Teachable Machine)
  • Learn the limits of AI and how can we improve a classification model through feature selection

Hands-on: Try out Google Teachable Machine’s to train an image Classification model

Introduce the principle of facial analysis

  • Understand how AI can learn faces through facial features
  • Learn the common use of facial analysis and facial verification in our daily life

Hands-on: Experience Azure Facial detection and verification through Una Platform

Understand how speech conversion is achieved

  • Learn what Text to Speech and Speech to Text are
  • Understand how AI recognise and synthesise speech

Hands-on: Experience Azure Speech services through Una Platform

Learn the basic principle of Pose detection

  • Learn real life examples of pose detection technologies
  • Learn limitations and capability of pose detection

Hands-on: Try out Google Teachable Machine- to train a pose recognition model

Introduce Conversational AI and

  • Learn the advancement in Chatbot through hands-on exercises
  • Learn to enhance the efficiency of using AI for text analytics

Hands-on: Interaction with ChatGPT POE and understand how to control output with prompts

Understand Machine Learning through creating a classification model

  • Introduce Features and Label in Training data
  • Learn types of algorithms used in Machine Learning

Hands-on: Experience how to train a classification model to classify diabetic cases through Una ML Platform

Understand Machine Learning through data preparation

  • Learn to observe the pattern in AI predicted result
  • Learn ways of data analysis

Hands-on: Experience how to train a regression model and evaluate model performance through Una ML Platform

Reflect on the ethics of using AI through real life cases

  • Investigate potential problems brought by the using of AI to understand the significance of righteous use of AI
  • Case study the real-life issues created by AI
  • Develop the proper attitude of using AI

Understand the basic concept of AI

  • Understand what Artificial Intelligence is
  • Find out the AI in our daily lives
  • Introduce the idea of AI training

Hands-on: Play QuickDraw and AI image generator to experience learning capability of AI

Understand How AI detects objects

  • Introduce types of Computer Vision AI
  • Understand data augmentation and how different factors will affect confidence of AI

Hands-on: Experience Azure Object detection through Una Platform

Learn how to use AI to classify items

  • Try out the image classification of the GTM (Google Teachable Machine)
  • Learn the limits of AI and how can we improve a classification model through feature selection

Hands-on: Try out Google Teachable Machine’s to train an image Classification model

Introduce the principle of facial analysis

  • Understand how AI can learn faces through facial features
  • Learn the common use of facial analysis and facial verification in our daily life

Hands-on: Experience Azure Facial detection and verification through Una Platform

Understand how speech conversion is achieved

  • Learn what Text to Speech and Speech to Text are
  • Understand how AI recognise and synthesise speech

Hands-on: Experience Azure Speech services through Una Platform

Learn the basic principle of Pose detection

  • Learn real life examples of pose detection technologies
  • Learn limitations and capability of pose detection

Hands-on: Try out Google Teachable Machine- to train a pose recognition model

Introduce Conversational AI and

  • Learn the advancement in Chatbot through hands-on exercises
  • Learn to enhance the efficiency of using AI for text analytics

Hands-on: Interaction with ChatGPT POE and understand how to control output with prompts

Understand Machine Learning through creating a classification model

  • Introduce Features and Label in Training data
  • Learn types of algorithms used in Machine Learning

Hands-on: Experience how to train a classification model to classify diabetic cases through Una ML Platform

Understand Machine Learning through data preparation

  • Learn to observe the pattern in AI predicted result
  • Learn ways of data analysis

Hands-on: Experience how to train a regression model and evaluate model performance through Una ML Platform

Reflect on the ethics of using AI through real life cases

  • Investigate potential problems brought by the using of AI to understand the significance of righteous use of AI
  • Case study the real-life issues created by AI
  • Develop the proper attitude of using AI

Include Raspberry Pi (Optional- Hardware: Raspberry Pi and sensor)

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

Feedback

Mr Jimmy Chan
Mr Jimmy Chan Vice Chairman of Council of the Hong Kong Association for Computer Education (HKACE) and Head of IT committee of SKH Li Fook Hing Secondary School
Read More
Under the pandemic, the Una platform allows students to participate in online lessons interactively, collaboratively and learn AI continuously at home. It is surprising that students can even test the coding result through a Raspberry Pi remotely. As a teacher, I appreciate the clear learning objectives and the comprehensive assessments to review what students have learned. Like!
Mr Jonathan Yau
Mr Jonathan Yau STEM Education Coordinator of Lam Tai Fai College
Read More
I am a science teacher without IT background, but Una helps me to conduct AI courses efficiently and solves problems encountered by teachers before, during and after class.
Mr Chris Yuen
Mr Chris Yuen Teacher of Alliance Cheng Wing Gee College
Read More
During the teaching process, I hope students can learn to connect AI concepts in real life. After using Una Platform, students can solve the problem as teams and grasp related concepts step by step.
Mr Chan Wing-Tak
Mr Chan Wing-TakIT Coordinator of Ko Lui Secondary School
Read More
Una provides AI courses with interesting topics and their learning platform’s interface is user-friendly. Also, trainers from Una have a great attitude and can effectively maintain a positive learning atmosphere.
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FAQ

Students need to login both Microsoft Teams and Una Platform for learning and coding, but it is unnecessary to use the same device.

  1. Microsoft Teams: Please download Microsoft Teams here and find out the detail of device requirements.
  2. Una Platform: Student can login Una with an internet-accessible computer, laptop or iPad, using Google Chrome or Microsoft Edge up-to-date browsers.

Important Notes for Login Una:

  1. Smartphone is not supported
  2. For iPad users, it requires iPadOS 14.5 or above
  3. Login with computer or laptop, using normal mode on the browser (NOT Incognito Mode), can enjoy a better user experience
  1. When we receive your registration, we will send you Una Platform login instruction.
  2. Once you receive login instruction, before the class, please visit https://app.una.study/ and see if you can login Una successfully. Otherwise, please change your device or update your browser prior class to ensure we can start the lesson on time and smoothly.

AI Maker 2.0 Online Training Course

  • 10 hours 1-on-1 real-time teaching by Una’s tutor
  • AI Maker Courses & Exercises (1-year)
  • AI Maker Student 1-year Subscription Plan
  • 1-year Priority Support

HKD 2,480 (USD 326)

Book Online Free Trial
Book Online Free Trial
Inquiry / Buy Now
Inquiry / Buy Now

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