FINTECH
AI & DATA SCIENCE IN FINTECH
About Module IV
Module IV introduces artificial intelligence, data science, big data, cloud computing, machine learning, Python, visual analytics, automation, IoT and generative AI. Through practical examples and SME stories, learners explore business applications, implementation choices, ethical risks, responsible AI and the EU AI Act, ending with cross-sector use cases in HR, marketing and education.
What You Will Learn
After the end of Module I, you will be able to:
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Knowledge 5
Understand fundamental AI concepts and terminology by demonstrating comprehensive understanding of core theories, principles, terminology, and contextual relevance in the domain.
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Knowledge 5
Explain foundational AI and Data Science concepts relevant to finance by demonstrating comprehensive understanding of core theories, principles, terminology, and contextual relevance in the domain.
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Knowledge 5
Describe the role of Big Data, Cloud Computing, and IoT in financial services by demonstrating comprehensive understanding of core theories, principles, terminology, and contextual relevance in the domain
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Knowledge 5
Recognise the power and limits of Generative AI (e.g. ChatGPT, Claude, Gemini, Midjourney) by demonstrating comprehensive understanding of core theories, principles, terminology, and contextual relevance in the domain.
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Knowledge 5
Understand the difference between Python and RPA tools for automating workflows through structured application of tools, analytical reasoning or methodologies.
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Knowledge 6
Explain how Machine Learning and Visual Analytics support decision-making by demonstrating comprehensive understanding of core theories, principles, terminology, and contextual relevance in the domain.
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Skill 6 / Responsibility & Autonomy 6
Integrate IoT and cloud services in data-driven financial systems by making informed decisions, managing assigned tasks independently or collaboratively, and evaluating the quality of outcomes within a defined scope of responsibility.
Contents
- 10 Learning Topics
- 21 lessons
Learning Topic 1: Introduction to AI and Data Science
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LESSON 1.1 – What Is Artificial Intelligence? [Intermediate]
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LESSON 1.2 – The Present and Future of AI [Intermediate]
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LESSON 1.3 – Types of AI by Capability [Intermediate]
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LESSON 1.4 – Types of AI by Functionality [Intermediate]
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LESSON 1.5 – Concept of Data Science [Intermediate]
Learning Topic 2: Big Data & Cloud Computing in Finance
Learning Topic 3: Machine Learning Concepts and Applications
Learning Topic 4: Introduction to Python for Business Users
Learning Topic 5: Visual Analytics and Dashboard Tools
Learning Topic 6: Robotic Process Automation (RPA) & Chatbots
Learning Topic 7: The IoT Ecosystem in Financial Services
Learning Topic 8: Generative AI – LLMs, Image Models and Beyond
Learning Topic 9: Risk, Ethics, and Responsible AI Use
Learning Topic 10: Capstone: Use Cases in HR, Marketing, and Education
References and Final Assessment
Download MODULE IV
Disclaimer. Material for Educational Purpose Only
The content on this platform is provided solely for educational and informational purposes and does not constitute financial, investment, legal, or tax advice. We do not recommend or endorse any specific cryptocurrency, financial product, or investment strategy. Cryptocurrencies are volatile and high-risk assets, and any investment decision is made at the user’s own responsibility. Users should seek advice from a qualified financial advisor before making financial decisions.
