Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
22 Hour(s) 50 Minute(s)
Language
English
Rating
3 views
Course Overview
Learn to use Python, Pandas, Matplotlib, and the QuantConnect Lean Engine to perform financial analysis and trading
Welcome to the ultimate online course to go from zero to hero in Python for Finance, including Algorithmic Trading with LEAN Engine!
This course will guide you through everything you need to know to use Python for Finance and conducting Algorithmic Trading on the QuantConnect platform with the powerful LEAN engine!
This course is specifically design to connect core financial concepts to clear Python code. You will learn about in-demand real world skills that are highly sought after in the fintech ecosystem.
We'll cover the following topics used by financial professionals:
Python Crash Course Fundamentals
NumPy for High Speed Numerical Processing
Pandas for Efficient Data Analysis
Matplotlib for Data Visualization
Stock Returns Analysis
Cumulative Daily Returns
Volatility and Securities Risk
EWMA (Exponentially Weighted Moving Average)
Sharpe Ratio
Portfolio Allocation Optimization
Efficient Frontier and Markowitz Optimization
Types of Funds
Order Books
Short Selling
Capital Asset Pricing Model
Stock Splits and Dividends
Efficient Market Hypothesis
Algorithmic Trading with QuantConnect
Futures Trading
Options Trading
and much more!
Why choose this specific course to learn Python, Finance, and Algorithmic Trading?
This course starts by teaching you some of the most important and popular libraries in Python for Data Analysis and Visualization, includign NumPy, Pandas, and Matplotlib.
Each lecture includes a high quality HD video with clear instructions and relevant theory slides as well as a full Jupyter Notebook with explanatory code and text.
This course has complete coverage allowing you to actually implement your ideas as algorithms, other courses online never actually show you how to trade with your new knowledge!
Powerful online community with our QA Forums with thousands of students and dedicated Teaching Assistants, as well as student interaction on our Discord Server.
All of this comes with a 30-day money back guarantee, so you can try out the course absolutely risk free!
Course Content
- 11 section(s)
- 135 lecture(s)
- Section 1 Course Welcome and Overview
- Section 2 Python Crash Course
- Section 3 NumPy
- Section 4 Core Pandas
- Section 5 Matplotlib
- Section 6 Pandas and Finance
- Section 7 Financial Concepts with Python
- Section 8 Stock Market Analysis Capstone Project
- Section 9 Algorithmic Trading Basics with QuantConnect
- Section 10 QuantConnect Research, Plotting, Universe Selection
- Section 11 Derivative Contracts
What You’ll Learn
- Learn to use powerful Python libraries such as NumPy, Pandas, and Matplotlib, Understand Modern Portfolio Theory, Use Monte Carlo simulation techniques to optimize portfolio allocation, Understand SciPy minimization algorithms to create optimized portfolio holdings, Use and understand stock fundamentals data, such as CFC, Revenue, and EPS, Calculate the Sharpe Ratio for any stock, Understand cumulative returns and daily average returns in stocks, Learn to use QuantConnect's LEAN engine for automated trading, Learn about Bollinger Bands and other classic technical analysis, Use algorithmic trading to trade derivative futures contracts, Dive into understanding CAPM - Capital Asset Pricing Model, Use fundamental stock company data to create rules based trading algorithms, Learn about alternatives to the Sharpe Ratio, such as the Sortino Ratio, Learn to read and understand a Backtest, including Probabilistic Sharpe Ratios, Conduct Research on QuantConnect, including full universe stock selection screening
Reviews
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MMorgan Philip-Gershon Penny
I just completed the course, so I thought I'd leave a review, I guess. I took this course cause i wanted basically a beginner-level understanding of how things are laid out on QuantConnect. It will help you navigate how you should proceed i guess, mostly cause it's not that easy to understand what QuantConnect needs for it to make your algorithm. The doc is basically a large pond of info, and with no way to really navigate what's required. So this course did clear that up, thanks for making it, i did enjoy the course its probably apparent that the course is a little out of date, but hear me out, it turns out that everyone seems to be out of date aha, so do bear that in mind, but its most just "_" and lower case, over caps. The end does get a little trickly cause the documentation is wayyyyyyyyyyyy different overall its pretty good. It would be cool if Jose made a course that was completely focused on quant connects ability and show cased allot of the things you can do, while expanding on different ways to use python with quant. i feel that he kept things way to seprate, rather than teaching the ideas he had together in parallel. by time you make it to the quant selection, you basically forget what was taught and have to double back. but yeah i liked it, it could be updated, but honestly i think allot of work went into it so maybe just make a new course instead aha!!
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JJeroen
yes good content although there is a lot of front loading before starting with the actual quantconnect system which i did not expect.
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AAbbas WebDev
The course is poorly structured, and the QuantConnect section is very basic and outdated. The content has not been updated for a long time, and some sections that were clearly promised, such as options and futures, were never delivered. I enrolled in this course specifically to prepare for QuantConnect, but it did not meet that objective. Unfortunately, because I followed the course from the beginning, Udemy refused a refund on the grounds that most of the content had already been accessed.
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JJoy Yan
Really good course and top explanation! Thank you for such a great introduction course to quantconnect.
