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

STARTS ON

26 June 2024

Course Duration

DURATION

3 months, online
8-10 hours per week

Course Fee

PROGRAMME FEE

US$1,699 and get US$169 off with a referral

Course Information Flexible payment available
Course Fee

For Your Team

Enrol your team and learn with your peers

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Applications close on 21 June 2024

Apply before 21 June 2024 and avail early bird tuition assistance of USD50. Use code APAC50ALL9153 while applying.

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

Pre-Recorded Video Lectures* from NUS faculty with for self-paced learning interspersed with live lectures from renowned NUS faculty and industry practitioners

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

2 faculty / program leader live sessions

Progressive capstone project

The programme highlights mentioned above are subject to change based on faculty availability and the desired outcomes of the programme.
*This programme is primarily self-paced online with some live sessions conducted by programme faculty. The availability of post-session video recordings is at the discretion of the faculty members, and Emeritus or the institute cannot guarantee their availability. We have a curated panel of distinguished industry practitioners who will conduct weekly live doubt-clearing sessions.
**Assignments will be graded by industry practitioners who are available to support participants in their learning journey, and/or by the Emeritus grading team. The final number of quizzes, assignments, and discussions will be confirmed closer to the start of the programme.

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

*This programme is primarily self-paced online with some live sessions conducted by programme faculty. The availability of post-session video recordings is at the discretion of the faculty members, and Emeritus or the institute cannot guarantee their availability. We have a curated panel of distinguished industry practitioners who will conduct weekly live doubt-clearing sessions.
**Assignments will be graded by industry practitioners who are available to support participants in their learning journey, and/or by the Emeritus grading team. The final number of quizzes, assignments, and discussions will be confirmed closer to the start of the programme.
The bonus content on Generative AI is optional and does not count towards your final evaluation.

Technological Tools

Numpy

Pandas

Matplotlib

Seaborn

Python

All product and company names mentioned in this material are trademarks or registered trademarks of their respective holders. Their use does not imply any affiliation with or endorsement by them.
The tools will be taught by teaching faculty, industry practitioners, or linked to relevant knowledge bases for your reference and self-guided learning

Case-studies

Newsvendor case:

Case Study using Python programme for profitability analysis.

Singapore's Major Public Hospitals:

Analysis of patient dataset of Singapore's major public hospitals.

Condo market in Singapore:

Analysis of condo prices and market in Singapore using data visualisation.

Monthly Salary Distribution:

Analysis of the monthly salary of full-time employees using Python simulation to perform random sampling.

Generative AI by Emeritus (Optional)

●   Module 1: Introduction to Generative AI

●   Module 2: Generative AI Models

●   Module 3: Working with Generative AI

●   Module 4: Coding

Masterclass to address cutting-edge tools and latest developments

Note: The above highlights are included as a part of bonus content. The bonus content is optional and does not count towards your final evaluation.
Please note that the bonus content is provided solely for self-study and does not come with any assistance
Please note that the bonus content is provided by Emeritus and is not part of the NUS Business School syllabus solely for self-study and does not come with any assistance.” or similar, under the section”Generative AI by Emeritus (Optional).

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.

1st

NUS (Asia) 2023

QS World University Ranking

8th

NUS (Global) 2024

QS World University Ranking

Programme Faculty

Faculty Member Xiong Peng

Xiong Peng

Senior Lecturer 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

Lecturer 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

Note - Programme Faculty for the live sessions might change due to unavoidable circumstances, and revised details will be shared closer to the programme start date.

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

*Although no prior coding experience is required, non-tech participants are encouraged to put additional effort and complete the set of pre-readings provided to prepare for the course.

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 Participant Profiles

Countries

Work Experience

Industries

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.

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

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

Download Brochure

All certificate images are for illustrative purposes only and may be subject to change at the discretion of the Asian Institute of Management.
*Emeritus or the institute does not guarantee availability of any live faculty session recordings.

Emeritus Career Services

Stepping into a business leadership career requires a variety of job-ready skills. Below given services are provided by Emeritus, our learning collaborator for this program. The primary goal is to give you the skills needed to succeed in your career; however, job placement is not guaranteed.

Emeritus provides the following career preparation services:

●   Resume building videos

●   Interview preparation videos

●   Linkedln profile building videos

●   Interview guidebooks

●   Glossary of resume templates

Please note:

NUS or Emeritus do not promise or guarantee a job or progression in your current job. Career Services is only offered as a service that empowers you to manage your career proactively. The Career Services mentioned here are offered by Emeritus. NUS is not involved in any way and makes no commitments regarding the Career Services mentioned here

Limited seats are available.
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Flexible payment options available. Learn more.