In this tutorial, we will learn how to find the index of a column that contains a certain value.
Example we have a dataframe with the following columns:
<pre><code class="language-python">import pandas as pd
df = pd.DataFrame({
 'A': [1, 4, 7, 1, 4],
 'B': [2, 5, 8, 2, 5],
 'C': [3, 6, 9, 3, 6]
})
</code></pre>
<pre><code> A B C
0 1 2 3
1 4 5 6
2 7 8 9
4 1 2 3
5 4 5 6
</code></pre>
Let us find the index of the column that contains the value <code>5</code>.
Using np.where from numpy
The numpy function <code>np.where</code> can be used to find the index of a column that contains a certain value.
The syntax is:
<code>numpy.where(condition[, x, y])</code>
<pre><code>Parameters
conditionarray_like, bool
Where True, yield x, otherwise yield y.

x, y: array_like
Values from which to choose. x, y and condition need to be broadcastable to some shape.

Returns
out: ndarray
An array with elements from x where condition is True, and elements from y elsewhere.
</code></pre>
For the above example, we can use the following code to find the index of the column <code>B</code> that contains the value <code>5</code>.
<pre><code class="language-python">import numpy as np
col_index = pd.DataFrame(np.where(df.eq(5))[1] + 1, columns=['col_index'])
</code></pre>
Output:
<pre><code> col_index
0 2
1 2
</code></pre>

Pandas how to find column contains a certain value

Ubuntu 20.04 comes with Python 3.8 pre-installed. However, you may want to install other Python versions. In this tutorial, I will show you the recommended way to install latest Python version on Ubuntu 20.04.
The tool we will use is called <code>pyenv</code>. pyenv is a tool that helps us manage multiple versions of Python. pyenv lets you easily switch between multiple versions of Python. It&#39;s simple, unobtrusive, and follows the UNIX tradition of single-purpose tools that do one thing well.

 <h2>
 Install dependencies
 <a name="install-dependencies" class="hash-link" href="#install-dependencies" title="Install dependencies">
 #
 </a>
 </h2>For <code>pyenv</code> to work properly, you need to install required dependencies.
Open a terminal and type the following command:
<pre><code class="language-bash">sudo apt-get update; sudo apt-get install make build-essential libssl-dev zlib1g-dev \
libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \
libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev
</code></pre>

 <h2>
 Install pyenv
 <a name="install-pyenv" class="hash-link" href="#install-pyenv" title="Install pyenv">
 #
 </a>
 </h2>Install <code>pyenv</code> by typing the following command:
<pre><code class="language-bash">curl https://pyenv.run | bash
</code></pre>
Restart your shell so the path changes take effect:
<pre><code class="language-bash">exec $SHELL
</code></pre>
Check if <code>pyenv</code> is installed successfully:
<pre><code class="language-bash">pyenv -v
</code></pre>

 <h2>
 Install/Unstiall Python with pyenv
 <a name="install-unstiall-python-with-pyenv" class="hash-link" href="#install-unstiall-python-with-pyenv" title="Install/Unstiall Python with pyenv">
 #
 </a>
 </h2>The <code>pyenv install</code> is used to install Python version. Its syntax is:
<pre><code class="language-bash">Usage: pyenv install [-f] [-kvp] &lt;version>
 pyenv install [-f] [-kvp] &lt;definition-file>
 pyenv install -l|--list

 -l/--list List all available versions
 -f/--force Install even if the version appears to be installed already
 -s/--skip-existing Skip the installation if the version appears to be installed already

 python-build options:

 -k/--keep Keep source tree in $PYENV_BUILD_ROOT after installation
 (defaults to $PYENV_ROOT/sources)
 -v/--verbose Verbose mode: print compilation status to stdout
 -p/--patch Apply a patch from stdin before building
 -g/--debug Build a debug version
</code></pre>
For example to install Python 3.9.6, type the following command:
<pre><code class="language-bash">pyenv install 3.9.6
</code></pre>
To activate the Python 3.9.6 globally, type the following command:
<pre><code class="language-bash">pyenv global 3.9.6
</code></pre>
The syntax for unstall a specific Python version is:
<pre><code class="language-bash">Usage: pyenv uninstall [-f|--force] &lt;version>

 -f Attempt to remove the specified version without prompting
 for confirmation. If the version does not exist, do not
 display an error message.
</code></pre>
To uninstall Python 3.9.6, type the following command:
<pre><code class="language-bash">pyenv uninstall 3.9.6
</code></pre>
You can install multiple versions of Python at the same time by using the <code>pyenv install</code> command. For example, to install Python 3.8.5 and 3.9.6, type the following command:
<pre><code class="language-bash">pyenv install 3.8.5 3.9.6
</code></pre>
You of course can keep multiple Python versions. 
For more information about pyenv, please visit <a href="https://github.com/pyenv/pyenv/" target="_blank" rel="noopener noreferrer">pyenv repository</a>

Recommended way to install multiple Python versions on Ubuntu 20.04

Web scraper is a technique for extracting structured information from a web page. With Python, you can build a efficient web scraper by using <code>BeautifulSoup</code>, <code>requests</code> and other libraries. However, these solution is not fast enough. In this article, I will show you some tips to build a super fast web scraper with Python.

