• Clearly articulate and apply core concepts in big data analytics and explain cutting-edge technologies for processing and analyzing large datasets.
• Develop proficiency in statistical methods and relevant machine learning algorithms.
• Apply regression models, clustering, and predictive analytics on economic, financial and business datasets.
• Balance theoretical understanding with practical application of statistical methods and machine learning algorithms.
• Demonstrate that they have acquired skills for effective communication through data visualization and present findings to diverse stakeholders, including investors and policymakers.
• Demonstrate they master the art of storytelling through data visualization to effectively communicate complex findings.
• Discuss ethical issues in Big Data use in economics and finance.
• Explore privacy concerns, data security, and regulatory frameworks.
• Proactively address ethical issues and privacy concerns in Big Data, preparing for future regulatory changes.
• Examine real-world applications in financial markets, risk management, and investment analysis.
• Handle real-world projects simulating economic and financial scenarios.
• Collaborate on industry-specific applications using Big Data tools.

Upon completion of this course, participants will be able to:

Big Data Fundamentals:

• Clearly articulate and apply core concepts in big data analytics.
• Explain cutting-edge technologies for processing and analyzing large datasets.

Statistical Techniques and Machine Learning:

• Develop proficiency in statistical methods and relevant machine learning algorithms.
• Apply regression models, clustering, and predictive analytics on economic, financial and business datasets.
• Balance theoretical understanding with practical application of statistical methods and machine learning algorithms.

Data Visualization and Interpretation:

• Demonstrate that they have acquired skills for effective communication through data visualization.
• Present findings to diverse stakeholders, including investors and policymakers.
• Demonstrate they master the art of storytelling through data visualization to effectively communicate complex findings.

Ethical and Privacy Considerations:

• Discuss ethical issues in Big Data use in economics and finance.
• Explore privacy concerns, data security, and regulatory frameworks.
• Proactively address ethical issues and privacy concerns in Big Data, preparing for future regulatory changes.

Applications in Finance and Business:

• Examine real-world applications in financial markets, risk management, and investment analysis.

Hands-on Projects and Industry Applications:

• Handle real-world projects simulating economic and financial scenarios.
• Collaborate on industry-specific applications using Big Data tools.
• Master the art of storytelling through data visualization to effectively communicate complex findings.

Upon completion, participants will possess the skills to leverage Big Data, enabling informed decisions, optimized financial strategies, and adept navigation of the data-driven finance landscape.

This course delves into the synergies between Big Data and Economics/Finance, emphasizing the transformative role of data analytics in financial and business decision-making. Participants will gain practical insights into large-scale data sets, advanced statistical techniques, and machine learning algorithms. The course will also present examples of how big data is used in finance and applied business contexts, ensuring a comprehensive understanding of its applications.

Scientific papers posted on Canvas.