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Python and Machine Learning in Financial Analysis is a course in economic analysis and financial statements using machine learning techniques published by Udemy Academy. Your main programming language and tool in this course is Python. Python is a versatile and fully flexible programming language that is used in various specialized fields such as artificial intelligence, machine learning, etc. At the beginning of this training course, you will be introduced to a series of economic and financial concepts that are very important in economic analysis, and then you will learn different methods of algorithm writing and development of analytical systems based on machine learning. Technical and fundamental analysis are two wings of financial market analysis that you will learn about in this training course.

After getting acquainted with the economic concepts and different methods of financial data analysis, go to Python and learn how to work with this programming language in a completely practical and applied way. Among the technical topics presented in this section, we can mention deep learning techniques, algorithm writing, artificial intelligence, building neural networks, and so on. Accurate raw data is one of the most important foundations of economic analysis. During the training process of this course, various resources for downloading and downloading economic data will be introduced to you. You will also learn about different types of economic data and their validation methods. Working with oscillators and indicators is one of the most important aspects of technical analysis that at the end of this training course you will build a trading robot based on indicators.

What you will learn in Python and Machine Learning in Financial Analysis

  • Familiarity with different methods and resources to obtain accurate and reliable economic information
  • Pre-processing and initial preparation of data for use in later stages of analysis
  • Time series analysis models
  • Familiarity with different methods of exponential smoothing
  • Integrated self-correlated moving average models (ARIMA)
  • Familiarity with different methods of predicting price fluctuations using financial time series models
  • Different methods of interpreting and reviewing financial statements
  • Familiarity with modern stock portfolio theory
  • Evaluate the overall performance of the stock portfolio using Python algorithms
  • Familiarity with different patterns in stock charts
  • Working with different indicators in technical analysis
  • Familiarity with the Monte Carlo simulation method and its use to estimate the stock price and options in the coming days
  • And …

Course specifications

Publisher: Udemy
Instructors: S.Emadedin Hashemi
Language: English
Level: Introductory to Advanced
Number of Lessons: 82
Duration: 20 hours and 17 minutes

Course topics

Python and Machine Learning in Financial Analysis Content

Python and Machine Learning in Financial Analysis Prerequisites

Statistics and Basic Python


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Python and Machine Learning in Financial Analysis introduction video

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