 <h2>
 Don&#39;t use BeautifulSoup4
 <a name="don-39-t-use-beautifulsoup4" class="hash-link" href="#don-39-t-use-beautifulsoup4" title="Don&#39;t use BeautifulSoup4">
 #
 </a>
 </h2>BeautifulSoup4 is friendly and user-friendly, but it is not fast. Even you use external extractor such as <code>lxml</code> for HTML parsing or use <code>cchardet</code> to detect the encoding, it is still slow.

 <h2>
 Use selectolax instead of BeautifulSoup4 for HTML parsing
 <a name="use-selectolax-instead-of-beautifulsoup4-for-html-parsing" class="hash-link" href="#use-selectolax-instead-of-beautifulsoup4-for-html-parsing" title="Use selectolax instead of BeautifulSoup4 for HTML parsing">
 #
 </a>
 </h2><code>selectolax</code> is a Python binding to <a href="https://github.com/lexborisov/Modest/" target="_blank" rel="noopener noreferrer">Modest</a> and <a href="https://github.com/lexbor/lexbor" target="_blank" rel="noopener noreferrer">Lexbor</a> engines.
To install <code>selectolax</code> with pip:
<pre><code class="language-bash">pip install selectolax
</code></pre>
The usage of <code>selectolax</code> is similar to <code>BeautifulSoup4</code>.
<pre><code class="language-python">from selectolax.parser import HTMLParser

html = """
&lt;body>
 &lt;h1 class='>Welcome to selectolax tutorial&lt;/h1>
 &lt;div id="text">
 &lt;p class='p3'>Lorem ipsum&lt;/p>
 &lt;p class='p3'>Lorem ipsum 2&lt;/p>
 &lt;/div>
 &lt;div>
 &lt;p id='stext'>Lorem ipsum dolor sit amet, ea quo modus meliore platonem.&lt;/p>
 &lt;/div>
&lt;/body>
"""
# Select all elements with class 'p3'
parser = HTMLParser(html)
parser.select('p.p3')

# Select first match
parser.css_first('p.p3')

# Iterate over all nodes on the current level
for node in parser.css('div'):
 for cnode in node.iter():
 print(cnode.tag, cnode.html)
</code></pre>
For more information, please visit <a href="https://github.com/rushter/selectolax/blob/master/examples/walkthrough.ipynb" target="_blank" rel="noopener noreferrer">selectolax walkthrough tutorial</a>

 <h2>
 Use httpx instead of requests
 <a name="use-httpx-instead-of-requests" class="hash-link" href="#use-httpx-instead-of-requests" title="Use httpx instead of requests">
 #
 </a>
 </h2>Python <code>requests</code> is a HTTP client for humans. It is easy to use, but it is not fast. It only supports synchronous requests.
<code>httpx</code> is a fully featured HTTP client for Python 3, which provides sync and async APIs, and support for both HTTP/1.1 and HTTP/2.
It offers a standard synchronous API by default, but also gives you the option of an async client if you need it.
To install <code>httpx</code> with pip:
<pre><code class="language-bash">pip install httpx
</code></pre>
<code>httpx</code> offers the same api with <code>requests</code>:
<pre><code class="language-python">import httpx
async def main():
 async with httpx.AsyncClient() as client:
 response = await client.get('https://httpbin.org/get')
 print(response.status_code)
 print(response.json())

import asyncio
asyncio.run(main())
</code></pre>
For examples and usage, please visit <a href="https://www.python-httpx.org/" target="_blank" rel="noopener noreferrer">httpx home page</a>

 <h2>
 Use aiofiles for file IO
 <a name="use-aiofiles-for-file-io" class="hash-link" href="#use-aiofiles-for-file-io" title="Use aiofiles for file IO">
 #
 </a>
 </h2><code>aiofiles</code> is a Python library for asyncio-based file I/O. It provides a high-level API for working with files.
To install <code>aiofiles</code> with pip:
<pre><code class="language-bash">pip install aiofiles
</code></pre>
Basic usage:
<pre><code class="language-python">import aiofiles
async def main():
 async with aiofiles.open('test.txt', 'w') as f:
 await f.write('Hello world!')

 async with aiofiles.open('test.txt', 'r') as f:
 print(await f.read())

import asyncio
asyncio.run(main())
</code></pre>
For more information, please visit <a href="https://github.com/Tinche/aiofiles" target="_blank" rel="noopener noreferrer">aiofiles repository</a>

