Welcome. I can't wait to help you build automations without code.

I have either created or tested these resources. They come with my seal of approval, and I hope they serve as a valuable resource for you.

These mini no-code projects are great complementary material to this course.

To make sure you have the best learning experience on this course, please review the statements in this lecture to tailor the course to your specific learning needs.

Here, you'll be learning about the fundamentals of the no-code (automation) ecosystem. Later in this course, as you begin building your projects, an understanding of these fundamentals will be beneficial.

In this lecture, I want to clarify no-code automation. What is no-code automation? How does no-code automation work? Etc.

In this lecture, let's talk about no-code stacks, i.e. no-code tools.

In this lecture, I want to discuss adopting a systems mindset with you.

For this project, we’ll build a web scraper for competitor price monitoring. Specifically, our scraper will be extracting the name and price of each book from a fictional online book store.

You'll need these resources to complete this project.

In this lecture, we’ll set up our web scraper.

In this lecture, we'll save our web scraper.

In this lecture, we’ll set up a database in Airtable.

In this lecture, we'll be scraping multiple pages for our data.

Congratulations on completing this project. Now, why not challenge your capabilities? Try implementing one of these suggestions. Or try your own.

In this lecture, we’ll configure Twitter in Zapier.

For this project, we’ll be scraping Quotes To Scrape. Specifically, the quote and author of each quote. We’ll be turning our web scraper and scraped data into an API. That will create a level of automation as we could query the API.

In this lecture, we'll set up our API in Parabola.

In this lecture, we'll be filtering unnecessary data.

In this lecture, we'll export the data to Google Sheets.

In this lecture, we'll publish the flow.

For this project, we'll be creating an automated data enrichment workflow. The automated workflow will enrich data with more valuable data. Specifically, we'll be feeding our process with URLs. And, the workflow will return the logos for each of those companies without any manual intervention.

In this lecture, we’ll set up the Google Sheet that will house the prospects data.

For this project, we’ll be automatically populating an Airtable database with Elon Musk’s tweets. This project will teach you how to use Airtable as a database. And how to automate manual tasks in Airtable.

In this lecture, we’ll configure Airtable in Zapier.

For this project, we’ll be creating an automated sales pipeline database in Airtable. It will only be a two stages sales pipeline. A contact will get moved, automatically, to the next stage in the pipeline when they’ve gotten selected as having been contacted. The fictional sales team will get an email too.

In this lecture, we’ll source the links for data on prospects.

In this lecture, we’ll set up Airtable as a sales database.

In this lecture, we'll set up the email automation in Airtable.

In this lecture, we'll set up an automation to move leads.

For this project, we'll be building an automated Reddit content curator in Zapier. Our automation will extract the hottest posts from a subreddit and add them to a Google Sheet: creating our automated content curation tool.

In this lecture, we'll set up a Phantom in Phantombuster.

In this lecture, we’ll set up the Google Sheet that will house our outputs.

In this lecture, we’ll configure Reddit in Zapier.

In this lecture, we'll configure Google Sheets in Zapier.

For this project, we'll create a Twitter post scheduler. Our automation will keep track of any updates to a Google Sheet. If it finds an update, it will post it as a tweet to Twitter automatically. This project will teach you how to use Zapier to automate your social media operations.

In this lecture, we’ll set up the Google Sheet that will house our posts.

In this lecture, we’ll configure Google Sheets in Zapier.

In this lecture, we'll configure Twitter in Zapier.

For this project, we’ll be automating a marketing (prospect generation) task in Phantombuster. Our automation will gather numerous prospects. It’ll return crucial data: phone, email, address, etc. We’ll be collecting the data from Google Maps. If this were to get done manually, it would take tens of hours.

In this lecture, we'll clean the CSV data in Parabola.

In this lecture, we'll publish the automation.

In this lecture, we'll insert an IF/ELSE column to convert the sentiment score.

For this project, we’ll be creating a data-driven content idea generator. The automation will gather popular topics from various sources and see which content type has the best chance for success. Specifically, we’ll be picking popular topics from Medium and Reddit.

In this lecture, we'll edit the Reviews Sentiment Score column.

In this lecture, we’ll set up the Google Sheet that will house the content insights.

In this lecture, we’ll source the links we wish to analyse for content insights.

In this lecture, we'll set up Medium in Phantombuster.

In this lecture, we'll set up Reddit in Phantombuster.

In this lecture, we'll clean the data for insights in Parabola.

For this project, we'll be creating a sentiment analyzer. The sentiment analyzer will score the sentiment of a string of text automatically. It will tell us whether a string of text is positive, negative, or neutral. Specifically, we'll be running a bunch of online reviews through our sentiment analysis tool.

In this lecture, we'll be setting up Parabola and importing our data.

In this lecture, we'll insert a column for enriched data.

In this lecture, we'll insert the sentiment analysis function.

In this lecture, we'll format the numbers in the sentiment analysis columns.

In this lecture, we'll insert the API enrichment function.

In this lecture, we'll remove unnecessary columns.

For this project, we'll be creating a browser automation to auto-follow Twitter users. Functionality wise, our browser automation will go-to Twitter. Then, log-in. It will loop through each user that we want to follow and follow them.