2022級(jí)應(yīng)用統(tǒng)計(jì)專(zhuān)業(yè)學(xué)位碩士研究生培養(yǎng)方案
所屬學(xué)科門(mén)類(lèi)：
所屬一級(jí)學(xué)科：
所屬院系：統(tǒng)計(jì)與信息學(xué)院
應(yīng)用統(tǒng)計(jì)（025200）
本專(zhuān)業(yè)旨在培養(yǎng)德才兼?zhèn)?，具有家?guó)情懷和國(guó)際視野，具備良好的政治素質(zhì)與職業(yè)道德，系統(tǒng)掌握統(tǒng)計(jì)學(xué)的基本思想和收集、整理與分析數(shù)據(jù)的方法，并能根據(jù)應(yīng)用領(lǐng)域數(shù)據(jù)的特點(diǎn)選用恰當(dāng)?shù)慕y(tǒng)計(jì)方法進(jìn)行調(diào)查、分析、推斷和預(yù)測(cè)，熟練應(yīng)用統(tǒng)計(jì)軟件并具備一定的編程能力，能夠正確分析判斷和解釋統(tǒng)計(jì)軟件的計(jì)算結(jié)果，畢業(yè)后能夠在國(guó)家機(jī)關(guān)、經(jīng)貿(mào)金融類(lèi)企事業(yè)單位、咨詢(xún)企業(yè)及社會(huì)組織，從事統(tǒng)計(jì)調(diào)查、數(shù)據(jù)分析和決策支持等工作的高層次、應(yīng)用型統(tǒng)計(jì)專(zhuān)門(mén)人才。
二、學(xué)制
本專(zhuān)業(yè)學(xué)制為2年。在規(guī)定時(shí)期完成課程學(xué)習(xí)，但未完成學(xué)位論文者，可申請(qǐng)延長(zhǎng)學(xué)習(xí)年限，累計(jì)最長(zhǎng)年限不超過(guò)4年。
三、研究方向
1.數(shù)據(jù)科學(xué)與商務(wù)統(tǒng)計(jì)
2.大數(shù)據(jù)技術(shù)與貿(mào)易統(tǒng)計(jì)
3.金融科技與風(fēng)險(xiǎn)管理
4.人工智能與商務(wù)數(shù)據(jù)挖掘
四、課程設(shè)置與學(xué)分要求
本專(zhuān)業(yè)碩士研究生在攻讀碩士學(xué)位期間應(yīng)修滿(mǎn)38學(xué)分，其中包括公共必修課7學(xué)分，學(xué)位必修課13學(xué)分，方向選修課至少7學(xué)分，專(zhuān)業(yè)選修課至少2學(xué)分，跨專(zhuān)業(yè)選修課2學(xué)分，實(shí)踐教學(xué)7學(xué)分（含案例分析1學(xué)分，名師講座2學(xué)分，社會(huì)實(shí)踐4學(xué)分）。具體課程安排和學(xué)分見(jiàn)附表。
五、社會(huì)實(shí)踐
根據(jù)本專(zhuān)業(yè)的培養(yǎng)方案，要求學(xué)生在研究生期間參加一定的社會(huì)實(shí)踐，在政府及企事業(yè)單位的統(tǒng)計(jì)工作崗位實(shí)習(xí)實(shí)踐不少于半年，參與和完成一項(xiàng)社會(huì)實(shí)際統(tǒng)計(jì)調(diào)查或數(shù)據(jù)分析的實(shí)踐工作和實(shí)踐報(bào)告。同時(shí)，須將思想政治教育融入社會(huì)實(shí)踐，協(xié)同育人。
通過(guò)社會(huì)實(shí)踐，培養(yǎng)學(xué)生的實(shí)踐能力、分析問(wèn)題和解決問(wèn)題的能力以及綜合運(yùn)用所學(xué)基礎(chǔ)知識(shí)和基本技能的能力，同時(shí)也增強(qiáng)學(xué)生適應(yīng)社會(huì)的能力和就業(yè)競(jìng)爭(zhēng)力。
具體要求見(jiàn)《上海對(duì)外經(jīng)貿(mào)大學(xué)碩士研究生社會(huì)實(shí)踐實(shí)施細(xì)則》。
六、培養(yǎng)方式
應(yīng)用統(tǒng)計(jì)專(zhuān)業(yè)的課程均采取講授、討論和專(zhuān)題研究的方式進(jìn)行。對(duì)應(yīng)用統(tǒng)計(jì)專(zhuān)業(yè)研究生的培養(yǎng)實(shí)行雙導(dǎo)師制，其中一位導(dǎo)師來(lái)自培養(yǎng)單位，另一位導(dǎo)師來(lái)自與本領(lǐng)域相關(guān)的校外專(zhuān)家。
七、學(xué)位論文
學(xué)位論文在導(dǎo)師指導(dǎo)下，由碩士研究生本人按計(jì)劃進(jìn)度獨(dú)立完成。學(xué)位論文應(yīng)與實(shí)際問(wèn)題、實(shí)際數(shù)據(jù)和實(shí)際案例緊密結(jié)合，可采用與數(shù)據(jù)收集、整理、分析相關(guān)的數(shù)據(jù)分析報(bào)告、應(yīng)用統(tǒng)計(jì)方法的實(shí)證研究等形式。
應(yīng)用統(tǒng)計(jì)專(zhuān)業(yè)研究生的學(xué)位論文開(kāi)題報(bào)告應(yīng)在第2學(xué)期完成。學(xué)位論文的寫(xiě)作要求參照《上海市應(yīng)用統(tǒng)計(jì)碩士專(zhuān)業(yè)學(xué)位論文基本要求和評(píng)價(jià)指標(biāo)體系》和《上海對(duì)外經(jīng)貿(mào)大學(xué)碩士學(xué)位論文內(nèi)容和格式要求（2020年修訂）》。
修滿(mǎn)培養(yǎng)方案規(guī)定的學(xué)分、完成專(zhuān)業(yè)實(shí)習(xí)并通過(guò)學(xué)位論文答辯者，經(jīng)學(xué)位評(píng)定委員會(huì)審核，授予應(yīng)用統(tǒng)計(jì)碩士專(zhuān)業(yè)學(xué)位。
附表：
類(lèi)別 | 課程名稱(chēng) | 第1學(xué)期 | 第2學(xué)期 | 第3學(xué)期 | 學(xué)時(shí) | 學(xué)分 | 開(kāi)課部門(mén) |
公共 課 | 中國(guó)特色社會(huì)主義理論與實(shí)踐研究 | 2 | 36 | 2 | 馬克思主義學(xué)院 | ||
