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In diesem Kurs gibt es 4 Module
Artificial Intelligence (AI) is rapidly reshaping the financial services landscape. From fraud detection and algorithmic trading to customer service chatbots and credit scoring, AI is at the heart of a new era in finance. This course is designed to give you a clear, practical understanding of how AI works, what it enables, and how it’s transforming the way financial institutions operate.
Through real-world examples, case studies, and engaging learning activities, you’ll gain insights into the key technologies that make AI possible, including machine learning, deep learning, and natural language processing, and see how they are applied across core functions in banking, fintech, and asset management. You’ll also explore how data drives these systems, the different learning methods AI uses, and the implications for strategy, governance, and ethics.
Whether you’re a financial professional, policymaker, or simply curious about the future of finance, this course will equip you with the knowledge and confidence to engage in AI-related conversations and decision-making. No programming background is required, just an interest in how technology is shaping the future of financial services.
By the end of the course, you will be able to:
• Understand the foundational technologies that underpin Artificial Intelligence (AI), including Machine Learning, Natural Language Processing, and Deep Learning.
• Explore the central role of data in powering AI systems, and the key learning methods used to train them.
• Identify how AI is applied in financial services, including use cases such as fraud detection, credit scoring, customer service, and algorithmic trading.
• Critically evaluate the risks, limitations, and ethical challenges associated with deploying AI in financial services.
This course is the first in the AI in Financial Services: Foundations through Future Trends specialization. It provides the essential groundwork for understanding how AI works and why it matters in finance. After completing this course, we recommend continuing with 'Designing the Future of Finance' and 'Open Data and Intelligent Finance' courses to explore how AI intersects with Open Finance, embedded systems, and intelligent, ethical financial innovation.
This module provides a foundational introduction to Artificial Intelligence and its transformative role in financial services. It also offers an overview of the course structure, highlighting key topics and how each module will build your understanding. You'll explore key AI technologies: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotics, and Expert Systems. These insights will prepare you to recognise how AI is reshaping financial operations, services, and decision-making processes.
Das ist alles enthalten
4 Videos7 Lektüren1 Aufgabe4 Plug-ins
Infos zu Modulinhalt anzeigen
4 Videos•Insgesamt 6 Minuten
Welcome from Professor Martin Schmalz•2 Minuten
What is AI?•2 Minuten
How NLP powers language-based technology•1 Minute
How Expert Systems replicate human reasoning•1 Minute
7 Lektüren•Insgesamt 96 Minuten
Your learning journey •15 Minuten
Before you begin: reflect on your learning goals •10 Minuten
Important note about course communication•1 Minute
Introducing AI in Financial Services•10 Minuten
What is Natural Language Processing (NLP)•30 Minuten
What are Expert Systems•20 Minuten
Conclusion: Inside the AI Toolbox•10 Minuten
1 Aufgabe•Insgesamt 20 Minuten
Module quiz•20 Minuten
4 Plug-ins•Insgesamt 60 Minuten
What is Machine Learning•15 Minuten
What is Deep Learning•15 Minuten
What is Computer Vision•15 Minuten
What is Robotics and Robotic Process Automation (RPA)•15 Minuten
Data and AI Learning Methods
Modul 2•3 Stunden abzuschließen
Moduldetails
This module explores the vital role of data in Artificial Intelligence and the different learning methods that AI systems use to generate insights and predictions. You’ll examine key data types, the characteristics of big data, and the core machine learning paradigms used in financial applications.
Das ist alles enthalten
6 Videos9 Lektüren1 Aufgabe4 Plug-ins
Infos zu Modulinhalt anzeigen
6 Videos•Insgesamt 10 Minuten
Data: the fuel that powers AI •2 Minuten
Challenges of working with large-scale data in finance•1 Minute
Comparing traditional computing and AI•3 Minuten
Supervised Learning: a loan repayment example•1 Minute
Unsupervised Learning: a segmentation example•1 Minute
Reinforcement Learning: a customer engagement example•1 Minute
9 Lektüren•Insgesamt 100 Minuten
Introduction•10 Minuten
Conclusion and reflection•20 Minuten
Traditional computing approaches •15 Minuten
Artificial Intelligence approaches •10 Minuten
Comparing traditional computing and AI - summary•10 Minuten
Conclusion and reflection•20 Minuten
Supervised Learning•5 Minuten
Unsupervised Learning •5 Minuten
Reinforcement Learning•5 Minuten
1 Aufgabe•Insgesamt 20 Minuten
Module quiz•20 Minuten
4 Plug-ins•Insgesamt 70 Minuten
Data Paradigms and Data Types •20 Minuten
Challenges of collecting, managing and using large data sets •15 Minuten
Choose the right computing approach •15 Minuten
Which type of learning is it? •20 Minuten
Applying AI in financial services
Modul 3•4 Stunden abzuschließen
Moduldetails
This module demonstrates how AI is applied across four core areas of financial services: fraud detection, credit scoring, customer service, and algorithmic trading. You’ll explore real-world use cases to understand how AI adds value, the models and data behind it, and the challenges institutions face when deploying these technologies.
Das ist alles enthalten
5 Videos9 Lektüren1 Aufgabe4 Plug-ins
Infos zu Modulinhalt anzeigen
5 Videos•Insgesamt 6 Minuten
Applying AI in Financial Services•2 Minuten
How AI enhances fraud detection•1 Minute
Why credit scoring needs a rethink•1 Minute
Personalisation and the future of customer service•1 Minute
AI at speed - the rise of algorithmic trading•1 Minute
9 Lektüren•Insgesamt 175 Minuten
Reflect on your own experience •15 Minuten
How AI-based fraud detection works •20 Minuten
Real-world examples of AI-based fraud detection •20 Minuten
How AI models assess credit risk •20 Minuten
Real-world examples of AI credit scoring •20 Minuten
How chatbots are driving increased personalisation •20 Minuten
Real-world examples of AI driven personalisation in finance •20 Minuten
How Algorithmic Trading works •20 Minuten
Real-world examples of AI in Algorithmic Trading •20 Minuten
1 Aufgabe•Insgesamt 20 Minuten
Module quiz•20 Minuten
4 Plug-ins•Insgesamt 60 Minuten
Challenges and considerations for AI-based fraud detection •15 Minuten
Challenges and considerations for AI-based credit scoring •15 Minuten
Challenges and considerations for chatbots in finance •15 Minuten
Challenges and considerations for AI in Algorithmic Trading •15 Minuten
Review, reflect, and demonstrate your learning
Modul 4•4 Stunden abzuschließen
Moduldetails
In this final module, you’ll consolidate your learning and apply your knowledge through a peer-reviewed written assignment. You’ll reflect on key concepts, revisit course highlights, and explore the real-world implications of AI in financial services.
Das ist alles enthalten
1 Video4 Lektüren1 Aufgabe1 peer review
Infos zu Modulinhalt anzeigen
1 Video•Insgesamt 2 Minuten
Summary•2 Minuten
4 Lektüren•Insgesamt 55 Minuten
Key takeaways and reflection•15 Minuten
Bibliography and further reading•10 Minuten
Written assignment information•20 Minuten
Next steps•10 Minuten
1 Aufgabe•Insgesamt 40 Minuten
Course quiz•40 Minuten
1 peer review•Insgesamt 120 Minuten
Written assignment submission•120 Minuten
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What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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