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Certificate Programs at SAE
50% Discount Offer - Limited Time Only
Certificate Programs at SAE
50% Discount Offer - Limited Time Only
Certificate Programs at SAE

Python for Biomedical Data Applications

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Course Overview

This course introduces the Python programming language to students and professionals in biomedical and healthcare fields with no prior programming experience. It focuses on using Python to analyze, visualize, and manage biomedical data, with the goal of improving decision-making and healthcare outcomes. The course will cover Python programming fundamentals, key libraries for data analysis (including Pandas and NumPy), data visualization, and basic statistical analysis, all within the context of biomedical applications.

Level Beginner

Duration 10 weeks.

SoftwarePython 3.13.3
(PyCharm IDE)

InstructorDr. Ganesh Naik, IHM

FeesAUD 1,000

What You’ll Learn

Upon successful completion of this course, students will be able to:

  • Understand the fundamentals of Python programming.
  • Set up a Python environment using Anaconda.
  • Import, export, and manipulate biomedical data using Python.
  • Perform descriptive statistical analysis using Python.
  • Create effective visualizations of biomedical data.
  • Apply Python to solve real-world biomedical data analysis problems.
  • Use Jupyter Notebooks to document and present the work clearly and effectively.

Who Should Enrol?

Biomedical students, healthcare professionals (doctors, nurses, pharmacists), medical researchers, public health workers, and anyone interested in applying Python to biomedical data.

Entry Requirements

No prior experience in programming or statistics is necessary. Basic computer literacy is expected.

Course Structure and Delivery

Online lectures, hands-on coding exercises, practical assignments, and a final project.

Acknowledgement of Country

IHM acknowledges the Traditional Owners of country throughout Australia and recognises their continuing
connection to land, waters and culture. We pay our respects to their Elders past, present and emerging.

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