馬克思主義與社會(huì)科學(xué)方法論研究 | 1 | 18 | 1 | 馬克思主義學(xué)院 | |||
高級(jí)英語(yǔ)口語(yǔ)與寫(xiě)作 | 2 | 36 | 2 | 國(guó)際商務(wù)外語(yǔ)學(xué)院 | |||
統(tǒng)計(jì)軟件（英） | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
學(xué) 位 必 修 課 | 學(xué)術(shù)規(guī)范與論文寫(xiě)作 | 1 | 18 | 1 | 統(tǒng)計(jì)與信息學(xué)院 | ||
高等統(tǒng)計(jì)學(xué) | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
高級(jí)程序設(shè)計(jì) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
數(shù)據(jù)分析與統(tǒng)計(jì)建模 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
高級(jí)數(shù)據(jù)庫(kù)技術(shù) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
機(jī)器學(xué)習(xí) | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
方 向 選 修 課 | 數(shù)據(jù)科學(xué)與商務(wù)統(tǒng)計(jì)方向 | ||||||
統(tǒng)計(jì)計(jì)算* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
復(fù)雜數(shù)據(jù)統(tǒng)計(jì)分析* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
算法設(shè)計(jì)與實(shí)踐* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
商務(wù)大數(shù)據(jù)案例分析* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
優(yōu)化方法與數(shù)據(jù)分析實(shí)踐* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
大數(shù)據(jù)技術(shù)與貿(mào)易統(tǒng)計(jì)方向 | |||||||
高級(jí)計(jì)量經(jīng)濟(jì)學(xué)* | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
國(guó)民經(jīng)濟(jì)核算理論與方法 | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
國(guó)際貿(mào)易統(tǒng)計(jì) | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
全球價(jià)值鏈統(tǒng)計(jì) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
數(shù)據(jù)科學(xué)技術(shù)與應(yīng)用* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
金融科技與風(fēng)險(xiǎn)管理方向 | |||||||
金融計(jì)量學(xué)* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
金融工程* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
數(shù)理金融* | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
金融科技專(zhuān)題選講* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
算法設(shè)計(jì)與實(shí)踐* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
人工智能與商務(wù)數(shù)據(jù)挖掘方向 | |||||||
算法導(dǎo)論* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
文本挖掘技術(shù)* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
分布式計(jì)算* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
計(jì)算機(jī)視覺(jué)* | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
深度學(xué)習(xí)* | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
專(zhuān)業(yè)選修課 | 統(tǒng)計(jì)學(xué)前沿文獻(xiàn)導(dǎo)讀 | 1 | 18 | 1 | 統(tǒng)計(jì)與信息學(xué)院 | ||
貝葉斯統(tǒng)計(jì) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
非參數(shù)統(tǒng)計(jì) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
多元統(tǒng)計(jì)分析 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
廣義線(xiàn)性及混合效應(yīng)模型（英） | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
試驗(yàn)設(shè)計(jì)與建模 |
| 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | ||
