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Una AI Maker x Microsoft AI-900 Online Training Course

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. Students can take the Microsoft AI-900 Certificate Exam under a passing guarantee, which the pass rate up to 98%. 

*All courses must be completed within one year 

  • 20 hours 1-on-1 real-time teaching by Una’s tutor
  • Una AI Maker Courses (1-year)
  • Microsoft AI-900 Intensive Course (1-year)
  • Microsoft AI-900 Exam Voucher for one
  • Passing Guarantee
  • Una AI Maker Student 1-year Subscription Plan
  • 1-year Priority Support
Pass Guarantee

  1. Training fee: HKD 285 x 20 hours = HKD 5,700 

  2. Subscription/ Teaching material fee: HKD 280 (yearly)

  3. Exam Voucher (handling fee included): HKD 635 (per one)

  4. Hardware fee: / 

Total: HKD 6,615

HKD 6,615
(USD 870)

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

What 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
  • Obtain the globally recognized Microsoft AI-900 Certificate
More detail of Microsoft Certified

Are you suitable for this course?

  • Age 10+
  • No coding background needed

Remarks:

  • If you have already enrolled in the AI Maker course, you can directly join the AI-900 course
  • No hardware requirement and learn with WebApp
  • Students can learn by using hardware like Raspberry Pi and Sensors (with extra payment)
  • Complete the exam at Una Office

Course Content

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

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

Feedback

Sing Hymm
Sing HymmStudent (13 years old)
Read More
During the study journey, I realized AI is not limited to applications like Siri and I gained more insights and knowledge about AI. The natural language processing function of AI, which can detect human emotions from text, is the most impressive AI feature I came across during this course. I genuinely think this learning experience is meaningful and exciting. Lastly, I really appreciate the guidance from Una’s teacher!
Michael Lai
Michael LaiStudent
Read More
This course can strengthen my knowledge of AI. Also, the teaching content is interesting, especially the coding part. Although the exam material is a bit challenging, I can still pass the AI-900 exam thanks to the detailed elaboration from the teachers. I will continue to strive for improvement in the AI and coding areas.
Mr Lai
Mr LaiParent of Michael Lai
Read More
This course is a bit challenging for Primary school students. But the rich and powerful teaching content is beneficial for my boy to understand AI's fundamental concept easily. Thanks for the effective teaching from Una's teacher!
Wilfred
WilfredStudent (11 years old)
Read More
I really enjoyed the class because I learned a lot of things about AI. Moreover, the teachers were immensely kind, helpful and accommodating! Overall, I really enjoyed the course. It was fun and amazing!
Ms Leung
Ms LeungParent of Toto (12 years old)
Read More
Thanks for the heartwarming attention and care from all the teachers and Una’s team! Because of the heartfelt teaching by the teacher, my son is able to achieve his ideal exam score. In this tech-oriented world, he will try his best to learn more. And hopefully, Una’s teacher can continue to teach excellent students in the future!
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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.

Una AI Maker x Microsoft AI-900 Online Training Course

  • 20 hours 1-on-1 real-time teaching by Una’s tutor
  • Una AI Maker Courses (1-year)
  • Microsoft AI-900 Intensive Course (1-year)
  • Microsoft AI-900 Exam Voucher for one
  • Passing Guarantee
  • Una AI Maker Student 1-year Subscription Plan
  • 1-year Priority Support

HKD 6,615 (USD 870)

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

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