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·Sign up for micro credit courses linking the degrees of the world's top universities
·Know and apply for College
·Pay attention to "one knowledge talk" and watch the experience and wisdom shared by education and knowledge workers
·Pay attention to "one knowledge focus" and timely obtain University news and higher education information
Course Details:
This course is designed for working professionals, aiming to help you master the applications of big data in the financial sector. You will learn how to leverage data analytics to make smarter investment decisions, manage risks, and optimize financial operations.
Course Highlights:
Taught by Industry Experts – Our instructors are experienced fintech professionals who will share their practical insights and industry expertise.
Hands-on Learning Approach – Gain valuable experience through case studies, practical projects, and simulation exercises.
Flexible Learning Format – Our online learning platform allows you to study anytime, anywhere, and progress at your own pace.
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| Week 1 / Module 1: Introduction to Big Data and Its Applications in Finance |
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| 🕒 Session 1: Concepts and Characteristics of Big Data (2 hours) |
| 🕒 Session 2: Applications of Big Data in the Financial Industry (2 hours) |
| 🕒 Session 3: Data Challenges and Opportunities in Finance (2 hours) |
└───────────────────────────────────────────────┘
┌───────────────────────────────────────────────┐
| Week 2 / Module 2: Financial Data Analysis Tools and Techniques |
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| 🕒 Session 1: Python and R Basics (2 hours) |
| 🕒 Session 2: SQL Database Querying and Analysis (2 hours) |
| 🕒 Session 3: Data Visualization Tools (e.g., Tableau, Power BI) (2 hours)|
└───────────────────────────────────────────────┘
┌───────────────────────────────────────────────┐
| Week 3 / Module 3: Machine Learning Applications in Financial Forecasting|
├───────────────────────────────────────────────┤
| 🕒 Session 1: Fundamentals of Machine Learning (2 hours) |
| 🕒 Session 2: Common Algorithms: Regression, Classification, Clustering (2 hours)|
| 🕒 Session 3: Financial Forecasting Cases: Stock Prices, Risk Assessment (2 hours)|
└───────────────────────────────────────────────┘
┌───────────────────────────────────────────────┐
| Week 4 / Module 4: Risk Management and Fraud Detection |
├───────────────────────────────────────────────┤
| 🕒 Session 1: Basic Concepts and Methods of Risk Management (2 hours) |
| 🕒 Session 2: Applications of Big Data in Risk Modeling (2 hours) |
| 🕒 Session 3: Fraud Detection Techniques and Case Studies (2 hours) |
└───────────────────────────────────────────────┘
┌───────────────────────────────────────────────┐
| Week 5 / Module 5: Blockchain Technology and Cryptocurrencies |
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| 🕒 Session 1: Principles and Applications of Blockchain (2 hours) |
| 🕒 Session 2: Mechanisms of Cryptocurrencies (2 hours) |
| 🕒 Session 3: Future Trends of Blockchain in Finance (2 hours) |
└───────────────────────────────────────────────┘
┌───────────────────────────────────────────────┐
| Week 6 / Module 6: Future Trends in FinTech |
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| 🕒 Session 1: Applications of AI and IoT in Finance (2 hours) |
| 🕒 Session 2: Trends in Cloud Computing and Big Data Integration (2 hours)|
| 🕒 Session 3: Career Opportunities in the FinTech Industry (2 hours) |
└───────────────────────────────────────────────┘
Instructors:
Dr. Lee Chen Wei – Head of the Fintech Department at Malaysia University of Science and Technology, with over 15 years of experience in the financial industry, specializing in big data analytics and machine learning applications in finance.
Prof. Tan Wei Ming – Senior fintech consultant with extensive experience in international financial institutions, specializing in blockchain technology and cryptocurrency.
Upon successful completion of this course, you will receive:
1. A micro-credential certificate issued by Al-Madinah International University.
2. 6 transferable credits toward the Bachelor's Degree in Business Analytics.
Download course outline