Quantitative Analyst in R

This Track uses the programming language R, which is a powerful language for performing data analysis.

This Track is especially beneficial to those who want to pursue a career in Quantitative Analysis, or enhance their existing career in finance. This Track can help users acquire the skills needed to excel in jobs such as portfolio analysis, trading strategy development, and asset pricing evaluation.

This Track will help you develop a strong understanding of quantitative analysis as it applies to finance and how to use R to explore and manipulate datasets. In addition, this Track provides hands-on practice with the use of a variety of techniques and modeling tools that are used in the industry.

This Track typically takes 65 hours to complete as it consists of several courses that upskill users with domain-specific knowledge.

Skill tracks are collections of courses that allow users to acquire new skills in a particular subject. Career tracks allow users to gain knowledge and experience to help them in their job search, career growth, and personal development objectives.

This Track covers a range of topics related to quantitative analysis and using R for exploring and manipulating datasets. Topics include portfolio analysis, credit risk modeling, time-series analysis, financial trading, importing and managing financial data, bond valuation and analysis, ARIMA models, visualizing time-series data, and forecasting. The content in this Track is designed to equip users to become proficient in quantitative analysis as it relates to finance.

This Track makes use of a variety of real-world data sets to provide students with a practical understanding of the quantitative analysis tools and techniques taught. Examples of datasets used in the Track include publicly available financial market data and data relating to cities and other places of interest.