國(guó)際貿(mào)易統(tǒng)計(jì)調(diào)查 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
經(jīng)濟(jì)數(shù)據(jù)挖掘與量化研究 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | ||||
高頻數(shù)據(jù)與量化交易 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
時(shí)空統(tǒng)計(jì)理論及應(yīng)用 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
高級(jí)計(jì)量經(jīng)濟(jì)學(xué)（II） | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
隨機(jī)過(guò)程 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
數(shù)據(jù)挖掘 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
管理決策理論與方法 | 3 | 54 | 3 | 統(tǒng)計(jì)與信息學(xué)院 | |||
博弈論 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
Android移動(dòng)應(yīng)用開(kāi)發(fā) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
互聯(lián)網(wǎng)前沿技術(shù)創(chuàng)新應(yīng)用案例 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
強(qiáng)化學(xué)習(xí)基礎(chǔ) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
復(fù)雜系統(tǒng)與復(fù)雜網(wǎng)絡(luò) | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
跨專(zhuān)業(yè)選修課 | 服務(wù)貿(mào)易與全球價(jià)值鏈 | 2 | 36 | 2 | 貿(mào)易談判學(xué)院 | ||
可拓學(xué)專(zhuān)題 | 2 | 36 | 2 | 統(tǒng)計(jì)與信息學(xué)院 | |||
市場(chǎng)營(yíng)銷(xiāo)專(zhuān)題 | 2 | 36 | 2 | 工商管理學(xué)院 | |||
心理與行為研究方法 | 2 | 36 | 2 | 工商管理學(xué)院 | |||
企業(yè)與公司法 | 2 | 36 | 2 | 法學(xué)院 | |||
財(cái)務(wù)管理研究 | 2 | 36 | 2 | 會(huì)計(jì)學(xué)院 | |||
公司金融研究 | 2 | 36 | 2 | 金融管理學(xué)院 | |||
創(chuàng)業(yè)管理 | 2 | 36 | 2 | 工商管理學(xué)院 | |||
國(guó)際貿(mào)易實(shí)務(wù) | 2 | 36 | 2 | 國(guó)際經(jīng)貿(mào)學(xué)院 | |||
金融風(fēng)險(xiǎn)管理 | 2 | 36 | 2 | 金融管理學(xué)院 | |||
實(shí)踐教學(xué)環(huán)節(jié) | 案例分析 | 1 | 18 | 1 | |||
名師講座 | 8次 | 2 | |||||
社會(huì)實(shí)踐 | 4 | ||||||
注：加*方向選修課亦可作為其他方向?qū)I(yè)選修課。 | |||||||
Masterin Applied Statistics Program（2022）
Field:Statistics：
Discipline:
School:School of Statistics
AppliedStatistics（025200）
I.Objectives
Thismajor aims to cultivate both ability and political integrity, withfamily and country feelings and international vision, with goodpolitical quality and professional ethics, systematic mastery of thebasic ideas of statistics and methods of collecting, collating andanalyzing data, and can choose appropriate statistical methods forinvestigation, analysis, inference and prediction according to thecharacteristics of data in the field of application, skilledapplication of statistical software and have certain programmingability, can correctly analyze and judge and interpret thecalculation results of statistical software, and can be in stateorgans after graduation. High-level and application-orientedstatistical professionals engaged in statistical surveys, dataanalysis and decision support, economic, trade and financialenterprises, consulting enterprises and social organizations.
