MBTI十六型性格之 你的管理風格是什麼?

MBTI十六型性格之 你的管理風格是什麼?

MBTI CPD Course

工作坊簡介

領袖要懂得「用人」,但更要懂得「閱人」!不同性格類型的人有著不同的溝通方式及工作動機,需要不同的激勵方式及管理方法。因此追求卓越的你,除了擁有常規的管理知識外,還要懂得「閱人」的技巧,才能做到用人唯才,因型施教,建立高效率的工作團隊。這工作坊沒有艱深難懂的理論,也沒有深奧難明的管理哲學;相反我們著重教授實際的性格分析方法,讓管理人以最短的時間,掌握分辨不同性格的精要方法。本課程以美國財星五百大企業常用於培訓領袖的「MBTI十六型性格學」為設計基礎,讓你透過課堂的理論學習、個案分析及體驗式活動等學習環節,提升你的管理層次。

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Experience Capitalization and Expert System (18 & 21 Feb 2020)

Experience Capitalization and Expert System

簡介:

As a branch of KM, experience capitalization is a complex process to transform experience and learning for future use. This workshop will equip with participants tools to capture experience and knowledge from him/herself and from others, especially from experts. The captured experience and knowledge will enable participants avoid repeating the same mistakes or succeeding in a faster speed. As part of the knowledge engineering, an expert system will be used for knowledge sharing.

目標:

The workshop enables the participants understanding and practicing the experience capitalization and capture of knowledge from experts for building the Expert System.

Target Audience:

  • Interest in KM
  • Middle Managers
  • Newly promoted supervisor/officers
  • Anyone who would like to equip themselves with up-and-coming techniques, knowledge and increase their “power” meeting the coming challenges in workplace.

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Conflict Management

Conflict Management

conflict_management

簡介

This course will give participants tools to improve their communication skills and learn how to solve conflict in work place.

課程大綱

  1. The basics of communication
  2. How conflicts arise and perpetuate
  3. Technics for conflict resolution
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Knowledge Discovery – Data Mining and Big Data (25 & 29 Feb 2020)

Knowledge Discovery – Data Mining and Big Data

簡介

This workshop provides participants with concepts of Big Data, importance of Big Data and its applications in business world. Participants will learn how to discover new knowledge by using Data-Mining, the core technique in Big Data. For this Unit, algorithm in Data Mining will not be discussed hence, all practical exercises will use MS Excel. No advanced arithmetic and knowledge in Excel are required.

誰適合參加?

Anyone interested in knowing the Data Analysis (simple data-mining) in Knowledge Discovery and learn how companies using them to their competitive advantages.

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Application of Hypothesis Testing

Application of Hypothesis Testing

簡介

This course offers an extension to the “Analysis” module on Lean Six Sigma methodology. Hypothesis testing is considered one of the important modules in decision analytics for managerial considerations based on the observations.

What is the target?

There are various data types and malicious manipulations and interpretations could be dangerous to strategic decisions on the Analysis stage during a Six Sigma Project, especially large-scaled projects. The course helps professionals and executives to have a correct decision making strategies based on correct usage of hypothesis testing types.

誰適合參加?

Specialists from Business Process Excellence, Market Research & Big Data, Quality Engineering, Process Engineering, Industrial Engineering, Pharmaceutical, Construction, Legal evidence, etc.

Teaching Methodology

  1. Background theory
  2. examples
  3. case-study scenarios

證書

Certificate of Successful Completion will be awarded to students who have achieved attendance criteria.

課程大綱

  1. Basic statistics & statistical terms
    •  Statistics recap
    • Statistical Terms
  2. 假設檢驗
    • Theory, workflow & Applications
    • Classifications
    • The Frequently-used Hypothesis Testings
      • Theory
      • Mathematical calculations & 例子
      • Minitab Simulation examples
  3. Industry specific Scenario Analysis
  4. In-class practices
  5. Useful References & Links

Fee

  • 專業資格註冊名單: HK$1,400
  • Six Sigma Community Buddies /Members of SSI Partners: HK$1,500
  • 其他: HK$1,650

授課語言: Mainly English with some Cantonese

地點: 單位 1627, 16/知名, 星光行, 沒有. 3 梳士巴利道, 尖沙咀, 九龍 *map*

日期:

CPD信用: 7 credits

時間: 1 日數, 9:30am to 5:30下午 (7 hours per day)