Python for Automation
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- Live or Self-paced
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Book live on Noble DesktopSummary
In this class, you’ll learn how to automate time-consuming tasks using Python, such as gathering data from websites. Whether your interests lie in social media, e-commerce, real estate, travel, or government affairs, the ability to instantly collect up-to-date data from across the web can be a significant advantage. You'll use Python code to extract the precise data you need from a website. Along the way, you’ll also learn to write loops that allow your web scraping code to process a large number of pages for you.
These fundamentals will be coupled with real-life examples of programs that scrape valuable data from major websites. The class will also cover common pitfalls, how to run your programs on a schedule, and different formats for storing your scraped data. This course is perfect for any programming beginner to be introduced to the powerful world of coding, and is a great fit for students with a clearly defined goal of using Python for web or software development. This course is included in our Data Science Certificate.
Who this course is for
Employees whose jobs involve any repetitive work in the browser Entrepreneurs running small businesses that need to run efficiently Individuals looking to learn automation techniques for personal or professional use Those interested in a career in automated software testing
Prerequisites
Participants should have knowledge equivalent to our Python for Data Science Bootcamp course.
Curriculum
What you'll learn
- Understand how websites are structured with HTML and CSS to identify elements for data extraction
- Learn Python fundamentals, such as variables, data types, conditionals, loops, and list manipulation
- Use the Requests and Beautiful Soup libraries to perform web scraping and target specific content
- Write loops to automate web scraping across multiple pages and streamline repetitive tasks
- Store scraped data in different formats, such as text files and CSVs, for analysis and reporting
- Schedule Python scripts to run on a regular basis, enabling continuous data collection and automating workflows
Course syllabus
Section 1
Introduction to HTML/CSS (Online)
- How a website is served
- Anatomy of a web page
- HTML tags
- IDs
- CSS classes
Python Part 1
- Integers + Floats
- Variables
- Strings
- Methods + Functions
Section 2
Webscraping Exercise Part 1
- Introduction to using packages
- Requests packages
- Performing a GET request
- String manipulation
- Debugging a Python script
Python Part 2
- Booleans
- Conditional Statements
- Lists
- Indexing into strings + lists
- Looping over lists
Section 3
Webscraping Exercises Part 2
- Beautiful Soup package
- Honing in on data
- Common webscraping pitfalls
- Using loops in webscraping
Storage and Scheduling
- Text files
- CSVs
- Scheduling a Python Script
What's included
- Free course retake within one year to refresh the material and gain practice.
- Class recordings
Stated by the provider. Confirm what your tuition covers before enrolling.
Live classes
Choose dates and book your instructor-led class on nobledesktop.com.
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In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
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In-person or live online
Starts at 18:00 · America/New_York (EDT); final session ends at 21:00 EDT
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In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
-
In-person or live online
Starts at 10:00 · America/New_York (EST); final session ends at 17:00 EST
-
In-person or live online
Starts at 10:00 · America/New_York (EST); final session ends at 17:00 EST
-
–
In-person or live online
Starts at 18:00 · America/New_York (EST); final session ends at 21:00 EST
-
In-person or live online
Starts at 10:00 · America/New_York (EST); final session ends at 17:00 EST
-
In-person or live online
Starts at 10:00 · America/New_York (EST); final session ends at 17:00 EST
-
In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
-
In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
-
In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
-
–
In-person or live online
Starts at 18:00 · America/New_York (EDT); final session ends at 21:00 EDT
-
In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
-
In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
-
In-person or live online
Starts at 10:00 · America/New_York (EDT); final session ends at 17:00 EDT
-
–
In-person or live online
Starts at 18:00 · America/New_York (EDT); final session ends at 21:00 EDT
-
In-person or live online
Starts at 10:00 · America/New_York (EST); final session ends at 17:00 EST
-
In-person or live online
Starts at 10:00 · America/New_York (EST); final session ends at 17:00 EST
-
In-person or live online
Starts at 10:00 · America/New_York (EST); final session ends at 17:00 EST
Confirm current dates and availability on Noble Desktop before booking.
Self-paced course
Learn through recorded lessons on your own schedule.
This course is available for 30 days. You can choose when to start your access period. Once you activate, you will have 30 days to complete it (access the course materials, quizzes, projects and videos). You may request one extension of seven (7) days. Other extension requests will be evaluated on a case-by-case basis. Videos are not downloadable.
- Tuition
- $425
- Course length
- 6 hours
- Schedule
- On your schedule
In this class, you’ll learn how to automate time-consuming tasks using Python such as gathering data from the internet. Whether your interests lie in social media, e-commerce, real estate, travel or government affairs, the ability to instantly collect up-to-date data across the web can be a big advantage.
Use Python code to grab precisely the data you want from a website. Along the way, you’ll learn how to write loops so that your web scraping code can process a large number of pages for you.
These fundamentals will be coupled with real-life examples of programs that can scrape valuable data from major websites. The class will also cover common pitfalls, how to run your programs on a regular schedule, and different formats for storing your scraped data.
This course is perfect for any programming beginner being introduced to the powerful world of coding, and is a great fit for students with a clearly defined learning goal of using Python for web or software development. This course is included in our Data Science & AI Certificate Online (Self-Paced).
Who the self-paced course is for
Employees whose jobs involve any repetitive work in the browser Entrepreneurs running small businesses that need to run efficiently Individuals looking to learn automation techniques for personal or professional use Those interested in a career in automated software testing
Self-paced prerequisites
Participants should have knowledge equivalent to our Python for Data Science Bootcamp course.
