Python For Analytics

Gain hands-on Python coding skills for practical business applications. No prior programming knowledge is required.

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Course Dates


31 March 2023

Course Duration


3 months, online
8-10 hours per week

Course Fee


US$1,500 or get US$150 off with a referral

Course Information Flexible payment available
Course Information Special group enrolment pricing

Free 6-Months Access to Emeritus Insights

This programme features 6 months of free Premium Access to Emeritus Insights—a mobile app with 5,000+ bite-sized, business-focused videos to help you meet your daily learning goals on the go.

Applications close on 30 March 2023

Apply before 30 March 2023 and avail early bird tuition assistance of USD 100.
Use code NUS100TA while applying.

WhatsApp an Advisor on +65 8014 3066
Have questions? Our Advisor will assist you promptly.

What Will This Programme Do For You?

Following successful completion of the Python for Analytics programme, participants will be able to:

ollowing successful completion of the Python for Analytics programme, participants will be able to:

Programme Learning Journey

118 Recorded Video Lectures with Faculty

118 Recorded Video Lectures with Faculty

18 Live online Office hour sessions with Programme Leaders

18 Live online Office hour sessions with Programme Leaders

13 Discussion Boards

13 Discussion Boards

10 Assignments

10 Assignments

10 Activities

10 Activities

Hands-on coding with Python

Hands-on coding with Python

Programme Modules

The programme is divided into two sections:
The first section features 5 modules on Python Programming and concludes with a Lab Week (The initial two weeks of learning will be warm-up coding practices before the actual programme starts). The second section comprises modules 7-10, centring on Data Analysis with Python.
    • Introduction to Programming and Business Analytics
    • Objects, Variables and Assignment Statements
    • Coding Style and Jupyter Notebook
    • Data Types and Data Type Conversion
    • Conditional Statements
    • Strings
    • Iterations and Loops
    • Lists
    • Dictionaries
    • Tuples
    • Functions
    • Modules
    • Introduction to Packages
    • NumPy
    • Datasets and Types of Variables
    • Constructing, Indexing, and Slicing a pandas.DataFrame
    • Accessing Columns and Rows in a pandas.DataFrame
    • Working with Subsets
    • Filtering Data
    • Lab Week Assignment
    • Numerical Summaries
    • Data Visualisation Using Packages
    • Data Manipulation Using Pandas
    • Visualisation Techniques
    • Time Trends
    • Relationship between Variables
    • Random Variables
    • Continuous Random Variables and Their Distributions
    • Discrete Random Variables and Their Distributions
    • Probability Calculations Using SciPy
    • Sampling Distribution
    • Samples and Populations
    • Decision Analysis

Technological Tools





Note: All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.

About NUS Business School

For more than 50 years, NUS Business School has offered a rigorous, relevant and rewarding business education to outstanding students from across the world.

Founded in the same year that Singapore gained independence, NUS Business School stands today among the world’s leading business schools. It is distinctive for offering the best of global business knowledge with deep Asian insights, preparing students to lead Asian businesses to international success and to help global businesses succeed in Asia.


NUS (Asia) 2022

QS World University Rankings



Financial Times Global Rankings 2021

Programme Faculty

Faculty Member Xiong Peng

Xiong Peng

Faculty at NUS Business School

Xiong Peng is currently a Lecturer in the Department of Analytics & Operations, NUS Business School. Prior to joining NUS Business School, he was a research staff at Texas A&M University... More info

Faculty Member Eli Yi-Liang Tung

Eli Yi-Liang Tung

Faculty at NUS Business School

Eli Yi-Liang Tung is a Lecturer in the Department of Analytics and Operations at NUS Business School. As one of the core course instructors offering Python programming at NUS Business School... More info

Why Enrol for the Python For Analytics Programme?

In current global economies, data has become the foundation of solving business problems or making critical decisions. Data analytics empowered by Python programming skills will provide you, as a professional, as well as the organisation you work for, a competitive edge in the market.

The Python for Analytics programme serves as a powerful tool for your professional development. Designed to provide you with a straightforward introduction to coding with Python, the programme will also teach you how to apply Python functions and packages to evaluate data and extract essential insights.

Python has become the most popular programming language in the data science world, and is used by global companies.* Python has also proven to be beneficial to financial advisors, data journalists, digital marketers, and product managers responsible for researching market opportunities.
(*Source – IEEE Spectrum)

Who is this Programme for?

Professionals who want a hands-on understanding of Python and Analytics may benefit from the programme, including.

  • Managers across domains and industries, including digital marketing, product development and CRM
  • Business or financial analysts, software or systems engineers
  • Small business owners and entrepreneurs, career changers looking to hone their data science skillset

Programme Testimonials

The programme has practical examples and really helpful Professors & Programme Leaders

— Corrine Png, Regional Head of Equities Research, AIA Investment Management

Recorded video is available 24/7 and this this programme is suitable for working professionals.

— Joanna Gan, Assistant Manager, SIT

The programme structure is built to accommodate for students without any programming background.

— Meng Meng Wong, Process Engineer, Micron Semiconductor Asia Pte Ltd

Lecturers and tutors are experienced and supportive and support team is also very helpful.

— Wai Ho Man, Audit senior, PwC Hong Kong

You get accessibility to learning material, videos and assignments until a year after the course is completed.

— Satya Sreekanth, Vice President, Bank of America

Read about participants who have completed the programme and shared their certificates on LinkedIn.
Click on the certificate to see what they have to say about the programme.

(These are LinkedIn posts & will require you to log in to LinkedIn to see them).

Past participants of Emeritus work at

Note: *All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.

Past Participant Profiles


Work Experience


Seeking Employer Assistance

When you make the decision to further your professional development, you are not only making a commitment to your own career advancement, but to the success of your organisation. And because you’ll be enhancing the skills and knowledge you will use to impact the way you do business, asking your employer to help fund your continuing education is a smart move.

Receiving financial assistance from an employer is more common than you may think, but it can feel rather intimidating. To help, here are some simple steps you can follow to make the request:

Do Your Research
Prior to asking for financial assistance, you need to make sure you can justify your programme of choice and how it will enhance your work performance.

Showcase Tangible Benefits
Get specific—discuss with your employer how your newly gained expertise will directly improve a process, service, strategy or any other aspect of your organisation that needs improving.

Start the Conversation
Don’t wait for your employer to broach the subject and present you with potential professional development opportunities. Once you’ve finished your research, send your employer an email to set up a meeting to discuss the programme you have in mind.



Upon successful completion of the programme, participants will be awarded a verified digital certificate by NUS Business School.

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Early registrations are encouraged. Seats fill up quickly!

Flexible payment options available. Learn more.