Build super fast web scraper with Python x100 than BeautifulSoup

Pandas is a Python library that provides a high-level interface to the data in SQL databases. It is a widely used data analysis tool that is used to create data visualizations and data analysis tools.
In this tutorial, we will learn how to convert an SQL query result to a Pandas DataFrame in Python. We will use the SQLite database for simplicity but any database that conforms to <a href="https://www.python.org/dev/peps/pep-0249/" target="_blank" rel="noopener noreferrer">PEP 0249</a> can be used. Hint: Use SQLAlchemy makes it possible to use any database supported by that library.
To convert an SQL query result to a Pandas DataFrame, we will use the <code>pandas.read_sql_query()</code> function.
Create the database in RAM
<pre><code class="language-python">import sqlite3
connection = sqlite3.connect(":memory:")
cursor = connection.cursor()
cursor.execute("CREATE TABLE users(id INTEGER PRIMARY KEY, name TEXT, age INTEGER)")
cursor.execute("INSERT INTO users VALUES(NULL, 'John', 42)")
cursor.execute("INSERT INTO users VALUES(NULL, 'Jane', 37)")
cursor.execute("INSERT INTO users VALUES(NULL, 'Jill', 30)")
cursor.execute("INSERT INTO users VALUES(NULL, 'Jack', 29)")
connection.commit()
</code></pre>
Create a query to read the data from the database
<pre><code class="language-python">query = "SELECT * FROM users"
</code></pre>
Let us execute the query and store the result in a Pandas DataFrame
<pre><code class="language-python">data = pd.read_sql_query(query, connection)
</code></pre>
Print the DataFrame
<pre><code class="language-python">print(data)
</code></pre>
The output of the above code is as follows:
<pre><code> id name age
0 1 John 42
1 2 Jane 37
2 3 Jill 30
3 4 Jack 29
</code></pre>

How to convert a SQL query result to a Pandas DataFrame in Python

Pandas is very useful for CSV processing. In this post, I will show you how to write a Pandas DataFrame to a .csv file in Python.
To write a Pandas DataFrame to a .csv file, you need to use the <a href="/pandas/reference/api/pandas.dataframe.to_csv">to_csv()</a> method.

 <h2>
 Writing a DataFrame to a .csv file
 <a name="writing-a-dataframe-to-a-csv-file" class="hash-link" href="#writing-a-dataframe-to-a-csv-file" title="Writing a DataFrame to a .csv file">
 #
 </a>
 </h2>Let check an example.
<pre><code class="language-python">import pandas as pd
df = pd.DataFrame({'col1': [1, 2, 3, 4, 5], 'col2': [6, 7, 8, 9, 10]})
print(df)
# Output
# col1 col2
# 0 1 6
# 1 2 7
# 2 3 8
# 3 4 9
# 4 5 10
df.to_csv('example.csv', index=False)
</code></pre>
<code>index=False</code> means that the index column will not be written to the .csv file. The default value is <code>True</code>.
The above code will output the following to the file <code>example.csv</code>:
<pre><code class="language-bash">col1,col2
1,6
2,7
3,8
4,9
5,10
</code></pre>

 <h2>
 Change the delimiter
 <a name="change-the-delimiter" class="hash-link" href="#change-the-delimiter" title="Change the delimiter">
 #
 </a>
 </h2>If you want to change the delimiter, you can use the <code>sep</code> parameter.
<pre><code class="language-python">df.to_csv('example.csv', index=False, sep=';')
</code></pre>
The above code will output the following to the file <code>example.csv</code>:
<pre><code class="language-bash">col1;col2
1;6
2;7
3;8
4;9
5;10
</code></pre>

 <h2>
 Change the datetime format
 <a name="change-the-datetime-format" class="hash-link" href="#change-the-datetime-format" title="Change the datetime format">
 #
 </a>
 </h2>If your data has a datetime format, you can use the <code>date_format</code> parameter.
Let check an example.
<pre><code class="language-python">import pandas as pd
from datetime import datetime

df = pd.DataFrame({
 'Datetime': [datetime(2021, 10, 26),
 datetime(2021, 10, 27)],
 'Todo': ['Write Python Tutorial', 'Read Javascript documentaion']
})

df.to_csv('example.csv', index=False)
</code></pre>
The above code will output the following to the file <code>example.csv</code>:
<pre><code class="language-bash">Datetime,Todo
2021-10-26,Write Python Tutorial
2021-10-27,Read Javascript documentaion
</code></pre>
Let change the datetime format to <code>%B %d %y</code>.
<pre><code class="language-python">df.to_csv('example.csv', index=False, date_format='%B %d %y')
</code></pre>
The new output will be:
<pre><code class="language-bash">Datetime,Todo
October 26 21,Write Python Tutorial
October 27 21,Read Javascript documentaion
</code></pre>
Further reading: Read more about Pandas&#39;s DataFrame.to_csv() method in the <a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html" target="_blank" rel="noopener noreferrer">Pandas documentation</a>.

