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管理學術研究中心 Management Studies Research Center National Sun Yat-sen University
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Core

Basic Data Analysis

Statistics and R(Harvard)

- An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

Data Analysis for Social Scientists (MIT)

- Learn methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest.

Introduction to R Programing (Microsoft)

- Learn the R statistical programming language, the lingua franca of data science in this hands-on course.

Explore Statistics with R (Karolinska Inst., Sweden)

- Learn basic statistics in a practical, experimental way, through statistical programming with R, using examples from the health sciences.


Business Analytics

The Analytic Edge (MIT)

- Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life.

Strategic Analytics (ESSEC & Accenture)

- This specialization is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts.

Build Intelligent Applications (UW)

- This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.


Social Media Analytics

Social Media Data Analytics (Rutgers, U. NJ.)

- Learner Outcomes: After taking this course, you will be able to:
1. Utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr.
2. Process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data.
3. Analyze unstructured data - primarily textual comments - for sentiments expressed in them.
4. Use different tools for collecting, analyzing, and exploring social media data for research and development purposes.

Social Media Marketing (Northwestern)

In today’s marketplace, organizations need effective, profitable social marketing strategies. In this Specialization, you’ll learn to match markets to social strategies to profitably grow your business. You’ll use social media tools and platforms to design, manage, and optimize social campaigns to promote growth and position your brand in the global digital marketplace, and you’ll develop targeted content to spark dialogue with various social communities.

Digital Marketing (UI. Urbana-Champaign)

- This Specialization explores several aspects of the new digital marketing environment, including topics such as digital marketing analytics, search engine optimization, social media marketing, and 3D Printing.

Gamification (U. Pennsylvania)

Gamification is the application of game elements and digital game design techniques to non-game problems, such as business and social impact challenges. This course will teach you the mechanisms of gamification, why it has such tremendous potential, and how to use it effectively. For additional information on the concepts described in the course, you can purchase Professor Werbach's book For the Win: How Game Thinking Can Revolutionize Your Business in print or ebook format in several languages.

Introduction to Communication Science (U. Amsterdam)

- Upon completion of this course, students should:
• have knowledge of the history and development of communication science
• have knowledge of the dominant theoretical approaches within communication science
• have knowledge and understanding of the most important models and concepts in this field.


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