Special Topic - AI Financial Application Course

AI4kids cooperated with the team of Professor Tsai Chih-hsiao from Taipei University of Education to record audio-visual teaching.
Through online learning, you can step into the cross-field practical courses of AI and finance step by step!

This course provides a preview of some chapters and units. You are welcome to watch and learn first before deciding whether to purchase the full course!

What you will learn in this online course

Introduction to AI finance, historical stock price data, AI prediction of stock price fluctuations, AI prediction of stock prices, prediction models and investment strategies.

【Teacher Introduction】

National Taipei University of Education Professor Tsai Chih-hsiao

Professor Cai Zhixiao's main research directions include online learning, educational assessment, learning analysis and mining, etc. He has participated in many research projects related to educational technology, published many academic papers in related fields, served as an editorial board member and reviewer for many domestic and foreign academic journals, and won many honors and awards in educational technology. Currently, we are also actively engaged in research in the field of AI finance, using technologies such as data mining and machine learning to apply data in the financial field.

【Detailed chapter content】

Chapter 1 Introduction to AI Finance
1-1 Basic Concepts of Investment
*Financial management and investment
*Understand the Taiwan stock market
*Investment mentality and strategy
1-2 Current Development of AI in the Financial Field
*AI technology in the financial sector
*Customer management: customer service robot
*Data analysis: investment recommendation system

Chapter 2 Historical Stock Price Information
2-1 Obtaining training data
* Obtain information from Taiwan Stock Exchange
*Information obtained through FinMind
2-2 Data Preprocessing
*Purpose of data pre-processing
*Financial data characteristics
*Pretreatment method
*Hands-on: Data pre-processing (Apple stock price data)

Chapter 3 AI predicts stock price fluctuations (classification task)
3-1 Using Machine Learning: Random Forest
*Model Introduction
*Hands-on practice: Using RF to predict TSMC's future price fluctuations
3-2 Using Machine Learning: SVM
*Model Introduction
*Hands-on practice: Use SVM to predict the rise and fall of TSMC tomorrow
3-3 Using Machine Learning: XGBoost
*Model Introduction
*Hands-on practice: Use XGBoost to predict TSMC's price rise or fall tomorrow
3-4 Using Deep Learning: LSTM
*Model Introduction
*Hands-on practice: Use LSTM to predict TSMC's future price increase or decrease

Chapter 4 AI predicts stock prices (regression task)
4-1 Using Machine Learning: Lasso Regression
* Model Introduction
* Hands-on practice: Use LR to predict the stock price of 0050 one week later
4-2 Using Machine Learning: Ridge Regression
* Model Introduction
* Hands-on practice: Use RR to predict the stock price of 0050 one week later
4-3 Using Machine Learning: SVR
* Model Introduction
* Hands-on practice: Use SVR to predict the stock price of 0050 one week later
4-4 Using Deep Learning: GRU
* Model Introduction
* Hands-on practice: Use GRU to predict the stock price of 0050 one week later

Chapter 5 Forecast Model and Investment Strategy
5-1 Single-day forecast
* Hands-on practice: tomorrow's stock price rise or fall, stock price in a week

Chapter 6 Assessment and Exercises
6-1 Self-operation practice: Please use XGBoost to build a model to predict the stock price rise and fall of Largan Precision (3008) in five days
6-2 Self-operation exercise: Please use GRU to establish a stock price prediction model for Hon Hai (2317) three days later
6-3 Overall evaluation

Total course time: 5:22:17
Number of classes: 6

Assessment <br>Assessment question types: multiple choice, true or false questions Number of assessment questions: 18 questions

Verification certificate

The certification certificate can be uploaded to the Ministry of Education's learning process platform .<br>The steps are as follows:
Log in to the learning history upload page → Multiple learning performance → Certification record → Domestic / Other / iQiyi Smart Technology / Certificate name (please select the test name) / Level score / Certificate code (please refer to the list below) → Upload supporting documents