Introduction to Data: Predicting Stock Market Prices

Introduction

Welcome to our comprehensive course desidnged to introduce you to the exciting world of data practices. This course aims to cover fundamental concepts in data engineering, data analysis and visualization, data science and machine learning. The unique focus of our learning journey is the application of these practices to predict stock market prices. The skills and knowledge gained here are not just limited to financial markets; you can apply these concepts to predict trends in costs, sales, user adoption rates, advertising and more, helping your company make data-driven decisions and products.

Course Structure

Our course is structured in soncequtive sessions, each building upon the last to teach you one aspects of the #data-world. We won't go deep in the concepts of programming and tools, as we won't spend much time to learn all the basics of fincancial markets. For those, we will provide references to diverse data sources. Our assumption is that you know the basics of Python programming. But, you would be able to learn the course without prior experience, and you will find enough time to learn the required Python concepts in one or two weeks.

Session 1: Very simple data engineering - Data Ingestion

We will dive into the basics of data engineering by learning how to accumulate data, which is called data ingestion or extraction in data engineering. We will cover getting stock market data using free APIs and storing them in the simplest format so we can learn about the value of a company and behaviour of its stock prices.

Prerequisites and Tools

• Basic understanding of Python programming is an asset
• Familiarity with basic statistics is helpful.
• You can use any development environment including VSCode, Python IDLE, Pycharm, etc. You can also use notepad or vim!

Expected Learning Outcomes

By the end of this course, you will be able to:

• Understand and implement data processing techniques.
• Perform basic data analysis and visualization on stock market data.
• Create simple predictive models for stock price forcasting.
• We will test our predictive models, and wiln (or loose) some actual money along the way.
• Automate data workflows using more advanced data processing tools.

Course Format

• Video tutorials
• Hands-on coding session
  • We will share all the codes on GitHub

Additional Resources

For those new to Python or needing a refresher, we recommend Python for Beginners and Pandas Tutorial. For those new to financial markets, we recommend Intoroduction to Financial Markets.