Data Mining and Analytics


Data Mining and Analytics

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  • Study Hours

    Study Hours

    150 Hours

  • Total Fee

    Total Fee


  • Delivery



  • Modality


    Self Paced

Programme Overview

You will explore the background of data science, fundamentals of data mining, and data analytics concepts and techniques in business Intelligence. The goal is for you to have a solid foundation in how data mining and analysis works together by understanding data patterns, structures, and useful information to solve real-world problems. You will demonstrate proficiency in programming skills (i.e.: Python, SQL, R or Java) to use algorithms in different languages to build data models, create testing strategies, and analytical methods. As a result, you will gain knowledge of data processing, design, and implementation of data warehouse, customer relationship management (CRM), and OLAP (online analytical processing) systems for emerging applications examples (i.e. eCommerce platforms). 

Learning Outcomes

  1. Describe the functionalities of data mining and data analytics and how these technologies work in overall Business Intelligence to benefit a business.
  2. Describe different data mining solutions that can be implemented through algorithms to solve problems using the appropriate programming language such as Python, SQL, R Minitab, or SAS. 
  3. Discuss how reporting dashboards for data analysis are designed based on techniques, algorithms, modelling strategies, and analytical methods.
  4. Summarise how business decisions are made after reviewing examples and data trends to identify potential outcomes, exceptions, or patterns to solve a real-world problem or circumstance. 
  5. Report on how to transform data from one format to another in relational databases for overall data management and its use in data warehousing, CRMs, etc.

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