The Safest Way to Trade Cryptocurrency - CryptoArbitrage

Course Details

Date: 27/8 - 4/10 (Every Tue & Fri)

Time: 7:30 pm - 9:30pm

No. of lesson: 12 lessons in 6 weeks.

Venue: BITWORK

Language: Cantonese

Course Fee: HK$16,800

(*Early bird: HK$ 13,800 by 13/8)

(**Pre-event on-site: HK$12,800 on 6/8) (Reg link: https://www.eventbrite.hk/e/66436109191)

Speakers:

Patrick Leung (Data Scientist @ Standard Chartered Bank)

Dr. Anushree Mahapatra (Machine Learning Engineer / PhD Computer

Engineering)

Course Summary

Who is this for

1. An absolute beginner that wants to learn and build the Algorithmic Trading model. Perfect for those who want to get a complete picture of Algorithmic Trading.

2. Business person looking to solve problems in machine learning

3. Experienced programmers who want to switch career to machine learning

Prerequisites

1. No prior knowledge in programming is required.

2. Intro-level algebra, comfortable with statistics, variables, coefficients, linear equations

End Product

1. Be able to create Algorithmic Trading models using Python and spreadsheets.

Curriculum

Week 1 - Introduction to Python

Class 1 - Overview of Arbitrage Trading & Python

- 1.1 Why automation is needed for cryptocurrency arbitrage?

- 1.2 What is the usage of coding in algorithmic trading?

Class 2 - Introduction to Python

- 2.1 Setup fundamentals framework

- 2.2 What can be done in python? (automation) (Why python?)

- 2.3 General python commands/Navigating in jupyter notebook

- 2.4 Variables

Week 2 - Python as a Data tool

Class 3 - Data type & Data Structure

- 3.1 Integer, string, float

- 3.2 List, dictionaries, tuples

Class 4 - Logical Operations in python

- 4.1 if-statements

- 4.2 loops

- 4.3 functions

Week 3 - Introduction to Data Science

Class 5 - Fundamentals of Data Science

- 5.1 What is Data Science?

- 5.2 What is Machine Learning?

- 5.3 What is the practical usage of data in trading?

Class 6 - Data Cleaning & Visualization

- 6.1 Introduction to pandas

- 6.2 Data cleaning in pandas

- 6.3 Visualization in matplotlib

- 6.4 Introduction to numpy

Week 4 - Application of Automated Trading I

Class 7 - Querying pricing data using API

- 7.1 API query using Request

- 7.2 Basic of web-scraping

Class 8 - Restructuring time-series Data

- 8.1 Introduction to time-series data

- 8.2 Data reshaping using