How to write a Pandas DataFrame to a .csv file in Python

Nginx is one of the most popular web servers in the world and is responsible for hosting the largest and busiest sites on the Internet. In most cases, it is more resource friendly than Apache and can be used as a web server or reverse proxy. 
This tutorial will show you how to install the latest version of Nginx on Debian and Ubuntu.

 <h2>
 Install latest version of Nginx on Debian
 <a name="install-latest-version-of-nginx-on-debian" class="hash-link" href="#install-latest-version-of-nginx-on-debian" title="Install latest version of Nginx on Debian">
 #
 </a>
 </h2>Update the apt package index:
<pre><code class="language-bash">sudo apt update &amp;&amp; sudo apt upgrade -y
</code></pre>
Incase you have Nginx installed, you should remove it before installing the latest version.
<pre><code class="language-bash">sudo apt remove nginx -y
</code></pre>
Install the prerequisites:
<pre><code class="language-bash">sudo apt install curl gnupg2 ca-certificates lsb-release debian-archive-keyring
</code></pre>
Import an official nginx signing key so apt could verify the packages authenticity. Fetch the key:
<pre><code class="language-bash">curl https://nginx.org/keys/nginx_signing.key | gpg --dearmor \
 | sudo tee /usr/share/keyrings/nginx-archive-keyring.gpg >/dev/null
</code></pre>
Make sure the downloaded file contains the correct key.
<pre><code class="language-bash">gpg --dry-run --quiet --import --import-options import-show /usr/share/keyrings/nginx-archive-keyring.gpg
</code></pre>
The output should include the full fingerprint.
<pre><code class="language-bash">pub rsa2048 2011-08-19 [SC] [expires: 2024-06-14]
 573BFD6B3D8FBC641079A6ABABF5BD827BD9BF62
uid nginx signing key &lt;signing-key@nginx.com>
</code></pre>
If the fingerprint is different, remove the file.
To set up an apt repository for a stable nginx package, run the following command:
<pre><code class="language-bash">echo "deb [signed-by=/usr/share/keyrings/nginx-archive-keyring.gpg] \
http://nginx.org/packages/debian `lsb_release -cs` nginx" \
 | sudo tee /etc/apt/sources.list.d/nginx.list
</code></pre>
Set up repository pinning to prioritize our packages over the packages provided by the distribution.
<pre><code class="language-bash">echo -e "Package: *\nPin: origin nginx.org\nPin: release o=nginx\nPin-Priority: 900\n" \
 | sudo tee /etc/apt/preferences.d/99nginx
</code></pre>
You may see the following output:
<pre><code class="language-bash">Package: *
Pin: origin nginx.org
Pin: release o=nginx
Pin-Priority: 900
</code></pre>
To install nginx, run the following commands:
<pre><code class="language-bash">sudo apt update &amp;&amp; sudo apt install nginx -y
</code></pre>

 <h2>
 Install latest version of Nginx on Ubuntu
 <a name="install-latest-version-of-nginx-on-ubuntu" class="hash-link" href="#install-latest-version-of-nginx-on-ubuntu" title="Install latest version of Nginx on Ubuntu">
 #
 </a>
 </h2>Install the prerequisites:
<pre><code class="language-bash">sudo apt install curl gnupg2 ca-certificates lsb-release ubuntu-keyring
</code></pre>
Import the official nginx signing key so that apt can verify the authenticity of the package. Get the key.
<pre><code class="language-bash">curl https://nginx.org/keys/nginx_signing.key | gpg --dearmor \
 | sudo tee /usr/share/keyrings/nginx-archive-keyring.gpg >/dev/null
</code></pre>
Verify that the downloaded file contains the proper key:
<pre><code class="language-bash">gpg --dry-run --quiet --import --import-options import-show /usr/share/keyrings/nginx-archive-keyring.gpg
</code></pre>
Import Nginx Stable Repository
<pre><code class="language-bash">echo "deb [signed-by=/usr/share/keyrings/nginx-archive-keyring.gpg] \
http://nginx.org/packages/ubuntu `lsb_release -cs` nginx" \
 | sudo tee /etc/apt/sources.list.d/nginx.list
</code></pre>
Just like for Debian, pin the repository to the latest version.
<pre><code class="language-bash">echo -e "Package: *\nPin: origin nginx.org\nPin: release o=nginx\nPin-Priority: 900\n" \
 | sudo tee /etc/apt/preferences.d/99nginx
</code></pre>
To install nginx on Ubuntu, run the following commands:
<pre><code class="language-bash">sudo apt update
sudo apt install nginx
</code></pre>
To verify that the installation was successful, run the following command:
<pre><code class="language-bash">sudo nginx -v
</code></pre>
The output should be something like:
<pre><code class="language-bash">nginx version: nginx/1.20.1
</code></pre>

How to install the latest nginx on Debian and Ubuntu

Next.js is a framework for building web applications. Next.js gives you the best developer experience with all the features you need for production: hybrid static &amp; server rendering, TypeScript support, smart bundling, route pre-fetching, and more. No config needed. 
Nginx is a web server and reverse proxy that is used to serve HTTP requests. It is a high performance, light-weight, and easy-to-use web server. It is used to serve HTTP requests and to proxy HTTP requests to other servers.
In this tutorial, we will learn how to setup a Next.js app on nginx with PM2 and letsencrypt.