Ⅱ.Duration of the Program
Thefull-time student of this major is 2 years. Those who have completedthe course study within the prescribed period, but have not completedthe degree thesis, may apply to extend the study period. The maximumcumulative years of study is 4 years.
Ⅲ.Research Areas
1.Data Science and Business Statistics
2.Big Data Technology andTrade Statistics
3.Financial Technology andRisk Management
4.Artificial Intelligenceand Business Data Mining
Ⅳ.Courses and Credits
Duringthe master's degree, the students should complete 38 credits,including 7 credits for common required courses, 13 credits forrequired courses, at least 7 credits for direction elective courses,at least 2 credits for major elective courses, 2 credits forcross-specialty courses, 7 credits for practical teaching (including1 credit for case analysis, 2 credits for lectures, 4 credits forsocial practice). See the attached table for the specific coursearrangement and credits.
Ⅴ.Social Practice
Accordingto the training objectives of this major, students are required toparticipate in certain social practices during postgraduate period,and practice in the statistical work positions of the government,enterprises and institutions for no less than half a year,participate in and complete the practical work and report of a socialactual statistical survey or data analysis. At the same time, we mustintegrate ideological and political education into social practiceand educate people cooperatively.
Throughsocial practice, students' practical ability, problem-analyzing andproblem-solving skills, and the ability to comprehensively using thebasic knowledge and basic skills learned are also cultivated. At thesame time, students' ability to adapt to society and employmentcompetitiveness are also enhanced.
Forspecific requirements, please refer to the Detailed Rules for “theImplementation of social practice for master's degree students ofShanghai University of International Business and Economics”.
VI.Education Modes
Thecourses of applied statistics are all finished in the patterns oflecture, discussion and research in the selected topics. A dual tutorsystem is implemented for the cultivation of graduate studentsmajoring in applied statistics. One tutor comes from the trainingunit, and the other tutor comes from outside the school and expertsin the field.
VII.Degree Thesis
Underthe guidance of the tutor, the dissertation should be independentlycompleted by the master student himself according to the schedule.The dissertation should be closely combined with practical problems,actual data and actual cases. And it may take the form of dataanalysis reports related to data collection, collation and analysis,empirical research using statistical methods, etc.
Thethesis proposal for graduate students of applied statistics should becompleted in the second semester. The writing requirements of thethesis refer to 'Basic Requirements and Evaluation Index Systemof Thesis for Master’s Degree of Applied Statistics in Shanghai'and 'Requirements for Format of Thesis for Master’s Degree inShanghai University of International Business and Economics (Revisedin 2020)'.
Thosewho complete the credits specified in the training plan, finishprofessional internships and pass the thesis defense will be awardeda master's degree in applied statistics by the degree evaluationcommittee.
AttachedTable:
Category | CourseName | Semester | CreditHours | Credit | Department | ||
1 | 2 | 3 | |||||
Common RequiredCourses | Researchon Theory and Practice of Socialism with Chinese Characteristics(degree course) | 2 | 36 | 2 | Schoolof Marxism | ||
Researchon Marxism and Social Science Methodology | 1 | 18 | 1 | Schoolof Marxism | |||
AdvancedEnglish Speaking and Writing | 2 | 36 | 2 | Schoolof Foreign Language | |||
StatisticsSoftware (English) | 2 | 36 | 2 | Schoolof Statistics and Information | |||
RequiredCourses | AcademicStandards and Paper Writing | 1 | 18 | 1 | Schoolof Statistics and Information | ||
AdvancedStatistics | 3 | 54 | 3 | Schoolof Statistics and Information | |||
AdvancedProgramming | 2 | 36 | 2 | Schoolof Statistics and Information | |||
DataAnalysis and Statistical Modeling | 2 | 36 | 2 | Schoolof Statistics and Information | |||
AdvancedDatabase Technology | 2 | 36 | 2 | Schoolof Statistics and Information | |||
MachineLearning | 3 | 54 | 3 | Schoolof Statistics and Information | |||
DirectionElective Courses | DataScience and Business Statistics | ||||||
StatisticalComputing* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
