Application of Python in trading & investing

Application of Python in trading & investing

nse-line

Application of Python in trading & investing

TOTAL DURATION CERTIFICATION VALIDITY COURSE TYPE
16 Hours No Expiry Date Online Interactive

For more information, please Contact:

Counsellor : +91 7418954716 / +91 8080533088

Email id: gen_pdp@nse.co.in

The Application of Python in Trading & Investing program covers the practical uses of Python for analyzing data and stock market trading. Participants will learn Python installation, usage of code editors, and execution of Python commands. The course equips learners with essential skills to analyze financial data and develop trading strategies using Python.

The sessions will cover the following topics:

  • Python Working Environment
  • Jupyter Notebook
  • Python history and features
  • Installing Jupyter Notebook, creating a Python environment on Windows
  • Python commands
  • Programming Basics
  • Keywords, syntax, variables
  • Logical, comparison, and mathematical operators
  • Conditional statements (if-else), string operations, arrays, loops, functions, and file I/O
  • Data Collections
  • Pandas data frames, dictionaries, arrays
  • Main Data Analysis
  • Importing/exporting financial data (file I/O)
  • Exploratory data analysis
  • Customized charts
  • Libraries: NumPy, technical indicators
  • News feed integration in Python
  • Backtesting in Python
  • Sample project
  • Live online interactive classes by professional faculty
  • Class recordings available for a limited period
  • Access through mobile, desktop and laptop
  • Certification from NSE Academy

This course is designed for finance enthusiasts, students, and professionals seeking to deepen their understanding of equity research and valuation. While no specific prerequisites are required, a basic understanding of finance and financial statements is beneficial. Whether you're a student or a professional, this course equips you with essential skills for effective company analysis and informed investment choices.