Machine Learning


Machine Learning

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  • Study Hours

    Study Hours

    150 Hours

  • Total Fee

    Total Fee


  • Delivery



  • Modality


    Self Paced

Programme Overview

You will gain foundational knowledge on the importance of machine learning in artificial intelligence and explore modern algorithms in machine learning, focusing on practical applications to understand how to structure data into models that can be created and utilised. Throughout the course, there will be a core emphasis on how to understand the components needed when using data and information to develop such as software libraries, regression, classification, mixture models, neural networks, deep learning, ensemble methods and reinforcement learning. In addition, you will have knowledge of machine learning techniques and how they can be applied in various processes and real-world solutions. 

Learning Outcomes

  1. Analyse the stages and steps of machine learning, its components, and how it is essential for overall Artificial Intelligence.
  2. Review various algorithms in machine learning for user data patterns, predictions and other concepts needed to solve business problems. 
  3. Examine how to determine what machine learning algorithms to use by understanding requirements for application design and implementation plans by reviewing business examples such as autonomous driving, robotics, and classification.
  4. Create a solution using machine learning tools, algorithms, components, and data to make recommendations by training a model.
  5. Report on how to use an algorithm to solve problems in business through optimisation, training data models, understanding trends in data and planning for implementation and usage. 

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