MSc in Marketing Programme

Director Prof. Jianmin JIA

§ Programme Director, MSc in Marketing, CUHK-Shenzhen§ Presidential Chair Professor§ Winner of 2019 Fudan Prize for Eminent Contributions to

Management Science§ Effie Greater China Board Member

Ph.D. in Information Systems and Management Science, The University of Texas at Austin; M.S. in Industrial Management, Shanghai Jiao Tong University; B.S. in Industrial Management, Southwest Jiaotong University

o Research Field：Big Data Behavioral Research, Social Networks, Decision Making, Perceptions of Risk

World Class Faculty

Jianmin Jia, Presidential Chair Professor

Popawka SamartAssociate Professor

Stella L.M. So Associate Professor

Kin-nam LauProfessor

Ming LiuProfessor

World Class Faculty

Wenli Zou, Assistant Professor Qitian Ren, Assistant Professor Yoonji Shim, Assistant Professor

Lingjing Zhan, Senior Lecturer

Qiang Zhang, Assistant Professor

Samson Tai, CTO, IBM Jeffrey Hui, Professional Consultant, Business School, CUHK

Highlights

Two Concentrations

Only AIMarketing

ProgrammeIn Shenzhen

InternationalExchange

Career Development

Practitioner Workshop

Industry Experts

BusinessSimulations

PractitionerWorkshops

Strategic Marketing Management Consumer Behavior Marketing Research in the Digital Age Communications in the Digital AgeBig Data Marketing StrategyCustomer Relationship ManagementDigital and Social Media Marketing

Curriculum

Required Courses

7 (21 credits)

Strategic Marketing Management Consumer Behavior Marketing Research in the Digital Age Communications in the Digital AgeBig Data Marketing StrategyCustomer Relationship ManagementDigital and Social Media Marketing

Curriculum

Artificial Intelligence Principles*Artificial Intelligence applications in Marketing*Marketing Analytics and Machine Learning*Big Data Modeling and Management*

Elective Courses

IOT and Retail Technology Creative Marketing and Design ThinkingStrategic Brand MarketingService MarketingMarketing Engineering Big Data Marketing Practicum Internet Finance Data MiningWeb AnalyticsFinancial Analytics

Note: students can declare the AI Marketing Concentration if they complete all the four courses marked with *.

5 (15 credits)

AI Marketing

Artificial Intelligence Principles Artificial Intelligence applications in Marketing

The course will provide an overview of AI from theory to practical. Student will learn what is AI and how it can be integrated into businesses from identify marketing potential to chatbot customer communication. The course will teach students how to use AI natural language classification services to build chatbots/virtual agents across of marketing channels and touchpoints to support sales and marketing; using image recognition to tag and classify visual content to support visual listening and unlock hidden value in unstructured data using the natural language understanding to find answers, monitor trends, and surface patterns.

This course presents students with a foundational understanding of state-of-the-art artificial intelligence (AI) technologies and their marketing implications as well as their limitations. We will cover three key AI technologies: machine learning, natural language processing, and robotics and discuss their marketing applications. Students will gain a practical introduction to these key AI technologies and their marketing implications. The course does not assume any particular technological background, though some programing knowledge is a plus. Students will focus on the marketing and managerial implications of these technologies and how they can be applied in the workplace. In addit ion, students wi l l have the oppor tun i t ies to learn how to app ly these AI technologies using real marketing dataset.

AI Marketing

Marketing Analytics and Machine Learning

The objective of the course is to help student to understand what machine learning is and how it can be used in marketing analytics. The course will first introduce to students the major machine learning algorithms that are commonly used in marketing and sales. It will also discuss real examples of using machine learning in marketing scenar ios, such as personal iz ing offers to customers or improving an onl ine customer experience. Students will also learn about the theory, techniques and how to choose the machine learning algorithm that best f i ts a part icular marketing problem in industry.

Big Data Modeling and Management

As the web technology and mobile use rapidly evolves, the volume of user-generated data expand exponentially. The distillation of knowledge from such a large amount of unstructured, dynamically changed data is an extremely difficult task without the help of distributed techniques. This course introduces most state-of-the-art Big data analytical concepts, techniques and tools. By taking this course, students will gain hands-on technical experiences on solving Big Data problems using distributed algorithms and tools widely adopted in industry. The topics include bas ic concepts about B ig Data, ins ta l la t ion and configuration of Hadoop and Spark under a multi-node environment, distributed algorithms (recommender systems, clustering, classification, topic models, and network analysis), web crawling and web data extraction using major application programming interfaces.

Academic Activities

The Greater Bay Area Economy and Development Forum

SFI Distinguished Lecture Series

解析新零售变化

曾斌每日优鲜联合创始人兼总裁

温书豪中科院博士

麻省理工学院量子物理专业博士后

AI、云计算与科技创新

Admissions• Hold a Bachelor‘s degree from a recognized university and

have achieved an average grade of not lower than “B” or second honor degree, or equivalent;

• Language proficiency

- TOEFL (normally not lower than 550 Paper-based; and 79 internet-based);

- IELTS (Academic) (normally not lower than Band 6.5);- GMAT (Verbal, normally not lower than 21); - or Completed a degree programme for which the medium of

instruction was English and the CUHK(SZ) Graduate School may request applicants to provide additional supporting documents to prove their English proficiency;

Requirements

• No written examination

• Group interview (language: Chinese)• One on one interview (language: English)

Interviews

Fees and Scholarships

Tuition Fees

RMB 198,000(tentative)

Scholarships

Merit-base Entrance Scholarships are granted to qualified candidates.Scholarship for Academic Excellence will be awarded subject to satisfactory academic performance.

Term of Study

18 months

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