國外小組科研—金融與商業(yè)分析專題：人工智能下的量化金融與金融科技---機器學習在商業(yè)數(shù)據(jù)分析和股票市場預(yù)測中的應(yīng)用

開始日期：

2023年8月12日

專業(yè)方向：

金融商科

導師：

Patrick（牛津大學 University of Oxford 終身教授）

課程周期：

7周在線小組科研學習+5周不限時論文指導學習

語言：

英文

建議學生年級：

大學生 高中生

項目產(chǎn)出：

7周在線小組科研學習+5周不限時論文指導學習 共125課時 項目報告 優(yōu)秀學員獲主導師Reference Letter EI/CPCI/Scopus/ProQuest/Crossref/EBSCO或同等級別索引國際會議全文投遞與發(fā)表指導（可用于申請） 結(jié)業(yè)證書 成績單

項目介紹：

2017年，摩根大通發(fā)布了一份題為《大數(shù)據(jù)與人工智能戰(zhàn)略：機器學習和其它投資數(shù)據(jù)分析方法》的報告，對機器學習對金融領(lǐng)域的影響進行了全面的闡述，昭示著機器學習已經(jīng)敲開金融領(lǐng)域和商業(yè)數(shù)據(jù)分析的大門。機器學習是什么？如何與商業(yè)分析相結(jié)合？項目將通過介紹兩種非常實用的商業(yè)分析工具，即Python編程語言和機器學習工具包，幫助學生厘清上述問題的答案。學生將著重了解機器學習在商業(yè)分析股市預(yù)測中的應(yīng)用，利用機器學習分析市場數(shù)據(jù)解決商業(yè)問題。該項目內(nèi)容包括機器學習與數(shù)據(jù)科學概論、商業(yè)分析中市場數(shù)據(jù)處理的機器學習技術(shù)與算法、Python與Jupiter notebooks交互式學習、機器學習庫、股市預(yù)測等。學生將在項目中學習如何使用機器學習完成商業(yè)市場數(shù)據(jù)分析，進行股市預(yù)測，在項目結(jié)束時，提交項目報告，進行成果展示。 In 2017, JPMorgan Chase released a report entitled Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing, which comprehensively elaborated the impact of machine learning on the financial sector, showing that machine learning has been introduced into the financial sector and business data analysis. What is machine learning? How to integrate it with business analysis? The program will help students clarify the answers to the above questions by introducing two useful business analysis tools, the Python programming language, and the machine learning toolkit. Students will focus on the application of machine learning in business analysis and stock market forecast, and use machine learning to analyze market data to solve business problems. The program covers an introduction to machine learning and data science, machine learning techniques and algorithms on market data processing in business analysis, interactive learning with Python and Jupiter notebooks, libraries for machine learning, and predicting the stock market. During the program, students will learn how to use machine learning to complete market data analysis, predict the stock market, and at the end of the program, submit a project report and present the results.