search

I WOULD LIKE TO

DS
Data Science for the Business User
SHARE
Data Science for the Business User
  • Overview
  • Objectives & Outline
  • Methodology
  • Participant Profile
  • Trainer
  • Overview
    PROGRAMME DETAILS

    Duration

    5 days

    TIME

    9:00 AM – 5:00 PM

    VENUE

    SAS Institute, KL Sentral

    40
    AICB
    CPD HOURS
    The demand for data scientists continues to grow beyond supply, companies and organisations are looking for solutions. As a result, Citizen Data Scientists are emerging from within the business analyst community. They combine the skills of traditional business analysts with some of the expertise of statisticians.

    With new, powerful and affordable tools available in the market, more and more people are finding they are empowered to do something intelligent with their data. Analytics is no longer the exclusive province of statisticians and specialists as it is now for all of us as we become more data-driven and analytical in our thinking and our work. This in turn has resulted in the rise of the Citizen Data Scientist. This programme will enable Citizen Data Scientists to gain the expertise and skills to perform their role with greater effectiveness and expertise. Participants will then be able to perform the main data-related tasks for the Citizen Data Scientist using the point-and-click capabilities of SAS Visual Analytics: data access and data manipulation, data exploration using analytics and building predictive models.
    LEARNING LEVEL
    Intermediate
    PROGRAMME FEE

    AICB MEMBER

    MYR

    7,000*

    / PAX

    NON-MEMBER

    MYR

    7,600*

    / PAX

    *Subject to 6% Service Tax

  • Objectives & Outline
    LEARNING OBJECTIVES
    By the end of this programme, participants will be able to:

    • Load data from different formats
    • Prepare data for analysis
    • Analyse data using effective data visualisation
    • Build and compare data mining models

    PROGRAMME OUTLINE
    INTRODUCTION TO BIG DATA AND ANALYTICS

    Introduction to Data Science
    • Era of abundance
    • Big Data explained
    • Data analysis overview

    Introduction to Statistics
    • Examining data distributions
    • Obtaining and interpreting sample statistics
    • Examining data distributions graphically
    • Using exploratory data analysis
    • Producing correlations
    • Fitting a simple linear regression model

    PREPARING FOR ANALYSIS

    Getting Started with SAS Visual Analytics
    • Exploring SAS Visual Analytics concepts
    • Using the SAS Visual Analytics home page
    • Discussing the course environment and scenario

    Using the SAS Visual Analytics Explorer
    • Examining the Visual Analytics Explorer
    • Selecting data and defining data item properties
    • Creating visualisation
    • Enhancing visualisation with analytics
    • Interacting with visualisation and exploration

    Examining SAS Visual Data Builder
    • Exploring SAS Visual Data Builder
    • Creating simple queries

    Creating Complex Queries in SAS Visual Data Builder
    • Importing data using Visual Data Builder
    • Creating calculated columns and filtering data
    • Creating advanced queries

    Advanced Topics for SAS Visual Data Builder
    • Accessing user-defined formats

    Using Explorer and Designer to Load Data
    • Using explorer and designer to import data
    • Using explorer and designer to create calculated columns

    ANALYTICAL DATA VISUALISATION AND MODELLING DATA

    Cluster Segmentation
    • Understanding segmentation
    • Using cluster analysis

    Models with Continuous Targets
    • Managing projects and models
    • Using linear regression models
    • Using generalised linear models

    Models with Categorical Targets
    • Using logistic regression
    • Using decision trees

    Model Comparison and Assessment
    • Comparing models
    • Scoring models

    CASE STUDY

  • Methodology

    Interactive lectures with a classroom style. The instructors will deliver real-world knowledge, cutting-edge techniques and useful tips by combining expertly designed lecture, software demonstration and Q&A sessions.

  • Participant Profile
    Business analysts and data analysts who want to practice the self-service data preparation capabilities of SAS and the ease of use of advanced analytics in exploring and visualising the data
  • Trainer

    FuiChoon Chu

    • HRDF Certified Trainer
    • SAS Certified Statistical Business Analyst
    • SAS Certified Predictive Modeler
    • SAS Certified Base Programmer
    • M.Sc - Applied Statistics

    Fui, a SAS certified Predictive Modeler, Statistical Business Analyst and Base Programmer, specialises in Data Mining - Risk Scorecard, Predictive Modelling and Customer Segmentation. She holds a Bachelor’s Degree with double major in Mathematics and Statistics, as well as a Master’s Degree in Applied Statistics.
    She has 20 years’ experience in Data Mining across banking, insurance, casino and manufacturing industries. Prior to becoming an independent consultant, Fui has worked in Database Marketing, Marketing Analytics, Decision Management, Customer Intelligence, Risk Scoring and Analytics for multinational companies such as Western Digital, AIG, Citibank (AVP – Decision Management), Genting Resorts (Head – Customer Intelligence Unit), Hong Leong Bank (Head – Scoring & Analytics) and Standard Chartered Bank (Senior Manager – Credit & Collections) in Malaysia and in America when selected as the Citigroup Global Talent Associate in 2005. She has conducted and trained professionals, especially from the financial sector, in Data Mining with SAS tools.

Copyright © Asian Banking School (ABS). All rights reserved.

 CONNECT WITH US

Ooops!
Generic Popup