Data Science for Power Users

Overview

Overview

Duration 14 days
Course Time 9.00am - 5.00pm
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This course is delivered by Nanyang Polytechnic.

Predictive analytics generates future insights with a significant degree of precision based on historical data. Through this course, learners will demonstrate their competencies in developing a predictive analytics project in teams by applying data privacy and ethical principles in the collection, use and disposal of data. With the data collected, learners will demonstrate their competencies to impute data format, transform and reshape the business data before applying relevant predictive modelling techniques to predict the desired business outcomes. Learners will then perform data exploratory analysis to discover patterns and trends and develop data stories for an effective narrative and visual representation of their predictive analytics project.


Key Takeaways

Key Takeaways

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

  • Collect data from multiple sources using appropriate collection tools and techniques that comply with data and privacy ethics.
  • Perform data pre-processing techniques to impute data format, transform, reshape and protect the data in accordance with the business requirements and data protection principles.
  • Develop interactive and effective visualisations with a global perspective to address international and cultural differences, diverse needs and expectations of the key stakeholders using visualisation tools.
  • Perform data exploratory analysis to identify underlying data patterns, trends and analytical insights using visualisation tools.
  • Apply relevant predictive modelling techniques to predict the desired business outcomes to meet the service expectation of the key stakeholders.
  • Work collaboratively in a team to develop dashboards using data storytelling approach for an effective narrative and visual representation of their predictive analytics project.

Who Should Attend

Who Should Attend

This course is targeted at:

  • IT professionals with knowledge of databases and software development

Prerequisites
Basic Data Analytics


ICT and SS Competency Framework

ICT and SS Competency Framework

As part of the ICTCF, this course falls under the Data Science & AI functional cluster and tagged to the following competencies:
  • Data Science & AI: Data Collection
  • Data Science & AI: Data Quality
  • Data Science & AI: Exploration Anaysis
  • Data Science & AI: Statistical Techniques
  • Data Science & AI: Machine Learning
  • Data Science & AI: Visual Analytics Principles
  • Data Science & AI: Charts & Dashboard
  • Data Science & AI: Data Storytelling
  • Data Science & AI: Scripting
The course is mapped to the following job roles:
  • GPO

Course Structure

Course Structure

This course will cover the following topics:

  • Introduction to Data Visualisation
  • Preparing Data for Analysis
  • Visualising Data
  • Create data-driven story
  • Advanced Interactive Report
  • Introduction to Python
  • Descriptive Statistics
  • Data Analysis using Python
  • Data Preparation Techniques
  • Introduction to Machine Learning Techniques
  • Machine Learning
  • Feature Engineering
  • Model Comparison & Evaluation
  • Natural Language Processing
  • Predictive Modelling Project

Instructors

Instructors


Fees

Fees


Full Fee

Full course fee

S$2400

7% GST on nett course fee

S$168

Total nett course fee payable, including GST S$2568

 
NOTE: Funding is available for this course. Please email to Aloysius or Angeline to find out about the updated course fee funding breakdown and eligibility.


How To Register

How To Register


Agency-sponsored

Step 1 Apply through your organisation's training request system.

Step 2 Your organisation's training request system (or relevant HR staff) confirms your organisation's approval for you to take the course.

Your organisation will send registration information to the academy.

Organisation HR L&D or equivalent staff can click here for details of the registration submission process.


Step 3 The Digital Academy will inform you whether you have been successful in enrolment.