Algorithmic Trading Python for Beginners - FULL TUTORIAL

We have a created an Algorithmic Trading Course in python for pure beginners wherein we discuss multiple concepts from a basic zero to hero framework. The video is a full tutorial which starts from basic installation of python and anaconda all the way to backtesting strategies and creating trading API. There are more quality quantitative strategy video son our channel that can be found below:

The full code can be downloaded from the link below:
Feel free to check out our Quantitative Trading course:

Chapters
00:00 Intro
00:55 Installation of Anaconda
01:50 Installing Yfinance
02:40 Working with Jupyter Notebook
06:58 Working with numpy and pandas and other libraries
07:50 Downloading stock data
12:00 Working with data
13:00 Read and writing Data
21:35 Separating and Segregating Data
23:00 Data visualization and graphs
26:00 Normalization
30:00 Making changes and creating new data
42:00 Deleting Data
44:40 Resampling Data
48:50 Histogram Graph
50:30 Mean, Variance and Standard Deviation
01:00:00 Scatter Plot
01:00:40 Stock Comparison with risk metric
01:01:50 For loops
01:09:00 Correlation and Covariance
01:10:20 Heat map
01:15:00 Challenge 1
01:16:00 Simple and Log returns
01:23:00 Creating Moving averages data
01:32:15 Challenge 2
01:35:00 Reindexing
01:37:45 Forward fill and Backfill
01:41:00 Cumulative returns and drawdowns
01:57:00 Creating and Backtesting Strategies
02:09:00 Comparison to buy and hold
02:11:40 Long bias Strategy
02:16:00 Challenge 3
02:16:30 Creating a function
02:26:30 Creating a class
02:43:30 Importing and Using a Class
02:48:45 Challenge 4
02:51:00 API
02:52:00 Working with API

[quantprogram]

Chapters
Download the python file in the description if you face any errors. You can also watch quantconnect via python tutorial on our channel to execute/automate your live strategies via your broker. Visit our website for more detailed algorithmic trading course with 10 strategies to start of your algorithmic trading career.
00:00 Intro
00:55 Installation of Anaconda
01:50 Installing Yfinance
02:40 Working with Jupyter Notebook
06:58 Working with numpy and pandas and other libraries
07:50 Downloading stock data
12:00 Working with data
13:00 Read and writing Data
21:35 Separating and Segregating Data
23:00 Data visualization and graphs
26:00 Normalization
30:00 Making changes and creating new data
42:00 Deleting Data
44:40 Resampling Data
48:50 Histogram Graph
50:30 Mean, Variance and Standard Deviation
01:00:00 Scatter Plot
01:00:40 Stock Comparison with risk metric
01:01:50 For loops
01:09:00 Correlation and Covariance
01:10:20 Heat map
01:15:00 Challenge 1
01:16:00 Simple and Log returns
01:23:00 Creating Moving averages data
01:32:15 Challenge 2
01:35:00 Reindexing
01:37:45 Forward fill and Backfill
01:41:00 Cumulative returns and drawdowns
01:57:00 Creating and Backtesting Strategies
02:09:00 Comparison to buy and hold
02:11:40 Long bias Strategy
02:16:00 Challenge 3
02:16:30 Creating a function
02:26:30 Creating a class
02:43:30 Importing and Using a Class
02:48:45 Challenge 4
02:51:00 API
02:52:00 Working with API

[jimgrajek]

If you think you are going to do this in just over 3 hours by following along that is not going to happen. Plan for 3 days. Just a great video. So much information. Thank you.

[buggycoder]

I came here from the code camp course. You are so much more easy to understand. Though with a lot of struggle I had managed to cope with the instructions of Codecamp course, turns out a lot of functions mentioned in the course are outdated. I was confronted with many decoding errors. So I luckily found your course, which is super beginner friendly and more importantly everything works!! Thank you very much for this course!

[kritimathur]

This video is the reason I got my first internship ever and I'll forever be grateful for it, thank you for this amazing content.

[agermoune]

Exactly what I was looking for, both the curriculum and finance subject. Glad I found your channel, subscribed immediately and will explore your other videos later.
Thank you for all your time and effort to spread knowledge!

[TheRoandroid]

Excellent video! I'm looking forward to watching the rest of your content. You explain concepts very well, and I particularly enjoyed your Python teaching skills. Watching a real person code and troubleshoot is incredibly valuable. This is an excellent and honest video that provides valuable content.

[pravinsharma]

I am just halfway down the line and I can say that it's the best video to date on Algo Trading!

[sahil]

What a video!! Just a simple and very good explanation so far on youtube. Tried learning from many, but this is the best❤

[omeruzun]

Unbelievable ... The algorithm recommended that video but I did not see it in the list when I looked once. I am at minute 6 and learned already some useful shortcuts for jupyter. Very good content thank you very much I will enjoy that video I see it helps to learn to code in a very practice-related way, that is how I like to learn!

[darshitgoswami]

One of the finest video on the topic, heavily underrated.. thanks for this..

[MichaelAlcock]

24:07. You may come accross an error when trying to use seaborn as explained in the video. This is due to an update in Python since 3.6(i think).
My work around was:
"
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_theme()
plt.style.use("seaborn")
"

Just an extra step but it works.

[anm_yoga]

This is the absolute best algo trading tutorial I have ever seen on YouTube because it is the only one completed. From now I only want to follow your channel. thank you for your excellent teaching.

[crazyvideos]

15 MINS INTO THIS TUTORIAL I am already I pray it goes well because I have been searching for aa step by step way to learn algo trading and none has been so helpful but this. Thanks so much. I am coding along and pausing the video to take note and I can tell your simplicity in explaining complex python syntax is epic

i have not encountered any issues yet. Thanks

[Tipate]

Just got through with the full tutorial !
Thanks a lot for putting online such a great video !

[venerateweb]

Fantastic video. Quick request actually: there seems to be a lot of talk about using AI (with python) in algorithmic trading. Could you make a video showing this in the same fashion/detail as you've created this wonderful video?

[pauleasther]

Great help, thanks for taking the time to create the video 😊 As a youtuber myself I know the time involved in creating vids can be 100 times longer than the play time

[anonymousdetective]

I have never traded before or done any kind of market analysis, but I have the interest to ackknoledge and do some investments. Should I watch this video, or this is for the intermdediate expert traders? Can you give me guidelines?

[froggyana]

Thank you for taking the time to make this video. I have really benefited. Cheers

[ryantao]

Thanks for the great video. It is very easy to understand. However, through the challenges, using multiple data columns and creating new ones for each is difficult. For example, for Challenge 2 where I had to create a moving average for every stock, you put spy["SMA50"] = spy.rolling(window=50, min_periods=50).mean()
This worked and made another column for a 50 SMA. When I put a dataframe with multiple stocks into it such as
unriskstocks["SMA50"] = unriskstocks(window=50, min_periods=50).mean()
It gave the error that I was trying to put many columns into the column SMA 50. I had to manually type out every stock such as how you did it. Is there a better and more efficient way to do this, especially with a trading strategy?
Thanks

[romainbrs]

Such a Wonderful video! Good idea the concept of challenge. Thank You for this