AI Automation Engineer course

“Hello and welcome to this quick tutorial where we learn how to install Microsoft Power Automate Desktop. Let’s get started.

To begin, we need a free automation tool from Microsoft called Microsoft Power Automate Desktop, often referred to as PAD. It is completely free, safe to use, and extremely powerful for automating routine work. Open Google Chrome and type: Download Microsoft Power Automate Desktop. Make sure you select the desktop version and not the web version. The first link you will see is the official Microsoft download page. Click on it to continue.

Once the page opens, scroll down until you find the section titled Install Power Automate using the MSI installer. This is the correct installer for Windows. Click the download link and the file will begin downloading. When the download is complete, open the file and start the installation. The setup will guide you through the process automatically. When you see the message Installation Successful, click Close to finish.

Now press the Windows key on your keyboard and search for Power Automate. You will see the application icon appear in the search results. Click on it to open the program. The first time you launch it, Power Automate Desktop will ask you to sign in. Use your Microsoft account, click Next, and then click Get Started. After a moment, you will arrive at the main home window of Power Automate Desktop, where all your flows and automation tools are available.

From here, you are ready to begin building your first automation. If you want to explore more about Power Automate basics or learn how to create your first flow, we can continue step by step in next video.

I hope you enjoy this video and I will see you in next.

“Hello and welcome to this tutorial, where we’re going to learn how to download a report from a website using a specific date range with the help of Microsoft Power Automate Desktop. Let’s jump straight into it and get started.

This is my personal learning website, created specifically for automation practice. It looks like a professional dashboard, even though I’m not a web designer. I actually built it with the help of AI, which is exciting, and later in this course I will also teach you how to build a website like this using simple prompts and automation concepts. If you want to explore more about AI automation or web dashboards, we can dive deeper anytime.

Now let’s open Power Automate Desktop. On the top‑left corner, you’ll see the plus button. Click on it and choose New Flow. A small pop‑up will appear asking for the flow name. You can give any name you prefer, and then click Create. After a moment, the main screen will load. On the left side, you’ll see the traditional File and Edit menus, and below that, the list of actions we will use in this flow. The center area is where our automation steps will appear, and on the right side, you’ll find the variables panel.

We’ll begin with our first action, which is opening the browser. Under Browser Automation, you’ll see options for Internet Explorer, Firefox, Chrome, and Microsoft Edge. I’ll select Microsoft Edge and drag it into the center screen. A pop‑up will appear with several fields. The launch mode will stay the same. In the Initial URL field, paste the website link where your report is available. Change the Window State from Normal to Maximized, keep the rest of the settings as they are, and click Save. Our first action is now ready.

To test it, click the Play button. Power Automate will start processing, open Microsoft Edge automatically, and load the webpage using the link we provided. Everything looks good so far.

Next, we need to click on the username field. For this, search for the action called Populate Text Field on Web Page. Drag it into the main screen. A pop‑up will appear again. The Web Browser Instance and Browser fields will already be selected. In the UI Element field, click the dropdown and choose Add UI Element. A message will appear saying you haven’t picked any UI element yet. To capture it, hold the Control key and click on the username box on the webpage. You’ll see a red outline indicating it has been detected. Once selected, it will return to the flow window, and you can even hover over the small icon to see the captured screenshot. In the text field, type the username “admin” and click Save.

We’ll repeat the same process for the password field. Capture the password box and type “password123,” which you can use for learning purposes.

Now we need to click the login button. Search for Click Link on Web Page, drag it into the flow, and capture the “Access Dashboard” button. Since this button doesn’t require typing, we only need to capture the UI element. To test everything, press Play again. The automation should log in successfully and take you to the landing page.

Next, we need to handle the date fields, which can be a little tricky, but AI makes it much easier. The challenge is that we want the automation to select the correct date automatically. For example, if you’re downloading yesterday’s sales report, the system should calculate the date without you entering it manually. To solve this, we’ll use a VBA script inside Power Automate Desktop. I already have a prompt prepared for this, and you can download all prompts at the end of the course.

We’ll add another Click Link on Web Page action and capture the From Date field. Then we’ll repeat the same for the To Date field. After that, I’ll open my prompt from Notepad, copy it, and paste it into Copilot. Copilot will generate the VBA script for us. Once the script is ready, copy it.

Now search for Script inside Power Automate. You’ll see an action called Run VB Script. Drag it between the last two actions. A small window will appear asking for the script. Paste the VBA code and click Save. Then copy this same script action and paste it below the To Date action so both date fields are automated.

The final step is to click the download button for the report. Use the Click Link on Web Page action again and capture the download button.

Our flow is now complete. To test everything, press the Play button and sit back. The automation will open the browser, log in, enter the dates, run the script, and download the report automatically. It’s impressive to see all these steps happening without any manual work.

In the next video, we’ll build the Excel dashboard report and apply a macro inside Excel that will handle the rest of the tasks, such as copying data from the dataset, saving the report as a PDF, copying the main dashboard page, opening Outlook, attaching the report, writing the email body, inserting the dashboard image, and sending the email. Imagine all of this happening with a single click.

I hope you enjoyed this tutorial, and I’ll see you in the next one.”

“Hello and welcome to this tutorial. In the previous lesson, we learned how Microsoft Power Automate Desktop works, and we created actions and flows that logged into a dataset page and downloaded the dataset file automatically. In this video, we will continue that process by learning how to open the Excel dashboard report, paste the downloaded dataset, and send the final email. This completes the entire end‑to‑end reporting procedure. It sounds interesting, so let’s jump right in.

For this automation, we need a Microsoft Excel VBA script. If you are not familiar with VBA, don’t worry. I also don’t write VBA code manually. We will generate the entire script using the free Copilot AI version with a single prompt. The secret is very simple: we write down the exact steps we perform every day when creating the daily sales report, and Copilot converts those steps into VBA code.