StatisticalAnalysis of Complex Data* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
AlgorithmsDesign and Practice* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
BusinessBig Data Case Analysis* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
OptimizationMethod and Data Analysis Practice* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
BigData Technology and Trade Statistics | |||||||
AdvancedEconometrics* | 3 | 54 | 3 | Schoolof Statistics and Information | |||
Theoryand Method of National Economic Accounting | 3 | 54 | 3 | Schoolof Statistics and Information | |||
InternationalTrade Statistics | 3 | 54 | 3 | Schoolof Statistics and Information | |||
GlobalValue Chain Statistics | 2 | 36 | 2 | Schoolof Statistics and Information | |||
DataScience Technology and Application* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
FinancialTechnology and Risk Management | |||||||
FinancialEconometrics* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
FinancialEngineering* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
MathematicalFinance* | 3 | 54 | 3 | Schoolof Statistics and Information | |||
SelectedLectures on Financial Technology* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
AlgorithmsDesign and Practice* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
ArtificialIntelligence and Business Data Mining | |||||||
Introductionto Algorithms* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
TextMining Technology* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
DistributedComputing* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
ComputerVision* | 2 | 36 | 2 | Schoolof Statistics and Information | |||
DeepLearning* | 3 | 54 | 3 | Schoolof Statistics and Information | |||
MajorElective Courses | Introductionto Frontier Literature of Statistics | 1 | 18 | 1 | Schoolof Statistics and Information | ||
BayesianStatistics | 2 | 36 | 2 | Schoolof Statistics and Information | |||
NonparametricStatistics | 2 | 36 | 2 | Schoolof Statistics and Information | |||
MultivariateStatistical Analysis | 2 | 36 | 2 | Schoolof Statistics and Information | |||
GeneralizedLinear Mixed Effects Model (English) | 2 | 36 | 2 | Schoolof Statistics and Information | |||
Designand Modeling of Experiments |
| 2 | 36 | 2 | Schoolof Statistics and Information | ||
InternationalTrade Statistics Research | 2 | 36 | 2 | Schoolof Statistics and Information | |||
DataMining and Quantitative Research in Economics | 2 | 36 | 2 | Schoolof Statistics and Information | |||
High-frequencyData and Quantitative Transaction | 2 | 36 | 2 | Schoolof Statistics and Information | |||
Theoryand Application of Spatio-temporal Statistics | 2 | 36 | 2 | Schoolof Statistics and Information | |||
AdvancedEconometrics（II） | 3 | 54 | 3 | Schoolof Statistics and Information | |||
StochasticProcess | 2 | 36 | 2 | Schoolof Statistics and Information | |||
DataMining | 2 | 36 | 2 | Schoolof Statistics and Information | |||
ManagementDecision Theory and Method | 3 | 54 | 3 | Schoolof Statistics and Information | |||
GameTheory | 2 | 36 | 2 | Schoolof Statistics and Information | |||
AndroidMobile Application Development | 2 | 36 | 2 | Schoolof Statistics and Information | |||
InternetLeading Technology Innovative Applications | 2 | 36 | 2 | Schoolof Statistics and Information | |||
ReinforcementLearning | 2 | 36 | 2 | Schoolof Statistics and Information | |||
ComplexSystems and Complex Networks | 2 | 36 | 2 | Schoolof Statistics and Information | |||
Cross-specialtyCourses | ServiceTrade and Global Value Chain | 2 | 36 | 2 | Schoolof Trade Negotiation | ||
SpecificLectures of Extenics | 2 | 36 | 2 | Schoolof Statistics and Information | |||
MonographicStudy on Marketing Management | 2 | 36 | 2 | Schoolof Management | |||
EmpiricalMethods in Psychology and Behavior Research | 2 | 36 | 2 | Schoolof Management | |||
MonographicStudy on Enterprise and Company Law | 2 | 36 | 2 | Schoolof Law | |||
Researchon Financial Management | 2 | 36 | 2 | Schoolof Accounting | |||
Researchin Corporate Finance | 2 | 36 | 2 | Schoolof Finance | |||
EntrepreneurialManagement | 2 | 36 | 2 | Schoolof Management | |||
Practiceof Import and Export | 2 | 36 | 2 | Schoolof Business | |||
FinancialRisk Management | 2 | 36 | 2 | Schoolof Finance | |||
PracticalTeaching | Casestudy | 1 | 18 | 1 | |||
Lectures | 8times | 2 | |||||
SocialPractice | 4 | ||||||
Note:* the above three elective courses can also be used asprofessional elective courses in other directions | |||||||