Study Material for CFA Exam

We are happy to announce the launch of “Study Material for CFA Exam” from Finance Train.

At Finance Train you can access all the study material that you will require to prepare for the CFA exam (Level I, II and III). The study material is organized as per the latest syllabus and learning outcome statements provided by CFA Institute.

You can access the CFA dashboard from here.

Our approach is to take up each learning outcome statement and provide you the best content and study resources for the same. Our objective is to cover atleast one learning outcome statement everyday and finish the entire syllabus within next 5 months.

You can visit us regularly to access new content, or you can even receive these lesson alerts via email.

So, stay tuned and start preparing for the CFA exam with us.

Link to CFA Exam Dashboard

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.