 <h2>
 1. Install Nginx, Node and certbot
 <a name="1-install-nginx-node-and-certbot" class="hash-link" href="#1-install-nginx-node-and-certbot" title="1. Install Nginx, Node and certbot">
 #
 </a>
 </h2>In your server console/terminal
<pre><code class="language-bash">cd ~ # go to the current user's home directory
curl -sL https://deb.nodesource.com/setup_14.x -o nodesource_setup.sh
sudo bash nodesource_setup.sh

sudo apt update
sudo apt install nginx nodejs certbot python3-certbot-nginx
</code></pre>
Also enable Nginx in ufw firewall.
<pre><code class="language-bash">sudo ufw allow 'OpenSSH' # needed for SSH connections
sudo ufw allow 'Nginx Full' # after installing Nginx!
sudo ufw enable
</code></pre>

 <h2>
 2. Setup letsencrypt with certbot
 <a name="2-setup-letsencrypt-with-certbot" class="hash-link" href="#2-setup-letsencrypt-with-certbot" title="2. Setup letsencrypt with certbot">
 #
 </a>
 </h2>You will need to point your domain to the server&#39;s IP by using A record in your DNS setting.
Edit the default Nginx configuration file.
<pre><code class="language-bash">sudo nano /etc/nginx/sites-available/default
</code></pre>
<blockquote>
You must change <code>example.com</code> to your actual domain name.
</blockquote>
<pre><code class="language-bash">server {
 # ...
 server_name example.com www.example.com;
 # ...
}
</code></pre>
Check if the nginx syntax is correct
<pre><code class="language-bash">sudo nginx -t
</code></pre>
Restart nginx
<pre><code class="language-bash">sudo systemctl restart nginx
</code></pre>
Run the following command let certbot to create a certificate for your domain.
<pre><code class="language-bash">sudo certbot certonly --nginx -d example.com -d www.example.com
</code></pre>

 <h2>
 3. Setup Reverse proxy with Nginx
 <a name="3-setup-reverse-proxy-with-nginx" class="hash-link" href="#3-setup-reverse-proxy-with-nginx" title="3. Setup Reverse proxy with Nginx">
 #
 </a>
 </h2>Edit the default Nginx configuration file.
<pre><code class="language-bash">sudo nano /etc/nginx/sites-available/default
</code></pre>
<pre><code class="language-bash"># ...

server {
 # ...
 server_name example.com www.example.com;
 # ...
 location / {
 # Reverse proxy for Next server
 proxy_pass http://localhost:3000;
 proxy_http_version 1.1;
 proxy_set_header Upgrade $http_upgrade;
 proxy_set_header Connection "upgrade";
 proxy_set_header Host $host;
 proxy_set_header X-Real-IP $remote_addr;
 proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
 proxy_set_header X-Forwarded-Proto $scheme;
 proxy_set_header X-Forwarded-Host $host;
 proxy_set_header X-Forwarded-Port $server_port;
 }
 # ...
}
</code></pre>
Check and restart Nginx
<pre><code class="language-bash">sudo nginx -t
sudo systemctl restart nginx
</code></pre>

 <h2>
 4. Setup Next.js with PM2
 <a name="4-setup-next-js-with-pm2" class="hash-link" href="#4-setup-next-js-with-pm2" title="4. Setup Next.js with PM2">
 #
 </a>
 </h2>Assuming you have a GitHub repository for the app
<pre><code class="language-bash">git pull https://github.com/user/repo.git myapp
cd myapp
npm install
npm run build
</code></pre>
Install PM2
<pre><code class="language-bash">npm install -g pm2
</code></pre>
To generate a sample configuration file you can type this command:
<pre><code class="language-bash">pm2 init 
</code></pre>
This will generate a sample ecosystem.config.js:
Edit the file and add the following lines:
<pre><code class="language-bash">{
 "apps": [
 {
 "name": "myapp",
 "script": "./server.js",
 "args": "start",
 "exec_mode": "cluster", # or fork
 "instances": 2, # Number of cluster instances
 "env": {
 "NODE_ENV": "production"
 }
 }
 ]
}
</code></pre>
Start the app with PM2
<pre><code class="language-bash">pm2 start ecosystem.config.js
</code></pre>
To stop the app with PM2
<pre><code class="language-bash">pm2 stop myapp
</code></pre>

