UWA PLUS

Data Analytics in Portfolio Investments

In the current globalized market, the ability to extract important information from large financial datasets is the key for a fund manager to make decisive investment decisions.

This micro-credential is designed specifically to equip you with the specialised skill set required in financial data analytics to help make informed investment decisions.

Working under the close supervision of a world-class scholar from the UWA Business School, participants will gain hands-on coding experience using the Python programming language, and extract important information from large financial datasets commonly used by fund managers in the real-world.

Recently voted as the most sought-after programming language in the world (www.codingdojo.com), Python is perfectly placed to provide participants with the cutting edge and know-how in financial data analytics and handling big data.

Upon successful completion, you'll receive:

  • Three PD Points  - stackable for unspecified academic credit in award courses
  • A Certificate of Achievement
  • A UWA Plus Professional Development Transcript, listing all successfully completed micro-credentials
Delivery mode
On campus
Course dates
18 March 2022 - 29 April 2022
Class to meet every Friday for 6 weeks: (except Good Friday 15 April)
Venue: UWA Business School Trading Room
Time: 5:30pm - 8:30pm (3 hours) per week
Duration
6 weeks
Effort
75 hours (including 18 contact hours)
Cost
$1,600 inc. GST
Critical information summary
  FINAM501 - Critical information summary [PDF, 246KB]

 

Students collaborating in data lab 

What you'll learn

Understand and apply the core analytic concepts in the Python programming environment

Efficiently use the full breadth of libraries (including Pandas and Numpy) in Python

Create, manipulate and extract important information from large financial datasets

Construct characteristic-based portfolio and investment strategies

Keyboard 

Why study this course?

  • This course is the first of its kind in Australia, specifically geared towards helping you develop the necessary skills required to efficiently extract important information from large financial datasets commonly used by fund managers in the real-world.
  • During the course you will have access to UWA's state-of-the-art Rosemarie Nathanson Financial Markets Trading Room within the UWA Business School.
  • You will learn to efficiently solve real-world problems in finance and investment using Python

Who should study this course

  • Corporate partners looking to equip their staff with the latest know-how in financial analytics
  • Professionals seeking to advance their careers and develop specialised skills in financial analytics
  • Consultants seeking to leverage Python's capabilities to solve business and real-world problems
  • Recent graduates seeking to gain a competitive edge and enhance their employability
  • Continuing postgraduate students looking to equip themselves with financial analytics
  • Third-year students eager to learn coding and solve real-world financial problems

How does it work?

  • 6 face-to-face intensive lectures that will run for a total of 18 class-time hours in UWA Business School Trading Room
  • Participants will gain hands-on coding experience using the Python programming language, and extract important information from large financial datasets commonly used by fund managers in the real-world
  • Participants are assessed via 4 mini assignments and 1 major individual project

What's next after this course?

  • Upon successful completion of the course, participants are expected to enjoy a competitive edge in terms of employability,and advancing in their careers in fund management and portfolio allocation
  • Stackable toward unspecified partial credit towards a unit when enrolling in the Master of Applied Finance (or alternative course if approved).

    Note – this will require successful completion of another 3 PD Points. PD Points earned via micro-credentials cannot be used as credit towards a course you are already enrolled in.

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Applications are open.

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