Skip to content Skip to sidebar Skip to footer

Python & Machine Learning for Financial Analysis

Python & Machine Learning for Financial Analysis

Master Python Programming Fundamentals and Harness the Power of ML to Solve Real-World Practical Applications in Finance

What you'll learn

  • Master Python 3 programming fundamentals for Data Science and Machine Learning with focus on Finance.
  • Understand how to leverage the power of Python to apply key financial concepts such as calculating daily portfolio returns, risk and Sharpe ratio.
  • Understand the theory and intuition behind Capital Asset Pricing Model (CAPM)
  • Understand how to use Jupyter Notebooks for developing, presenting and sharing Data Science projects.
  • key Python Libraries such as NumPy for scientific computing, Pandas for Data Analysis, Matplotlib/Seaborn for data plotting/visualization
  • Master SciKit-Learn library to build, train and tune machine learning models using real-world datasets.
  • Apply machine and deep learning models to solve real-world problems in the banking and finance sectors
  • Understand the theory and intuition behind several machine learning algorithms for regression, classification and clustering
  • Assess the performance of trained machine learning regression models using various KPI (Key Performance indicators)
  • Assess the performance of trained machine learning classifiers using various KPIs such as accuracy, precision, recall, and F1-score.
  • Understand the underlying theory, intuition behind Artificial Neural Networks (ANNs), Recurrent Neural Networks (RNNs) & Long Short Term Memory Networks (LSTM).
  • Train ANNs using back propagation and gradient descent algorithms.
  • Optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance.
  • Master feature engineering and data cleaning strategies for machine learning and data science applications.

Go Link :  Python & Machine Learning for Financial Analysis

Python is ranked as the number one programming language to learn in 2020, here are 6 reasons you need to learn Python right now!

1. #1 language for AI & Machine Learning: Python is the #1 programming language for machine learning and artificial intelligence.

2. Easy to learn: Python is one of the easiest programming language to learn especially of you have not done any coding in the past.

3. Jobs: high demand and low supply of python developers make it the ideal programming language to learn now.

4. High salary: Average salary of Python programmers in the US is around $116 thousand dollars a year.

5. Scalability: Python is extremely powerful and scalable and therefore real-world apps such as Google, Instagram, YouTube, and Spotify are all built on Python.

6. Versatility: Python is the most versatile programming language in the world, you can use it for data science, financial analysis, machine learning, computer vision, data analysis and visualization, web development, gaming and robotics applications.

Online Course CoupoNED based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.