This course provides an in-depth exploration of financial technology (FinTech) and artificial intelligence (AI) programming in the context of the finance industry. Students will learn essential programming skills in Python and how to apply them to various financial tasks such as data visualization, web scraping, machine learning, and deep learning. The course covers topics such as data preprocessing, supervised and unsupervised learning techniques, natural language processing (NLP), and text analysis. By the end of the course, students will have the knowledge and skills to analyze financial data using AI-related techniques.This course provides an in-depth exploration of financial technology (FinTech) and artificial intelligence (AI) programming in the context of the finance industry. Students will learn essential programming skills in Python and how to apply them to various financial tasks such as data visualization , web scraping, machine learning, and deep learning. The course covers topics such as data preprocessing, supervised and unsupervised learning techniques, natural language processing (NLP), and text analysis. By the end of the course, students will have the knowledge and skills to analyze financial data using AI-related techniques.
1. AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning 1st Edition, Tobias Zwingmann (Author), 2022.
2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 2nd Edition, Geron Aurelien (Author), 2019.
3. Machine Learning For Absolute Beginners, Oliver Theobald (Author), 2017.
1. AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning 1st Edition, Tobias Zwingmann (Author), 2022.
2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 2nd Edition, Geron Aurelien (Author), 2019.
3. Machine Learning For Absolute Beginners, Oliver Theobald (Author), 2017.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| Class ParticipationClass Participation class participation |
20 | |
| In-class assignmentsIn-class assignments in-class assignments |
25 | |
| Midterm ExamMidterm Exam midterm exam |
25 | |
| Final ReportFinal Report final report |
30 |
