Module 6 Overview

Blockchain's applicability to information systems is vast and continues to evolve as the technology matures, and new use cases emerge. Its core strengths lie in its ability to provide transparency, security, and trust in data and transactions across various industries and sectors. However, the integration of blockchain into information systems requires a deep understanding of both blockchain technology and the specific requirements of the information system architecture for being developed or enhanced. Careful consideration of architectural factors and components is essential to ensure that blockchain solutions align with information systems goals effectively.

For the first time, we look at blockchain architectural design from system system-thinking perspective. In fact, the idea of system-thinking in blockchain architectural design offers a comprehensive understanding of the blockchain ecosystem and its interactions with various stakeholders and components for the learners.

This new educational solution satisfies the following properties:

1) Better understanding of complex interaction in blockchain ecosystems. It helps in identifying and comprehending the intricate relationships and dependencies between various participants, protocols, and technologies in blockchain.

2) Feedback loops in blockchain ecosystems where it can prevent unintended consequences and allow for better decision-making.

3) A comprehensive interdisciplinary collaboration across various domains, such as cryptography, economics, and computer science by promoting a shared understanding of the system's complexities.

4)  Long-Term sustainability in blockchain ecosystems. Integrating system-thinking model assists in planning for the future, including scalability, maintenance, and growth strategies

From the system-thinking blockchain architectural design perspective, all modules will be designed and developed to adhere the aforementioned properties.

In this module, we will cover the following topics:

  • Blockchain

Module Objectives

Upon the completion of this module, you will be able to:

  1. Compare and contrast contemporary machine learning techniques
  2. Analyze the applications of machine learning in the FinTech field
  3. Apply appropriate machine learning tools for vulnerability and risk assessment
  4. Develop machine learning-based solutions for FinTech problems.

Assigned Reading

Please check Module 06 and then the Learning section


Optional Reading

Please check Module 06 and then the Supplemental Resources  section


Assessment & Assignment

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