Machine Learning

This module provides a hands-on introduction to machine learning, starting with core concepts and progressing to practical case studies using real-world data. It covers key machine learning algorithms, model design, and deployment, with a strong focus on data analytics and modern tools for machine learning.

Learning Objectives

I have learned how to :

  • Identify and discuss the key professional, ethical, legal, and societal issues that arise in the field of machine learning.
  • Evaluate the suitability and limitations of various datasets when applying machine learning algorithms.
  • Implement machine learning solutions to practical problems and critically assess their performance in situations involving risk or uncertainty.
  • Develop and implement the skills required to be an effective member of a development team in a virtual professional environment, adopting real-life perspectives on team roles and organization.

Artefacts and Reflections

Artefacts.

Find all the artifacts demonstrating my development throughout the module, and more specifically the Collaborative Discussions, Team Projects, Individual Projects, and E-Portfolio ActivitiesHere

Individual Reflection

This is my reflection piece on:

  • The artefacts that I developed during this module.
  • My contributions to and experience throughout the Development Team Project.
  • My understanding of the different Machine Learning Algorithms covered in this module.
  • The impact on my professional/personal developmentHere

Professional Skills Matrix and Action Plan

I have gained and improved several valuable skills from the Machine Learning module.

  • Key Machine Learning Algorithms and Techniques.
  • How to use tools such as Python Programming for Machine Learning
  • Working effectively with a team.
  • How to implement Machine Learning and Data Analytics in Real World applications.
  • How to build and evaluate a neural network in Machine Learning.

I can apply all these skills at my workplace and in Research. However, I still need to work on more case studies involving the implementation of machine learning algorithms to expand my Data Science Portfolio and improve my skills as a Data Professional.