How to setup next.js app on nginx + PM2 with letsencrypt

AI is currently very popular, and free courses are being offered in various places. The quality of the courses is very high, including those from major industry leaders, famous universities in the US, and materials from famous companies, etc. I think it&#39;s a great time to be able to learn this for free. I thought it would be useful to put them all together in one place, so I put them together. As for how to use it, I think it&#39;s better to complete one course that you feel suits you, rather than taking all of the courses introduced in this article. It will be more effective if you then supplement those courses with other courses.
This is as much as I could find, so I would be very grateful if you could point out to me that I should include this as well.

 <h2>
 1. AI For Everyone
 <a name="1-ai-for-everyone" class="hash-link" href="#1-ai-for-everyone" title="1. AI For Everyone">
 #
 </a>
 </h2>This course <code>AI For Everyone</code>, taught by Stanford University Professor Andrew Ng and can be taken without any prior knowledge of AI, and is recommended for those who want to know what AI is. There is a fee for taking the test and obtaining the certificate, but the course is free of charge.
You can learn more about the course at <a href="https://www.coursera.org/learn/ai-for-everyone" target="_blank" rel="noopener noreferrer">AI For Everyone - Coursera</a>.

 <h2>
 2. Machine Learning for Beginners (from Microsoft)
 <a name="2-machine-learning-for-beginners-from-microsoft-" class="hash-link" href="#2-machine-learning-for-beginners-from-microsoft-" title="2. Machine Learning for Beginners (from Microsoft)">
 #
 </a>
 </h2>A curriculum published by Microsoft on GitHub. This curriculum can be studied in 12 weeks / 24 lessons. The curriculum is designed to help people of all ages learn the basics of machine learning, and primarily uses the Scikit-learn library to teach &quot;classical machine learning&quot;.
The course is at <a href="https://github.com/microsoft/ML-For-Beginners" target="_blank" rel="noopener noreferrer">Machine Learning for Beginners</a>

 <h2>
 3. CS50’s Intro to Artificial Intelligence with Python
 <a name="3-cs50-s-intro-to-artificial-intelligence-with-python" class="hash-link" href="#3-cs50-s-intro-to-artificial-intelligence-with-python" title="3. CS50’s Intro to Artificial Intelligence with Python">
 #
 </a>
 </h2>This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation.
This course requires you to have a computer science background or at least one year of experience with Python, and is offered by <a href="https://cs50.harvard.edu/ai/2020/" target="_blank" rel="noopener noreferrer">CS50’s Introduction to Artificial Intelligence with Python</a>.

 <h2>
 4. EDX Artificial Intelligence (AI)
 <a name="4-edx-artificial-intelligence-ai-" class="hash-link" href="#4-edx-artificial-intelligence-ai-" title="4. EDX Artificial Intelligence (AI)">
 #
 </a>
 </h2>Learn the basics of Artificial Intelligence and apply it. Design intelligent agents to solve real-world problems such as search, games, machine learning, logic, and constraint satisfaction problems.
You can enroll in this course at <a href="https://www.edx.org/course/artificial-intelligence-ai" target="_blank" rel="noopener noreferrer">EDX Artificial Intelligence</a>.

 <h2>
 5. Artificial Intelligence for Robotics(Stanford University via Udacity)
 <a name="5-artificial-intelligence-for-robotics-stanford-university-via-udacity-" class="hash-link" href="#5-artificial-intelligence-for-robotics-stanford-university-via-udacity-" title="5. Artificial Intelligence for Robotics(Stanford University via Udacity)">
 #
 </a>
 </h2>This class will teach you basic methods in Artificial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics
Link to the course: <a href="https://www.classcentral.com/course/udacity-artificial-intelligence-for-robotics-319" target="_blank" rel="noopener noreferrer">Artificial Intelligence for Robotics</a>

 <h2>
 6. Knowledge Based Artificial Intelligence (from Udacity)
 <a name="6-knowledge-based-artificial-intelligence-from-udacity-" class="hash-link" href="#6-knowledge-based-artificial-intelligence-from-udacity-" title="6. Knowledge Based Artificial Intelligence (from Udacity)">
 #
 </a>
 </h2>This is a core course in artificial intelligence. It is designed to be a challenging course, involving significant independent work, readings, assignments, and projects. It covers structured knowledge representations, as well as knowledge-based methods of problem solving, planning, decision-making, and learning.
The link to the course is <a href="https://www.udacity.com/course/knowledge-based-ai-cognitive-systems--ud409" target="_blank" rel="noopener noreferrer">Knowledge Based Artificial Intelligence</a>

 <h2>
 7. Machine Learning Crash Course By Google
 <a name="7-machine-learning-crash-course-by-google" class="hash-link" href="#7-machine-learning-crash-course-by-google" title="7. Machine Learning Crash Course By Google">
 #
 </a>
 </h2>Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
You can learn more about the course at <a href="https://developers.google.com/machine-learning/crash-course" target="_blank" rel="noopener noreferrer">Machine Learning Crash Course</a>.

