Microsoft Python x AI Online Training Course

Students can take our courses which incorporate Microsoft textbook elements to learn about Python 3 basic programming and data analysis. Students will apply their mathematical and statistic knowledge to make different AI applications.  

*All courses must be completed within one year 

  1. Training fee: HKD 350 x 12 hours = HKD 4,200
  2. Subscription/ Teaching material fee: HKD 80 (yearly)
  3. Azure Credit: HKD 300
  4. Hardware fee: /

Total: HKD 4,580 

HKD 4,580
(USD 603)

What you will learn

Are you suitable for this course?

Remarks:

Course Content

Understand what it AI and how to use Microsoft Azure

  • Learn the basic concept of AI
  • Explore Azure portal and create Azure machine learning studio service
  • Explore the features of Azure machine learning studio
  • Learn about python notebook

Refresh Python knowledge

  • Variable and operators
  • Conditional statement
  • Loop statement
  • Function
  • Class & Object

Understand the basic concept of data in AI

  • Learn about the data preparation process: Feature selection, Cleaning the outlier, Handing missing value, Feature engineering, Data normalization
  • Basic of data manipulation libraries (NumPy and Pandas)

Understand the basic statistic in AI

  • Learn the basic concept of statistic
  • Learn different fundamental graphical methods of data analysis: Scatter Plots, Line Graphs, Bar Charts, and Histograms
  • Study categorical, numerical distributions and their difference

Learn how to use regression to predict numeric values and understand how various parameters can optimise prediction accuracy

  • Learn what is regression and when to use it
  • Train and evaluate regression models using the Scikit-Learn framework

Learn how to categorize items into classes in machine learning and how to evaluate classification model

  • Learn what is classification and when to use it
  • Train and evaluate a classification model using the Scikit-Learn framework

Learn how to apply clustering model and understand its principles in grouping similar items into clusters in machine learning

  • Learn what is Clustering and when to use it
  • Train and evaluate a clustering model using the scikit-learn framework

Learn basic principles of deep learning and train a deep neural network (DNN) using PyTorch or Tensorflow

  • Learn what is Neural Network(NN) and Deep Neural Network(DNN)
  • Train a model using Neural Network Algorithm

Use transfer learning to train a convolutional neural network (CNN) with PyTorch or Tensorflow

  • Learn what is convolutional neural network (CNN)
  • Use transfer learning to train an image classification model

Understand what it AI and how to use Microsoft Azure

  • Learn the basic concept of AI
  • Explore Azure portal and create Azure machine learning studio service
  • Explore the features of Azure machine learning studio
  • Learn about python notebook

Refresh Python knowledge

  • Variable and operators
  • Conditional statement
  • Loop statement
  • Function
  • Class & Object

Understand the basic concept of data in AI

  • Learn about the data preparation process: Feature selection, Cleaning the outlier, Handing missing value, Feature engineering, Data normalization
  • Basic of data manipulation libraries (NumPy and Pandas)

Understand the basic statistic in AI

  • Learn the basic concept of statistic
  • Learn different fundamental graphical methods of data analysis: Scatter Plots, Line Graphs, Bar Charts, and Histograms
  • Study categorical, numerical distributions and their difference

Learn how to use regression to predict numeric values and understand how various parameters can optimise prediction accuracy

  • Learn what is regression and when to use it
  • Train and evaluate regression models using the Scikit-Learn framework

Learn how to categorize items into classes in machine learning and how to evaluate classification model

  • Learn what is classification and when to use it
  • Train and evaluate a classification model using the Scikit-Learn framework

Learn how to apply clustering model and understand its principles in grouping similar items into clusters in machine learning

  • Learn what is Clustering and when to use it
  • Train and evaluate a clustering model using the scikit-learn framework

Learn basic principles of deep learning and train a deep neural network (DNN) using PyTorch or Tensorflow

  • Learn what is Neural Network(NN) and Deep Neural Network(DNN)
  • Train a model using Neural Network Algorithm

Use transfer learning to train a convolutional neural network (CNN) with PyTorch or Tensorflow

  • Learn what is convolutional neural network (CNN)
  • Use transfer learning to train an image classification model

Feedback

Mr Tse Wai Tak
Mr Tse Wai TakScience and Physics teacher of St. Paul's Co-educational College
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Una did a great job at constructing the course structure. Even the teaching materials are considered challenging compared with the student’s level, students can still keep up with the learning progress, grasp the coding logic of Python and the fundamental AI concepts under Una tutor’s instructions.
Student
Student St. Paul's Co-educational College
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The rich teaching materials and practical examples provided by Una teachers make us understand how Python and AI work. I am more confident to learn advanced levels of Python and AI after I complete the course. I believe the skill I gained would be beneficial in the future if I apply for a tech-related job.
Ms Lau Oi Ha
Ms Lau Oi Ha Head of science; Science and biology teachers of St. Paul's Co-educational College
Read More
Teachers from Una are good at explaining challenging coding concepts to students in a clear, exciting and vivid manner. Therefore, students are willing to learn despite the seemingly complicated content.
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Microsoft Python x AI Online Training Course

HKD 4,580 (USD 603)

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