Data Analytics Deployment & Performance Monitoring

Home
Data Analytics Deployment & Performance Monitoring

Data Analytics Deployment & Performance Monitoring

Course Reference No:
TGS-2020503219 (Classroom Learning)

Course Objectives

This course is the sequel to our Data Analytics for Business Analysts course, and is designed for IT business analysts and professionals to undertake data science consultancy or advisory roles for data analytics projects, to drive a deeper discernment in:

Data-driven problem solving
Connecting business problems to apply data science methods
Examining critical success factors of data science projects
Managing analytics projects (both the innovation cycle and deployment cycle)
Methods of data extraction, cleansing and transforming raw data into analytics-ready data

It aims to equip participants with the knowledge and skills to:

Experiment with data science capabilities and recognise its limitations
Implement and manage the data science process for innovation and deployment cycles
Provide advisory for and deliver high-quality data analytics projects

At the end of this course, participants will be able to:

Get up to speed on analytics life cycle and move into data-driven problem solving
Assess relevant data components for data exploration and insight discovery
Distinguish model equation and outputs from modeling scripts
Setup predictive analytics model with the right mix of features and functionality requirement
Apply model performance monitoring metrics and method
Design UI from user perspective
Design and construct a model for predictive analytics and model performance monitoring

Outline

Day 1

Introduction to Data Analytics Deployment and Performance Monitoring
Starting the journey: data-driven problem-solving approach
Model/algorithm storing, execution, and output data

Day 2

Predictive Analytics and Model Performance Monitoring
Workshop-style Learning

Tools

Python (Jupyter Notebook) and Power BI

Pre-Requisites

Participants should have at least 2 years of working experience with the following data analytics knowledge in part or whole:

Overview of data science techniques, process and technology
Data science consulting skills
Connecting business problems to data science
Managing analytics projects (both innovation cycle and deployment cycle)
Understand data science capabilities and its limitations
Implement and manage the data science process for innovation and deployment cycles
Advise and deliver high-quality data analytics projects

Who Should Attend

IT Business Analysts and professionals who would like a deeper dive into data analytics.

Mode of Training

On-campus

MS CATHERINE KHAW

Catherine Khaw is an evangelist for data and analytics literacy at economy, organisational and individual levels. She is the founder of DNA Capitals which drives competitive advantage for organisations in all industries through taking full advantage of the opportunities which arise from digitization and big data. As a data and analytics evangelist, she is an active member of Tech Talent Assembly (TTAB) association which nurtures tech talents for lifelong employability, learning and sharing.

Catherine was formerly the Practice Chief of Analytics & Intelligent System at NUS Institute of Systems Science (NUS-ISS), where she imparted her experience and knowledge to graduate students, business leaders and ICT practitioners. She also continues to serve as adjunct lecturer and coach to NUS ISS students and short course participants.

Course Date / Duration / Venue


Date	Duration	Venue
TBC	2 Days 9.00am to 5.30pm (Daily)	National University of Singapore University Town

Course Fees

	International Participant	Singapore Citizen¹ 39 years old or younger	Singapore Citizen¹ 40 years or older eligible for MCES²	Singapore PRs	Enhanced Training Support for SMEs³
Full Programme Fee	S$2,100.00	S$2,100.00	S$2,100.00	S$2,100.00	S$2,100.00
SkillsFuture Funding (Refer to Funding Page for Claim Period)	–	(S$1,470.00)	(S$1,470.00)	(S$1,470.00)	(S$1,470.00)
Nett Programme Fee	S$2,100.00	S$630.00	S$630.00	S$630.00	S$630.00
7% GST on Nett Programme Fee	S$147.00	S$44.10	S$44.10	S$44.10	S$44.10
Total Nett Programme Fee Payable, Incl. GST	S$2,247.00	S$674.10	S$674.10	S$674.10	S$674.10
Less Additional Funding if Eligible Under Various Scheme	–	–	(S$420.00)	–	(S$420.00)
Total Nett Programme Fee, Incl. GST, after additional funding from the various funding schemes	S$2,247.00	S$674.10	S$254.10	S$674.10	S$254.10

Main Links

Department of Statistics & Data Science

Block S16, Level 7, 6 Science Drive 2,
Faculty Of Science,
National University of Singapore
Singapore 117546