 <h2>
 8. Intro to Artificial Intelligence (from Udacity)
 <a name="8-intro-to-artificial-intelligence-from-udacity-" class="hash-link" href="#8-intro-to-artificial-intelligence-from-udacity-" title="8. Intro to Artificial Intelligence (from Udacity)">
 #
 </a>
 </h2>Learn the Fundamentals of AI. Course run by Peter Norvig
Link to the course: <a href="https://www.udacity.com/course/intro-to-artificial-intelligence--cs271" target="_blank" rel="noopener noreferrer">Intro to Artificial Intelligence</a>

 <h2>
 9. Elements of AI
 <a name="9-elements-of-ai" class="hash-link" href="#9-elements-of-ai" title="9. Elements of AI">
 #
 </a>
 </h2>Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want as many people as possible to learn what AI is, what it can (and can&#39;t) do, and how to start creating AI methods. The course combines theory with practical exercises and can be completed at your own pace.
You can check out the course at <a href="https://course.elementsofai.com" target="_blank" rel="noopener noreferrer">Elements of AI</a>

 <h2>
 10. Exam AI-900: Microsoft Azure AI Fundamentals
 <a name="10-exam-ai-900-microsoft-azure-ai-fundamentals" class="hash-link" href="#10-exam-ai-900-microsoft-azure-ai-fundamentals" title="10. Exam AI-900: Microsoft Azure AI Fundamentals">
 #
 </a>
 </h2>This course, offered by Microsoft Japan Corporation, is designed to teach the basics of AI and to help students acquire the Microsoft AI-900 certification. The course is designed to teach the basics of AI and to help students obtain the Microsoft AI-900 certification. General knowledge and experience in programming is preferred as prerequisite knowledge. The course duration is approximately 9 hours.
Link to the course: <a href="https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900" target="_blank" rel="noopener noreferrer">Exam AI-900: Microsoft Azure AI Fundamentals</a>

10 free AI courses you should learn to be a master

Apache Cassandra is an open source NoSQL distributed database that delivers scalability and high availability without compromising performance and is trusted by thousands of companies. Linear scalability and proven fault tolerance on commodity hardware and cloud infrastructure make it an ideal platform for mission-critical data. This tutorial describes how to install Apache Cassandra on an Ubuntu 20.04 server.

 <h2>
 Prerequisites
 <a name="prerequisites" class="hash-link" href="#prerequisites" title="Prerequisites">
 #
 </a>
 </h2><ul>
<li>An Ubuntu 20.04 server</li>
<li>Create a non-root user with sudo access.</li>
<li>For using cqlsh, the latest version of Python 2.7 or Python 3.6+. To verify that you have the correct version of Python installed, type <code>python --version</code></li>
</ul>

 <h2>
 Install Apache Cassandra
 <a name="install-apache-cassandra" class="hash-link" href="#install-apache-cassandra" title="Install Apache Cassandra">
 #
 </a>
 </h2><ol>
<li>Install Java 8
 Install the latest version of Java 8, either the Oracle Java Standard Edition 8 or OpenJDK 8.
<pre><code class="language-bash">$ sudo apt install openjdk-8-jdk -y
</code></pre>
 To verify that you have the correct version of java installed, type <code>java -version</code>.
<pre><code class="language-bash">$ java -version
</code></pre>
 The out may be:
<pre><code>openjdk version &quot;1.8.0_222&quot;
OpenJDK Runtime Environment (build 1.8.0_222-8u222-b10-1ubuntu1~16.04.1-b10)
OpenJDK 64-Bit Server VM (build 25.222-b10, mixed mode)
</code></pre>
</li>
<li>Install the required dependencies.
<pre><code>$ sudo apt install apt-transport-https gnupg2 -y
</code></pre>
</li>
<li>Download and add the Apache Cassandra GPG key.
<pre><code class="language-bash">$ sudo wget -q -O - https://www.apache.org/dist/cassandra/KEYS | sudo apt-key add -
</code></pre>
 You may see the output:
<pre><code>% Total % Received % Xferd Average Speed Time Time Time Current
 Dload Upload Total Spent Left Speed
100 266k 100 266k 0 0 320k 0 --:--:-- --:--:-- --:--:-- 320k
OK
</code></pre>
</li>
<li>Add the Apache Cassandra repository to your system.
<pre><code class="language-bash">$ echo "deb http://www.apache.org/dist/cassandra/debian 40x main" | sudo tee -a /etc/apt/sources.list.d/cassandra.sources.list
</code></pre>
</li>
<li>Update the package index.
<pre><code class="language-bash">$ sudo apt-get update
</code></pre>
</li>
<li>Install Apache Cassandra.
<pre><code class="language-bash">$ sudo apt-get install cassandra -y
</code></pre>
</li>
<li>Verify that Apache Cassandra is installed.
<pre><code class="language-bash">$ dpkg -l | grep cassandra
</code></pre>
</li>
<li>Verify that Apache Cassandra is running.
<pre><code class="language-bash">$ sudo systemctl status cassandra
</code></pre>
</li>
<li>Verify the stats of your node.
<pre><code class="language-bash">$ sudo nodetool status
</code></pre>
 The status column in the output should report UN which stands for &quot;Up/Normal&quot;.
 Alternatively, connect to the database with:
<pre><code class="language-bash">$ cqlsh
</code></pre>
 The output should look something like this:
<pre><code>Connected to Test Cluster at localhost:9042.
[cqlsh 5.0.1 | Cassandra 3.8 | CQL spec 3.4.2 | Native protocol v4]
Use HELP for help.
</code></pre>
</li>
</ol>