Self-paced curriculum
What you'll learn self-paced
- The syntax of Python and how to construct programs
- How to run your programs on a regular schedule
- Identify and correct common errors
- How to write scripts that automate manual tasks
- How to update Excel files automatically using Python
Self-paced syllabus
Section 1
Introduction to HTML/CSS (Online)
- How a website is served
- Anatomy of a web page
- HTML tags
- IDs
- CSS classes
Python Part 1
- Integers + Floats
- Variables
- Strings
- Methods + Functions
Section 2
Webscraping Exercise Part 1
- Introduction to using packages
- Requests packages
- Performing a GET request
- String manipulation
- Debugging a Python script
Python Part 2
- Booleans
- Conditional Statements
- Lists
- Indexing into strings + lists
- Looping over lists
Section 3
Webscraping Exercises Part 2
- Beautiful Soup package
- Honing in on data
- Common webscraping pitfalls
- Using loops in webscraping
Storage and Scheduling
- Text files
- CSVs
- Scheduling a Python Script
What's included with self-paced
- Self-paced video lessons
Self-paced lessons
Watch free previews and explore the lessons included with enrollment at Noble Desktop.
Python for Automation Course Online (Self-Paced)
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APIs Intro
Lesson 1: APIs
5:05
Access data from an API using Python by sending an HTTP request to a specific URL and receiving the expected data response.
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Enrollment required
API Keys
Lesson 1: APIs
8:13
Explore the setup and use of the AlphaVantage stock market data API, including obtaining an API key and configuring a Python program to request stock data.
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Enrollment required
HTTP Status Codes
Lesson 1: APIs
5:03
Access an API using Python's requests library to send a GET request to a URL, check the response's status code for errors, and handle data retrieval upon receiving a 200 OK status.
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Enrollment required
JSON
Lesson 1: APIs
3:58
Convert a JSON string response from a web request into a Python dictionary or list using the .json() method from the requests library.
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Enrollment required
Challenge 1 Navigating API Data
Lesson 1: APIs
0:47
Navigate the data variable to find and print the stock information for Apple on the specified date.
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Challenge 1 Navigating API Data Solution
Lesson 1: APIs
4:29
Access the desired date's data within the time series daily key in the API response dictionary, then retrieve the closing value for Apple on that date.
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Making a Dataframe From Api Data
Lesson 1: APIs
4:22
Transpose the data frame, convert strings to numeric values, and format the index as date times for easier data manipulation.
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Enrollment required
Challenge 2 Finding Highest Value
Lesson 1: APIs
0:53
Find the highest and lowest stock prices and their respective dates from the data frame.
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Challenge 2 Finding Highest Value Solution
Lesson 1: APIs
3:07
Find the highest apple price using the numeric value in the dataset and identify the date of that price.
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Plotting Our Api Data and a Plotting Challenge
Lesson 1: APIs
3:29
Plot the low and high apple prices using pyplot's scatterplot method by identifying the lowest and highest prices with their corresponding dates and adding these points to the existing graph.
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Plotting Our Data With Bmh and Scatter
Lesson 1: APIs
1:47
Add scatter plots for the highest and lowest apple prices using green and red markers respectively.
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APIs Conclusion
Lesson 1: APIs
3:13
Access data using APIs by researching, understanding their structure, and extracting information with minimal code.
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Data Scraping Intro
Lesson 2: Data Scraping
4:37
Access data by programmatically scraping it from third-party websites while considering ethical and legal implications.
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Enrollment required
Data Scraping and HTML
Lesson 2: Data Scraping
7:04
Learn to understand and utilize HTML structure for web scraping by identifying and inspecting elements like headings (H3) to extract specific data efficiently.
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Enrollment required
Our First Data Scraping
Lesson 2: Data Scraping
8:54
Parse an HTML page using BeautifulSoup to extract and print specific text elements like act and scene names from H3 tags.
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Enrollment required
Accessing One Part of a Page
Lesson 2: Data Scraping
4:19
Use BeautifulSoup to extract the desired text from the HTML.
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Challenge 3: Scraping on Your Own
Lesson 2: Data Scraping
0:51
Scrape and print specified text from the page, then find and print the text of the first 10 tags.
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Enrollment required
Challenge 4: Scraping on Your Own
Lesson 2: Data Scraping
3:04
Identify and extract text from specific HTML elements using BeautifulSoup for web scraping.
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More Complex Data Scraping Queries
Lesson 2: Data Scraping
8:37
Extract attribute values from HTML elements and find nested elements within specified parent elements.
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Challenge: Scraping a New Page
Lesson 2: Data Scraping
3:14
Scrape book titles and prices from books2scrape.com using the requests and Beautiful Soup libraries.
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Challenge: Scraping a New Page Solution
Lesson 2: Data Scraping
12:49
Extract book titles and prices from a webpage using BeautifulSoup by identifying specific HTML tags, handling issues with truncated titles and currency symbols, and converting prices to numerical values.
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Saving our Scraped Data in a Dataframe
Lesson 2: Data Scraping
1:33
Convert data into a Pandas DataFrame and prepare to scrape all pages for complete results.
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Challenge: Scraping the Page Number Max
Lesson 2: Data Scraping
1:36
Extract the text from the page element indicating "page 1 of 50" and retrieve the last word to determine the total number of pages.
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Challenge: Scraping the Page Number Max Solution
Lesson 2: Data Scraping
3:36
Extract the maximum page number by finding the LI element with the class "current," splitting its text into words, and converting the last word to an integer.
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Scraping an Entire Website
Lesson 2: Data Scraping
8:41
Loop through pages, scrape book titles and prices, and compile into a data frame with 1,000 entries.
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Comparing APIs and Data Scraping
Lesson 3: Comparing APIs and Data Scraping
3:35
Compare using APIs and web scraping in Python to access structured and unstructured data, respectively.
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