Who should attend
The programme is recommended for anyone who desires a hands-on understanding of Python and Analytics, and is designed for those who have no prior programming knowledge.
Individuals who will derive a benefit from the programme may include:
- Managers across domains and industries, including digital marketing, product development or customer relationship managers who are interested in learning to solve business problems through data insights, and who wish to gain a competitive edge by acquiring the latest technology tool available.
- Analysts (business or financial) or software engineers who want to develop a foundation for a future in data science so that they could communicate better with managers/stakeholders.
- Small business owners or entrepreneurs who would like to understand data science and how to use or apply analytics in their business.
About the course
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 organization you work for, a competitive edge in the market.
The Python for Analytics programme will serve as the first step in your data science learning journey, and does not require you to have prior programming knowledge, as this programme will teach you these skills. Designed to provide you with a straightforward introduction to essential Python programming for analytics purposes, the programme will also teach you how to gain essential insights by evaluating data.
Python has become the most popular programming language in the data science world, and is used by global companies. Python has proven to be beneficial to financial advisors, data journalists, digital marketers, and product managers responsible for researching market opportunities.
- Module 1: Introduction to Python, Analytics, and Data Science
- Module 2: Data Type Conversion and Control Flow
- Module 3: Working with Built-in Compound Data Types
- Module 4: Functions, Methods, and Packages
- Module 5: Data Manipulation and Analysis with Pandas
- Module 6: Descriptive Analytics with Numerical Summary
- Module 7: Descriptive Analytics with Data Visualisation
- Module 8: Foundation of Predictive Analytics
Eli Yi-liang Tung is a Lecturer in the Department of Analytics and Operations at National University of Singapore (NUS). He is an enthusiastic teacher to advocate the use of Business Analytics in undergraduate business teaching. Currently, Eli is one of the core course instructors offering Python...
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. His research interests are in the domain of data-driven decision-making and optimization under uncert...
Videos and materials
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.