Applied Data Analytics for Finance and Investment

Become a certified data-analyst able to make smarter decisions about Investment

This is a super-basic course intended for people who know absolutely nothing about python or data-science.

What you’ll learn

  • Python programming.
  • Supervised Machine Learning.
  • Unsupervised Machine Learning.
  • Build and deploy machine learning web-app.
  • Web-scraping.
  • Building map-plots and putting up online.

Course Content

  • Programming Fundamentals – Python 3 –> 5 lectures • 47min.
  • Introduction to Data Science –> 5 lectures • 18min.
  • Pre-processing the data –> 5 lectures • 37min.
  • [BONUS] Scraping and preparing the data –> 2 lectures • 17min.
  • Data Visualisation: Network Analysis of the Stock Market –> 5 lectures • 39min.
  • Supervised Machine Learning –> 4 lectures • 34min.
  • Unsupervised Machine Learning –> 2 lectures • 17min.
  • Data Visualisation: Building Maps for Real-Estate Investment –> 3 lectures • 28min.
  • Final assessment –> 1 lecture • 5min.

Applied Data Analytics for Finance and Investment

Requirements

  • A computer with internet facility.

This is a super-basic course intended for people who know absolutely nothing about python or data-science.

My aim is to help you learn python programming while learning to employ data-science solutions to financial investment problems. At it’s best, this course is probably your first-stepping stone into the world of python and data-science. If you are a seasoned python programmer or data-scientist – this course might serve as a refresher (at the most). Also, this is an applied course and there is little theory in it. I hope to offer some insight into the theory from the quizzes. But I recommend you to read books on python, data-science and statistics for more in-depth learning. Also, I have restricted the use of jargons in this tutorial and made it as simple as possible.

Why financial investment problems?

Money is a basic need for everyone of us – and almost all of us hope to buy an apartment, trade in stocks, and curious what type of customers will buy our product if we open a startup. No matter whether you are in academia or in industry – money connects us all.

Since this course is intended for people of different disciplines, students and practitioners from Management to Medicine, Social Sciences to Humanities might be interested to learn Python programming and implement data-science solution to their workplace problems. I chose financial investment problems for demonstration purpose – with a hope that everyone will be able to find it as a common platform – no matter what is your academic or trade background.

Disclaimer: This course is not meant for financial education and neither encourages financial investments. Also, I am not an expert in finance – so I do not recommend students to blindly invest their money after following my tutorials. Although I tried to follow research papers and investment websites still I do not have domain knowledge so there are chances that I might have mistaken. Most of the data used here are toy-data (i.e. I just made them up). The information conveyed through this course is similar to a college or python/data-science school course; it is not intended to give investment advice, but instead to communicate basic information to help learners understand the basics of Python and Data-Science.

 

Certificate Course for Absolute Beginners | Free Codes to Download | Business Analytics | Finance and Investment

DEDICATED DOUBT CLEARANCE (Great for new learners) – Response within approx. 24 hours.