Overview What You Will Learn Curriculum Instructor

Course Overview

Artificial intelligence (AI) is leading the front of the digital transformation strategy in finance today. AI can practically be employed in everything present in the digital world.

We will begin with an introduction to Artificial Intelligence and all the related terms. Here, we will get to know the connection between AI and Finance. Moving ahead, we will explore Python and the pythonic ways of working. Here, we will get a hang of many interesting things like Quandl, NumPy, SciPy, and artificial neural networks. Finally, we will end the course by knowing about linearity and non-linearity in Finance.

At the end of the course, you will be able to master the art of applying Python-based programming to different paradigms in the financial industry and perform effective and efficient data analysis.

The necessary resources for this course are in the "Resources" section of Video 1.1. You can also access them through this direct link - https://github.com/ec-council-learning/AI-for-Finance


“Disclaimer: The opinion expressed in this course/contents are those of the speaker/author and they do not reflect the opinion or views of his current and former employers.”

What You Will Learn

  • You will learn to use ML for Finance.
  • The entire course has leveraged Python as a tool for applying AI driven solutions in the domain of Finance.
  • How to create efficient and powerful data-driven solution framework for financial decision making using popular libraries such as TensorFlow 2
  • Keras
  • NumPy
  • SciPy
  • scikit-learn and many more.

Program Curriculum

  • Introduction to AI and ML
  • Types of Machine Learning
  • Major Applications of AI in Finance
  • Why Data is Important
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Introduction to Pythonic way of working!
  • Introduction to quandl and Yahoo Finance
  • Getting Started with Numpy and Scipy
  • Getting Started with Pandas
  • Introduction to Artificial Neural Network
  • Chapter 2 Quiz

  • Linear Optimization, A Maximization Example using LP
  • Introduction to CAPM and APT Model
  • Introduction to Non-Linear Models in Finance
  • Chapter 3 Quiz

Instructor

Shovon Sengupta

Shovon Sengupta is an experienced data scientist with over 12 years of experience in advanced predictive analytics, machine learning, deep learning, and reinforcement learning. He has worked extensively in designing award-winning solutions for various organizations, for different business problems in the realm of Finance. Currently, he is Director - Data Science @AI CoE in one of the leading NBFCs in the USA. He has a USA patent(United States Patent - Sengupta et al. : Automated Predictive Call Routing Using Reinforcement Learning) for designing a reinforcement learning-based solution to his credit.

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