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