Blended Learning Programmes / Programmes / Course BL

Course BL

Overview

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Enquiry	Please email to iss-blendedlearning@nus.edu.sg.

This is an introductory course to help the non-technical users perform a variety of data analysis in order to derive factual insights and ultimately to gain experience in making evidence-based business decisions.

You will explore multiple statistical concepts and learn how to apply them to business use cases. You will work on cleaning and preparing the data for analysis and generating insights. You will experience the use of data visualisation to find answers to business questions. You will learn how to discover correlations in data and to build simple linear regression models. Finally, you will learn about supervised and unsupervised machine learning techniques. Here you will practice building classification trees to predict customer behavior or condition; and using cluster analysis methods to create customer groupings that would lead to more effective customer management and engagement.

All the topics taught will be delivered through a problem-based approach and active discussions that are driven by use of numerous business scenarios. Emphasis is placed on critical thinking, practice skills and practical knowledge with the use of software and tools only as delivery mechanisms.

This instructor-led training course is an invaluable introduction to data analysis and forms a part of a suite of courses designed to give a thorough grounding in Data Science.

Key Takeaways

At the end of the course, learners will be able to learn how to:

● Apply statistics to solve a variety of business problems.

● Compute and interpret data summaries- numerically as well as visually.

● Use visual data exploration to find answers to business problems.

● Present data visually for better understanding of relationships between variables.

● Statistically analyze whether there is a relationship between two variables and determine the size of the relationship.

● Predict one variable in terms of another to make improvement in business performance.

● Perform classification and prediction using decision tree modeling approach.

● Cluster data into homogenous subsets to enable focused group-based customer management.

Structure

● Course duration: 6 weeks online.

● Learners' time commitment: 3 to 4 hours per week.

● This course has 3 live sessions for group activities, discussions, feedback and interactions.

● Throughout the course, learners are expected to actively contribute to the group activities and online discussions, and are encouraged to apply the knowledge learnt.

Who Should Attend

This course is ideal for professionals in Singapore and around the world, as it is conducted entirely online. Whether you are a business professional beginning to analyse data and need a kickstart, aiming to learn business analysis from the ground up, or you are exploring career opportunities in business analytics, interested to learn how to make data-driven decision, or aspiring to gain practical skills and knowledge in using business analytics to solve real-life business problems, we encourage you to register.

Instructors

Mr. Charles PANG

Head, Graduate Programme Student Affairs

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Fees And Funding

Type of Learners	Course Fee	Total course fee payable, including GST
Learners residing in Singapore (SGD)	SGD 900	SGD 981
Learners residing outside Singapore (USD)	USD 700	USD 700

Things To Note

● Learners are expected to set aside time for group activities before and beyond the course.

● The NUS-ISS Certificate of Completion will be issued to learners who have met the course requirements successfully. This will include attending all synchronous Zoom sessions and completing the learning activities, workshops and assessments (where applicable).

● Read the terms and conditions of NUS-ISS Course Registration here.

● Read about NUS-ISS and Learner’s Commitment and Responsibilities here.

● All classes are subject to confirmation and NUS-ISS will send an acceptance email to learners one week prior to the commencement date.

● All responses to feedback and surveys conducted by NUS-ISS and its partners must be submitted by learners.

● All trainings and assessments will be delivered by NUS-ISS, as described in the course webpage.

● For general enquiries and feedback, please feel free to reach out to us via email at iss-blendedlearning@nus.edu.sg.

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