Course Information
Schedules
- 12 Jul 2023 (Wed) - 13 Sep 2023 (Wed) 7:00 PM - 10:00 PM
Registration period
23 Mar 2023 (Thu) - 2 Jul 2023 (Sun)
Price
HKD 4,800
Course Level
Study Mode
Duration
3 Hour(s)
Language
English
Location
8 Hoi Wang Road Mongkok (West)
27 views
Course Overview
INTRODUCTION
Citizen data scientists are enterprise power users who can do moderate data analysis tasks. Gartner defines a citizen data scientist as “a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.” They bridge the gap between those doing self-service analytics as business users and those doing advanced analytics as data scientists.
DESIGN FOR
This course is designed for business executives who want to enhance his/her career path and turning into a Citizen Data Scientist.
OBJECTIVES
- Able to master the skills sets of Business Analytics
- Explain why and how different tools for Big Data and Business Analytics are being used
- Explain the key factors to solve and handle the ever-changing Big Data challenges
- To become a professional citizen data scientist
What You’ll Learn
CONTENTS
A) Introduction to Big Data ( 大數據介紹 )
- Introduction to Big Data
- How important the Big Data Analytics skills are
- Prospects of Analytic skills
B) Tools for Business Analytics ( 商業分析工具 )
- Brief introduction of tools available for Business Analytics
- Introduction to diff erent tools for Business Analytics
- Exploratory analysis of Business operations using these tools
C) Data Visualization ( 數據可視化 )
- How Data Visualization works
- Data Visualization showcases
D) Role of Citizen Data Scientist ( 公民數據科學家 )
- Job natures of a Citizen Data Scientist
- 4 processes of Business Analytics
- Descriptive analytics use cases
E) Business Analytics in Action ( 商業數據分析 )
- Defi nition of descriptive analytics
- Data Analysis life cycle
- Data Representation
F) Analytics Processes in Diagnostic and Predictive Analytics ( 診斷和預測分析中的分析過程 )
- Recall and explain of diagnostic analytics and predictive analytics
- Interpretation and application of the diagnostic analytics and predictive analytics
- Application of diagnostic and predictive analytics in business modelling
G) Diagnostic Analytics Essentials ( 診斷分析要點 )
- Name and explain tools use in collecting data
- Implement visualisation and apply analysing data tasks
H) Predictive Analytics Essentials ( 預測分析要點 )
- Machine learning: supervised and unsupervised learning
- Build a predictive model with: Simulation models, Decision Tree, Clustering with Python
I) Case Studies ( 個案分析 )
