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Business has become more challenging day by day. The traditional methods and rules are replaced by the by Artificial Intelligence. One of the most challenging parts of this knowledge-oriented world is to manage knowledge.
The [course_title] course teaches the process of knowledge management and Big data management in Business. Throughout the course, you will learn how knowledge is captured, elicited, organised and created in the business. The course teaches you about big data and shows how you can use data analytics from a laymen perspective. The techniques of mining knowledge from big data, social problems with big data, cloud computing and cloud services, various case studies will also be illustrated in the course.
Assessment
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
Certification
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Course Credit: Hong Kong Polytechnic University
Course Curriculum
Module 1 | |||
Welcome Video | 00:10:00 | ||
Team of instructors | 00:06:00 | ||
Brief Introduction of PLE&N | 00:01:00 | ||
PLE&N Configuration | 00:06:00 | ||
Module 1 Intro Video | 00:01:00 | ||
1.1 Introduction to Knowledge | 00:06:00 | ||
1.2.1 A Brief History of Knowledge Management | 00:11:00 | ||
1.2.2 Knowledge-based Economy | 00:16:00 | ||
1.3.1 Types of Knowledge Processes | 00:12:00 | ||
1.3.2 Interview with Melina Handriz on KM Framework | 00:07:00 | ||
1.4.1 Two Main Types of KMS | 00:02:00 | ||
1.4.2 Soft & Hard KM Tools (People-based & IT-Oriented) | 00:01:00 | ||
1.4.3 Common Myths of KMS | 00:03:00 | ||
1.4.4 KM System – Are they Real? | 00:01:00 | ||
1.4.5 Linking Knowledge Management Technologies to Strategy | 00:11:00 | ||
1.5.1 Categorizing KMS by Knowledge Processes | 00:04:00 | ||
1.5.2 Codification & Personalization of KMS | 00:04:00 | ||
1.5.3 EDMS & Knowledge Repositories | 00:14:00 | ||
1.5.4 Collaboration | 00:10:00 | ||
1.5.5 Shortfalls | 00:04:00 | ||
1.6.1 KM Sharing Tools | 00:03:00 | ||
1.6.2 Good Practices | 00:01:00 | ||
1.6.3 Use of Storytelling to elicit Near-Miss Knowledge | 00:07:00 | ||
1.6.4 Storytelling from Hong Kong Police | 00:08:00 | ||
1.6.5 Communities of Practice | 00:01:00 | ||
1.6.6 Knowledge Café | 00:01:00 | ||
1.6.7 After Action Review | 00:02:00 | ||
1.7.1 KM Process, Projects and Program | 00:08:00 | ||
1.7.2 Managing KM Projects | 00:07:00 | ||
1.7.3 Interview with Nicole Sy on KM Projects and Journey | 00:08:00 | ||
1.7.4 KM Metrics | 00:16:00 | ||
1.7.5 Interview with Chief Superintendent Dr. Eric Cheng on Strategic Planning | 00:05:00 | ||
1.7.6 KM Practices | 00:01:00 | ||
1.8.1 Relationship between KM and Big Data | 00:14:00 | ||
1.8.2 Interview with Muhammad Saleem Sumbal on Big Data and Enterprise KM | 00:14:00 | ||
Module 2 | |||
Module 2 Intro Video | 00:02:00 | ||
Introductory Video on Wiki | 00:06:00 | ||
2.1.1 Taxonomy | 00:17:00 | ||
2.1.2 The Angns Company Case Study | 00:06:00 | ||
2.1.3 Extraction of IC from Annual Reports | 00:12:00 | ||
2.1.4 Intro to TaxoFolk | 00:14:00 | ||
2.1.5 Demonstration of the TaxoFolk system | 00:06:00 | ||
2.2.1 Search Engine | 00:20:00 | ||
2.2.2 Common Method for Locating Experts | 00:06:00 | ||
2.3.1 Enterprise Portal | 00:16:00 | ||
