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Python & Machine Learning for Financial Analysis is the name of a video training package in the field of programming. In this course you will start learning machine and python. In fact, this course is designed and published with the aim of learning the practical application of Python and machine programming in order to analyze data science. In this course, you will first start learning the basics of Python programming. You will further improve your skills in this area.

In the following, you will learn how to analyze complex financial statistical data. So that with this type of analysis you can get statistical information accurately. In the end, you will be well acquainted with the concept of artificial intelligence and advanced content in this field will be provided to you. This course is recommended for those financial analysts who want to use the power of artificial intelligence and data science to optimize business processes and maximize interest rates.

Features of Python & Machine Learning for Financial Analysis

  • Learn the basics of Python programming for data science and machine learning
  • How to use Python to get statistical data
  • Get acquainted (gain, obtain) with present-day techniques that came from Python
  • Familiarity with a variety of Python libraries, including NumPy
  • Familiarity with the Master SciKit-Learn library and the use of real-world datasets
  • And…

Course details:

  • Duration: 10h 6m
  • English language
  • Number of chapters: 10
  • Number of courses: 43
  • Instructor: EmbeddedExpertIO and Israel Gbati

Course chapters

Python & Machine Learning for Financial Analysis

Prerequisites for Python & Machine Learning for Financial Analysis

  • No prior experience required.


Python & Machine Learning for Financial Analysis

Sample film

Installation guide

After Extract, watch with your favorite Player.

English subtitle

Quality: 720p

download link

Download Part 1 – 2 GB

Download Part 2 – 2 GB

Download Section 3 – 2 GB

Download section 4 – 2 GB

Download Section 5 – 1.5 GB

File password (s):


9.5 GB

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