Big Data Ana­lyt­ics for Eco­nom­ic and Fin­an­cial De­cision-Mak­ing

Course content

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

Big Data Fundamentals:

• Articulate and apply core concepts in big data analytics.

Statistical Techniques and Machine Learning:

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

Data Visualization and Interpretation:

• Effectively communicate findings through data visualization to diverse stakeholders.
• Master the art of storytelling through data visualization to clearly convey complex insights.

Ethical and Privacy Considerations:

• Discuss ethical issues in the use of Big Data in economics and finance.
• Explore privacy concerns, data security, and regulatory frameworks.
• Proactively address ethical issues and privacy concerns in Big Data.

Applications in Finance and Business:

• Examine real-world applications in economic and finance.

Hands-on Projects

• Examine real-world applications in economic and finance.

Upon completion, participants will possess the skills to leverage Big Data, enabling informed decisions and optimized strategies in various economic contexts.

This course explores the intersection of Big Data and Economics/Finance, highlighting the transformative role of data analytics in decision-making. Participants will gain practical insights into handling large-scale data sets, applying advanced statistical techniques, and utilizing machine learning algorithms. The course includes practical exercises ensuring hands-on experience with real-world data. Examples will illustrate how big data is used in economic analysis and applied business contexts, providing a comprehensive understanding of its applications.