UiPath Foundations A-Z

Automate navigating to the add order screen in UiPath by combining tap into, clicking options, typing 1, and clicking go now, opening the new order window for bot automation.

Learn to log order details in a single UiPath message with each item on a new line, including product code, units ordered, price, total price, date ordered, and scope.

Read excel data into a data table with UiPath, then iterate each row to log product code, quantity, and unit price to the console.

Learn to extend your orders data table in UiPath foundations A-Z by adding total price, cost center, state ordered, and orderer, update headings, and sync changes to the Excel document.

Apply a filter data table to remove rows with no record found in the product code, then save the filtered orders table back to the same Excel sheet.

Automate the Australian business number lookup across browsers with UiPath, from Internet Explorer to Chrome and Firefox, including Citrix. Run parallel automations to reduce licensing costs and speed results.

Automate car listing creation by filling the transmission, price, and terms and conditions checkboxes, then submitting the form to add cars to the list and test the bot.

Learn to dynamically select dropdown options in UiPath by using selectors and mustache variables to handle changing lists, avoiding long if statements and maintaining robust automation.

Add a new field to a screen-scraping workflow by selecting an invoice item and using get OCR text with a clipping region to extract the invoice number and date.

Leverage OCR to read contents from a document image, output the text, and extract sections such as the invoice number for console display.

Install python with Anaconda, create a conda environment, install required machine learning packages and pillow via pip, then verify packages to enable pokemon recognition.

Learn how to run a Python prediction script in Anaconda, feeding an image, a model file, and a labels dictionary to predict the top Pokemon.

UiPath foundations teaches how to integrate Python to run a machine learning model that recognizes Pokemon from an image, using a predict function with image path, model, and labels.