The Complete Course of Algo Trading with Python

Pricing options

Both option include life-time access to the Complete Course, but the course + 4 mentoring sessions combination is recommended so that you get the best support.

Course Curriculum: The Complete Course of Algo Trading with Python

  1. 1

    • Optional (For Mac Users)
  2. 2

    • Installing Anaconda
  3. 3

    • Installing Ta-Lib
  4. 4

    • Python Expressions

    • If You Are On a Mac

    • Overview of Data Types

    • Numerical Data Type

    • String Data Type

    • List Data Type

    • Tuple Data Type

    • Set Data Type

    • Dictionary Data Type

    • Control Flow Structure
  5. 5

    • Chapter Introductions and Overview

    • Working with Pandas DataFrame

    • DataFrame at a Glance

    • Working with DataFrame - Part 2

    • DataFrame at a Glance - Part 2

    • Accessing Columns

    • Subsetting, Indexing and Slicing

    • Unique Values

    • Selecting Rows

    • Selecting Rows - Part 2

    • Subsetting

    • Adding New Columns

    • Sorting

    • Using Groupby

    • Pandas Summary

    • Accessing Columns - Part 2
  6. 6

    • Python Function Overview

    • Functions

    • Error Handling - Try / Except

    • Why Using Error-Handling

    • Functions - Part 2

    • Best Practices
  7. 7

    • Datetime Objects in Python

    • Timezones

    • Timedelta

    • Converting Datetime to String

    • Conveting String to Datetime
  8. 8

    • Installing MetaTrader5 Module

    • Connecting to MT5 Terminal

    • Setting Timezones to Match Market Watch Time
  9. 9

    • Overview

    • Building Indicators via Pandas

    • Building Indicators via Ta-Lib
  10. 10

    • Getting Account Info
  11. 11

    • Recap

    • Stoploss

    • Calculate Size
  12. 12

    • Putting It Together

    • Putting It Together for Long Positions

    • Putting It Together for Short

    • One More Thing

    • Summary

    • Documentation and Summary
  13. 13

    • Recap of What We Have So Far

    • Updating Stoploss

    • Updating Stoploss - Part 2

    • Move Stops to Breakeven and Trail Afterwards for Long Positions

    • Move Stops to Breakeven and Trail Afterwards for Short Positions

    • Overall Summary

Instructor

Instructor and Mentor

Jenny Hung

Jenny had always loved math, but she decided to pursue accounting in the first place. She has 10 years of experience in tax compliance and tax planning, her passion for math was reignited, and she went back to school to study mathematics and statistics.

Jenny believes that numbers help us understand the world, and a math-based approach helps us understand numbers because mathematics is essentially a way of thinking through any problem. We are surrounded by numbers, equations and algorithms – especially in this age of the digital world, data is the ammunition for the digital world.

She loves coding, data analysis, quantitative finance, and everything mathematical. Her specialty is finance / econometrics-related deep reinforcement learning and uses data analysis and machine learning to support the decision-making process.

More importantly than her love of code and math, she loves to make a difference and inspire. This is because citizens of the globe don’t always get to vote to either get in or stay out of this digital world — even when people are not actively participating in the digital world, they are passively being involved in it. Data about this world, and the algorithms that feed upon the data, are shaping our world in ways that are not always desirable to the passive participants.

Her goal with this signature course is to teach as many people as possible the vital skills of critical data thinking, data analysis and applied machine learning so that students can leverage these life-long skills to improve their lives.

Jenny received her law degree from National Taiwan University, is a designated CPA.CA (Canada), and received her Bachelor of Science degree from Simon Fraser University.

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