• Anytime
    Application Deadline
  • 1 month
    Duration
This Python and Statistics for Financial Analysis offered by Coursera in partnership with The Hong Kong University of Science and Technology combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.
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Overview

Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. 

By the end of the Python and Statistics for Financial Analysis offered by Coursera in partnership with The Hong Kong University of Science and Technology, you can achieve the following using python:

  • Import, pre-process, save and visualize financial data into pandas Dataframe
  • Manipulate the existing financial data by generating new variables using multiple columns
  • Recall and apply the important statistical concepts (random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. ) into financial contexts
  • Build a trading model using multiple linear regression model 
  • Evaluate the performance of the trading model using different investment indicators

Detailed Programme Facts

Programme Structure

Courses include:

  • Visualizing and Munging Stock Data
  • Random variables and distribution
  • Sampling and Inference
  • Linear Regression Models for Financial Analysis

English Language Requirements

This programme may require students to demonstrate proficiency in English.

General Requirements

Beginner Level

  • You will get the most out of the course if you have basic knowledge in probability.

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved.

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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