 <h2>
 Configuring Apache Cassandra
 <a name="configuring-apache-cassandra" class="hash-link" href="#configuring-apache-cassandra" title="Configuring Apache Cassandra">
 #
 </a>
 </h2>The Cassandra configuration files location varies, depending on the type of installation:
<ul>
<li>tarball: <code>conf</code> directory within the tarball install location</li>
<li>package: <code>/etc/cassandra</code> directory</li>
</ul>
Since we are installing using a package, we will use the <code>/etc/cassandra</code> directory.
<ol>
<li>Edit the <code>cassandra.yaml</code> file.
<pre><code class="language-bash">$ sudo nano /etc/cassandra/cassandra.yaml
</code></pre>
 The file is a YAML file that contains the configuration for Apache Cassandra.
 The file is divided into sections. The sections are separated by a line that starts with a <code>#</code> character.
 Let update the <code>cluster_name</code> section.
<pre><code class="language-bash"># cluster_name: The name of the cluster.
cluster_name: My First Cluster
</code></pre>
 The <code>cluster_name</code> section is used to identify the cluster.
</li>
<li>Clear the system cache
<pre><code class="language-bash">$ nodetool flush system
</code></pre>
 The <code>flush system</code> command clears the system cache.
 The system cache is used to store information about the cluster. This information is used to speed up the cluster startup. The system cache is cleared by running the <code>flush system</code> command. This command is useful when you want to start up the cluster with a different configuration. For example, you might want to start up the cluster with a different number of nodes. 
</li>
<li>Restart the Cassandra service.
<pre><code class="language-bash">$ sudo systemctl restart cassandra
</code></pre>
 The <code>systemctl</code> command is used to start, stop, restart, and enable/disable the service. 
</li>
<li>Verify the change
<pre><code class="language-bash">$ cqlsh
</code></pre>
</li>
</ol>

How to install Apache Cassandra on Ubuntu 20.04

The simple answer is yes but the truth is a little more complicated.

Yes the application will still be running; it'll resume with the rest of the system's processes. There are, however, stateful things like <a href="/why-are-my-network-connections-being-rejected" rel="dofollow">network connections</a> and graphics driver states. These need to reinitialise with external hardware and that may mean some added network latency to begin with, or even a proper disconnect-reconnect (as happens to me on Ethernet). In particularly bad situations —definitely exceptions to the rule— the entire desktop environment can crash and restart.

So I can't guarantee what'll happen to you. If your application will crash if it loses network connectivity, there might be an issue. If it's doing rendering or CUDA/OpenCL stuff, it might break.

If it's just a plain CPU/disk stuff, it should be fine. 
But who knows for certain. Computers make fools of us all. 
Good luck.
 When you suspend the system (put it to sleep), it stores all its <a href="/why-are-cpu-registers-fast-to-access" rel="dofollow">CPU registers</a> etc. that represent what it's currently doing in your RAM and then powers down most components except those that preserve RAM contents and those that are needed to wake the computer up again later (input devices, etc).

When you wake it up later again, the previous state gets restored and the computer continues exactly at the point where you had suspended it.

That is the main concept, of course in reality there happens more because all this doesn't magically happen when snipping your fingers. There are many system scripts etc involved that get run before suspending and after waking up. 

However, unless you manually set something up to do that, suspending the computer will never close any running applications. There is a small risk that something crashes in the process, but normally if it worked once, it works always.
 If the laptop goes to sleep (=suspend), definitely yes. The only thing that can be disrupted are network connections or similar, real-time thing; in that case, it depends if the running program is safely written to accept temporary failures and recover. 

If the laptop powers off, definitely no --- there is an option somewhere in the Control Panel to decide between the two behaviors, I think.

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