國(guó)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(jī)器學(xué)習(xí)在商業(yè)數(shù)據(jù)分析和股票市場(chǎng)預(yù)測(cè)中的應(yīng)用 余1席

開始日期：

2023年6月24日

專業(yè)方向：

金融商科

導(dǎo)師：

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

課程周期：

7周在線小組科研學(xué)習(xí)+5周不限時(shí)論文指導(dǎo)學(xué)習(xí)

語言：

英文

建議學(xué)生年級(jí)：

大學(xué)生 高中生

項(xiàng)目產(chǎn)出：

7周在線小組科研學(xué)習(xí)+5周不限時(shí)論文指導(dǎo)學(xué)習(xí) 共125課時(shí) 項(xiàng)目報(bào)告 優(yōu)秀學(xué)員獲主導(dǎo)師Reference Letter EI/CPCI/Scopus/ProQuest/Crossref/EBSCO或同等級(jí)別索引國(guó)際會(huì)議全文投遞與發(fā)表指導(dǎo)（可用于申請(qǐng)） 結(jié)業(yè)證書 成績(jī)單

項(xiàng)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(jī)器學(xué)習(xí)和其它投資數(shù)據(jù)分析方法》的報(bào)告，對(duì)機(jī)器學(xué)習(xí)對(duì)金融領(lǐng)域的影響進(jìn)行了全面的闡述，昭示著機(jī)器學(xué)習(xí)已經(jīng)敲開金融領(lǐng)域和商業(yè)數(shù)據(jù)分析的大門。機(jī)器學(xué)習(xí)是什么？如何與商業(yè)分析相結(jié)合？項(xiàng)目將通過介紹兩種非常實(shí)用的商業(yè)分析工具，即Python編程語言和機(jī)器學(xué)習(xí)工具包，幫助學(xué)生厘清上述問題的答案。學(xué)生將著重了解機(jī)器學(xué)習(xí)在商業(yè)分析股市預(yù)測(cè)中的應(yīng)用，利用機(jī)器學(xué)習(xí)分析市場(chǎng)數(shù)據(jù)解決商業(yè)問題。該項(xiàng)目?jī)?nèi)容包括機(jī)器學(xué)習(xí)與數(shù)據(jù)科學(xué)概論、商業(yè)分析中市場(chǎng)數(shù)據(jù)處理的機(jī)器學(xué)習(xí)技術(shù)與算法、Python與Jupiter notebooks交互式學(xué)習(xí)、機(jī)器學(xué)習(xí)庫(kù)、股市預(yù)測(cè)等。學(xué)生將在項(xiàng)目中學(xué)習(xí)如何使用機(jī)器學(xué)習(xí)完成商業(yè)市場(chǎng)數(shù)據(jù)分析，進(jìn)行股市預(yù)測(cè)，在項(xiàng)目結(jié)束時(shí)，提交項(xiàng)目報(bào)告，進(jìn)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.