Current Courses: Overview and Objectives

Course Objectives

• Grasp the fundamentals of Python programming, including data types, control structures, and functions.
• Learn how to load, clean, and manipulate data using Pandas for effective data analysis.
• Learn to use NumPy for numerical operations and handling large datasets efficiently.
• Understand the use of Pandas for handling research problem datasets.
• Create a variety of static and interactive visualisations to represent data insights, covering Matplotlib and Plotly.
• Apply machine learning techniques using Scikit-Learn for predictive modelling.
• Implement testing framework, manage dependencies with virtual environment.
• Learn methods to ensure that research and analyses can be reproduced and validated by others.

Learning Objectives

<ul>
  <li>Understand the fundamental concepts and benefits of using NumPy for scientific computing.</li>
  <li>Create and initialize NumPy arrays from various data sources, including lists and files.</li>
  <li>Perform file operations such as saving and loading NumPy arrays to and from different file formats.</li>
  <li>Manipulate and analyze data using array attributes and methods.</li>
  <li>Execute arithmetic operations, including matrix and statistical operations, on NumPy arrays.</li>
  <li>Apply advanced techniques such as array slicing, indexing, and broadcasting to efficiently handle large datasets.</li>
</ul>