2.3.2 Empty Portal | 00:10:00 | ||
2.3.3 Case Study – The InTaxon Project | 00:10:00 | ||
2.3.4 Interview with Major Barry Byrne | 00:12:00 | ||
2.4 Knowledge Audit for Unstructured Business Process | 00:08:00 | ||
2.5 Case Study – The K-MISS Project | 00:11:00 | ||
2.6.1 Interview with Hong Kong Police on KM Journey | 00:13:00 | ||
2.6.2 Interview with Detective Senior Superintendent Wyman Lee on Detective Plus | 00:07:00 | ||
2.6.3 Interview with Superintendent Alex Law on Marine Policing | 00:08:00 | ||
2.6.4 HKPolice – Auxiliary Police – Amy Lee | 00:06:00 | ||
2.6.5 HKPolice – KM Training – Dr. Chiu | 00:03:00 | ||
Module 3 | |||
00:00 | |||
3.1 Intro | 00:01:00 | ||
3.1.1 What are SMEs | 00:06:00 | ||
3.1.2 SMEs’ characteristics | 00:10:00 | ||
3.1.3 Working in Smaller Companies | 00:06:00 | ||
3.1.4 Why KM in SMEs | 00:06:00 | ||
3.1.5 KM desicions in SMEs | 00:16:00 | ||
3.1.6 Interview with Dr Bolisani – KM for SMEs | 00:09:00 | ||
3.1.7 SME Case Studies | 00:05:00 | ||
3.2 Intro | 00:01:00 | ||
3.2.1 K_Challenge Retirement | 00:08:00 | ||
3.2.2 K_Challenge Knowledge Retention | 00:06:00 | ||
3.2.3 K_Challenge Knowledge Leakage | 00:04:00 | ||
3.2.4 K_Challenge Knowledge Loss | 00:03:00 | ||
3.2.5 K_Challenge Knowledge Risk Management | 00:05:00 | ||
3.2.6 Interview with Haley on Knowledge Risk | 00:07:00 | ||
3.3 Using KMS: a taxonomy of SME strategies | 00:13:00 | ||
Module 4 | |||
Module 4 Intro Video | 00:03:00 | ||
4.1.1 Introduction | 00:01:00 | ||
4.1.2 Definition | 00:04:00 | ||
4.1.3 An Analogy | 00:03:00 | ||
4.1.4 Characteristics of the Cloud | 00:03:00 | ||
4.1.5 The Concept of “Virtualization” | 00:02:00 | ||
4.1.6 Internet, Web 2.0 and the Cloud | 00:02:00 | ||
4.1.7 Animoto company case study | 00:04:00 | ||
4.2.1 Introduction | 00:01:00 | ||
4.2.2 Types of cloud services and their benefits | 00:12:00 | ||
4.2.3 Common types of Cloud | 00:04:00 | ||
4.2.4 Advantages of cloud-based Knowledge Management Systems | 00:09:00 | ||
4.2.5 Common cloud applications | 00:04:00 | ||
4.3.1 Introduction | 00:01:00 | ||
4.3.2 Cloud for transformation | 00:02:00 | ||
4.3.3 What is a Knowledge Cloud | 00:12:00 | ||
4.4.1 Introduction | 00:01:00 | ||
4.4.2 Knowledge Cloud applications | 00:03:00 | ||
4.4.3 The Cloud as an intelligent Knowledge Center | 00:04:00 | ||
4.4.4 Robots and intelligent software | 00:01:00 | ||
4.4.5 Cloudsourcing | 00:08:00 | ||
4.4.6 Drawing human intelligence from the cloud | 00:03:00 | ||
4.5.1 Introduction | 00:01:00 | ||
4.5.2 Introduction to a Personal Learning Environment & Network (PLE&N) | 00:12:00 | ||
4.5.3 Results, Benefits and Advantages of the PLE&N | 00:08:00 | ||
4.5.4 Learners’ Experiences, Sustainability, Latest Development of PLE&N | 00:07:00 | ||
Module 5 | |||
Module 5 Intro Video | 00:03:00 | ||
5.1.1 Introduction to PKM | 00:21:00 | ||
5.1.2 Challenges and Tools for PKM | 00:25:00 | ||
5.1.3 PKM Models | 00:13:00 | ||
5.2 Applying KM to Project | 00:14:00 | ||
5.3 Section Intro | 00:01:00 | ||
5.3.1 Interview with Florian Kragulj – Design Thinking | 00:08:00 | ||
5.3.2 Interview with Rudolf DSouza Design thinking | 00:13:00 | ||
5.3.3 Interview with Prof de Bont Design thinking | 00:11:00 | ||
