Course curriculum

    1. Welcome

    2. Course overview

    3. Syllabus

    4. Reading list

    5. How to use this course

    1. Defining Big Data

    2. Finding examples of Big Data

    3. 6 Vs of Big Data

    4. Data Quality and How Data Can be Shaped

    5. Data Processing Methods

    6. Big Data - Helpful Research Articles

    7. Different Types of Data Structures

    8. Introducing Structured, Unstructured and Semi-Structured Data

    9. Quantitative Data

    10. Qualitative Data

    11. Why Organisations Need a Big Data Strategy

    12. Advice from IBM and McKinsey on Designing a Big Data Strategy

    1. Structured Data

    2. Structured Data and Relational Databases

    3. Advantages and Disadvantages of Structured Data

    4. Summary of Structured Data and Helpful Links

    5. Semi-Structured Data

    6. Advantages and Disadvantages of Semi-Structured Data

    7. Summary of Semi-Structured Data

    8. Unstructured Data

    9. Advantages and Disadvantages of Unstructured Data

    10. Summary of Unstructured Data

    11. The Need for a Big Data Framework 1/3

    12. The Need for a Big Data Framework 2/3

    13. The Need for a Big Data Framework 3/3

    14. How to Choose a Big Data Framework

    15. Introducing Hadoop and Spark - Big Data Frameworks

    16. Hadoop

    17. Benefits of Hadoop

    18. Challenges of Hadoop

    19. Spark and the differences between Hadoop and Spark

    20. Benefits of Spark

    21. Challenges of Spark

    22. The Need for Data Architecture

    23. GDPR and Data Protection Act 2018

    24. Fines – implications of non-compliance with GDPR

    25. Data Governance - Data Protection

    26. ISO/IEC 27001

    1. Time Series Analysis

    2. Bayesian Classifiers

    3. Bayes Theorem 1/2

    4. Bayes Theorem 2/2 (Formula)

    5. Naïve Bayesian Classifier 1/2

    6. Naïve Bayesian Classifiers 2/2

    7. Decision Trees

    8. Linear Regression

    9. Machine Learning

    10. Data Mining

    11. Predictive Analytics

    12. Text Analytics

    1. Why Machine Learning Needs Big Data - Data Quality

    2. Why Machine Learning Needs Big Data - Relevance, Bias in Data

    3. How Machine Learning uses Big Data

    1. Preparation for the exam (Updated September 2021)

      FREE PREVIEW

    2. Sample Question Paper

    3. Sample Answer Paper

About this course

  • £395.00
  • 61 lessons

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