5.3.4 Research Interview with Nikolina on Design Thinking | 00:14:00 | ||
5.3.5 Design Thinking Interview in AKF2017 | 00:01:00 | ||
5.4.1 Introduction | 00:01:00 | ||
5.4.2 Managing Knowledge in the Age of Digitalization | 00:19:00 | ||
5.4.3 Interview with Dr. Bonnie Cheuk | 00:13:00 | ||
5.4.4 Interview with Mr. Eric Hunter | 00:06:00 | ||
5.4.5 Interview with Dr. Wong | 00:09:00 | ||
5.4.6 Interview with Mr. Colin Farrelly | 00:08:00 | ||
5.4.7 Interview with Mr John Obrien – Digitalisation | 00:22:00 | ||
5.4.8 Networked Economy | 00:07:00 | ||
5.5 Section Intro | 00:01:00 | ||
5.5.1 Prof. Wilkesman – Organizing Routines or Innovations | 00:10:00 | ||
5.5.2 Interview with Maurizio on KM&I4.0 | 00:12:00 | ||
5.5.3 Dr. Maurizio Massaro – IC Disclosure and digital communication | 00:13:00 | ||
Module 6 | |||
Module 6 Intro Video | 00:02:00 | ||
6.1.1 Introduction | 00:01:00 | ||
6.1.2 What is a Web of document, how to create it and its limitations | 00:10:00 | ||
6.2.1 Introduction | 00:01:00 | ||
6.2.2 What is Web of data, structured data and open linked data | 00:11:00 | ||
6.2.3 Applications of the open linked data cloud | 00:06:00 | ||
6.2.4 Interview with Professor Klaus Tochtermann – Clarifications on questions posed in forum | 00:06:00 | ||
6.2.5 Interview with Kim Salkeld on Open Data in Hong Kong | 00:10:00 | ||
6.3.1 Introduction | 00:01:00 | ||
6.3.2 Library use of the Web of data – the Econbiz system | 00:05:00 | ||
6.3.3 Library use of Web of data – the EconStor system | 00:05:00 | ||
6.4.1 Introduction | 00:01:00 | ||
6.4.2 Social Web and Social Media Tools | 00:09:00 | ||
6.5.1 Introduction | 00:02:00 | ||
6.5.2 Sentiment analysis and social media monitoring tools | 00:12:00 | ||
6.5.3 Social Media Strategy and Demonstration of Sentiment Analysis | 00:10:00 | ||
6.6 Interview with Professor Klaus Tochtermann – Introduction to semantic technology | 00:07:00 | ||
6.7.1 Introduction | 00:01:00 | ||
6.7.2 Science 2.0 and its impacts | 00:16:00 | ||
Module 7 (Part 1) | |||
Module 7 Intro Video | 00:13:00 | ||
7.1.1 Introduction | 00:01:00 | ||
7.1.2 Data Mining Overview | 00:24:00 | ||
7.2.1 Introduction | 00:01:00 | ||
7.2.2 The Application lifecycle in On-line Business | 00:26:00 | ||
7.3.1 Introduction 1 | 00:01:00 | ||
7.3.2 From Basics to OLAP | 00:14:00 | ||
7.3.3 Introduction 2 | 00:01:00 | ||
7.3.4 Data Mining techniques | 00:21:00 | ||
7.4.1 Introduction | 00:01:00 | ||
7.4.2 Classic Data vs. Big Data | 00:24:00 | ||
7.5.1 Introduction | 00:01:00 | ||
7.5.2 Principles of Data Governance | 00:20:00 | ||
Module 7 (Part 2) | |||
7.6.1 Introduction | 00:01:00 | ||
7.6.2 The Hadoop Stack Ecosystem | 00:21:00 | ||
7.7.1 Introduction | 00:01:00 | ||
7.7.2 Analytics & Applications and case studies | 00:28:00 | ||
7.8.1 Introduction | 00:01:00 | ||
7.8.2 Advanced Topics in Big Data Analytics | 00:19:00 | ||
7.9.1 Introduction | 00:01:00 | ||
7.9.2 Conclusions and Lessons Learned | 00:37:00 | ||
7.10 Big Data overview (Module Summary and New Frontiers) | 00:20:00 | ||
End-of-Course Video | |||
End-of-Course Video | 00:07:00 | ||
Additional Content in PLE&N | 00:01:00 | ||
Assessment | |||
Submit Your Assignment | 00:00:00 | ||
Certification | 00:00:00 |
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