I prepared the prompt by starting with the line: ‘I want a Microsoft Excel VBA macro script that performs the following steps.’ Then I listed each step clearly. First, I mentioned the folder path where the downloaded file is stored. Next, I specified the exact file name and added the instruction to identify the latest downloaded file, because the same file name appears every day and we need the most recent one. After that, I asked the script to copy the file and paste it into another folder path, and if the file already exists, it should overwrite it.

Then I added the instruction to open the pasted file. After that, I listed all the steps I normally perform inside my daily sales report. My report is simple: once I paste the data, everything updates automatically because the formulas and dashboard are already built. If your report requires additional steps, you can add them to the prompt as well. After the report is updated, I asked the script to save it as a PDF, copy the main dashboard area, open Outlook, write the email address, subject, and body, paste the dashboard image, attach the PDF file, and prepare the email.

Once the prompt is ready, I press the send button and Copilot begins processing. Within a minute, it generates the complete VBA code. I copy the script, open my daily sales report, click the Developer tab, and open Visual Basic. A new window appears. I click Insert, choose Module, and paste the entire VBA code into the blank screen. Then I close the window.

Next, I insert a new sheet because we need a button that will run the entire VBA script. I go back to the Developer tab and click Insert. Under Form Controls, I select the button option. I draw the button on the sheet, and a pop‑up appears asking me to assign a macro. I select the macro name, which shows as ‘Daily Sales Automation,’ and click OK. I then rename the button from ‘Button 1’ to ‘Click,’ or any name you prefer.

Now the procedure is ready. I click the button to test it. Everything works perfectly. At the end, Outlook opens automatically and the email is prepared exactly as expected. It’s impressive how powerful VBA becomes when combined with Copilot. If you get any errors, you can take a screenshot and ask Copilot to correct the script. It will fix the issue and send the updated code again.

Now the automation is almost complete, but we want everything to run with a single click. So we return to Power Automate Desktop and add a few more flows. If you remember, our last flow ended after downloading the dataset. Now we need to open the Excel dashboard report. Under the Excel actions, we select ‘Launch Excel’ and drag it into the flow. A pop‑up appears. The first option shows ‘Launch Excel with a blank document,’ but we change it to ‘Launch Excel and open the following document.’ In the document path field, we enter the exact path where our daily sales report is saved, including the file name. Then we click Save.

Next, we add a Wait action because the report takes a few seconds to open. Five seconds is usually enough. To test this part, we click the three dots and choose ‘Run from here.’ The report opens successfully.

When the report opens, it shows the dashboard sheet by default. But we need to switch to the sheet where the button is located. So we add the action called ‘Set active Excel worksheet.’ In the pop‑up, the Excel instance remains the same. The active worksheet option stays on ‘Name,’ and in the worksheet name field, we type the sheet name, which is ‘Sheet1.’

Now we search for the action called ‘Move mouse to image.’ We drag it into the flow. A pop‑up appears with the option ‘Select Image.’ When we click it, a capture button appears. We click the capture button and select the button inside our daily sales report. Once captured, we can see the preview on the left side. Below that, we enable the option ‘Send a click after moving mouse,’ which means Power Automate will click the button automatically. Then we click Save.

That’s it. Our flow is complete. Now we run the entire automation and watch everything happen with a single click. The whole process finishes within a minute or two, and the final email is ready in Outlook. It’s amazing to see how all these tools work together.

I hope you enjoyed this video, and I will see you in the next one.”

“Hi, and welcome to this tutorial. Today we’re going to learn how to install Python, and the good news is that the entire process is simple, quick, and completely free. Python is one of the most popular programming languages in the world, especially for automation, data analysis, and AI‑related tasks. Installing it correctly is the first step toward building powerful automation workflows.

We’ll begin by opening the Microsoft Store. Once it’s open, type ‘Python’ in the search bar. You’ll notice several free versions available, but we’ll choose Python 3.12, which is the latest stable release. Click the Get button, and the installation will begin immediately. After a few moments, the store will confirm that Python is installed on your computer.

To verify the installation, open the Command Prompt. You can do this by pressing the Windows key and typing CMD. When the Command Prompt window appears, type ‘python --version’ and press Enter. If everything is installed correctly, you’ll see Python 3.12 displayed on the screen. This confirms that Python is ready to use for automation.”

“Now that Python 3.12 is installed, the next step is to prepare it for automation. Python cannot control a browser or Outlook on its own, so we need to install three important packages. These packages allow Python to automate websites, manage browser drivers, and communicate with Outlook just like Power Automate Desktop.

The first package is Selenium. Selenium is the tool that allows Python to open a web browser and control it automatically. With Selenium, Python can click buttons, fill forms, select dates, upload files, and download reports. It acts like a digital robot inside the browser. To install Selenium, open the Command Prompt and type: pip install selenium Press Enter, and Python will download and install Selenium automatically.

The second package is WebDriver‑Manager. Every browser, such as Chrome or Edge, needs a driver file that Selenium uses to communicate with it. Normally, users have to download this driver manually and keep it updated. WebDriver‑Manager removes all of this manual work. It automatically downloads the correct driver, updates it when needed, and configures everything behind the scenes. This makes your automation script cleaner and more reliable. To install WebDriver‑Manager, type: pip install webdriver-manager Press Enter, and the package will be installed.

The third package is pywin32. Selenium can only control web browsers, but Outlook is a desktop application. To automate Outlook, Python needs a different method. Pywin32 gives Python the ability to communicate with Windows applications like Outlook, Excel, and Word. With pywin32, Python can open Outlook, create an email, write the subject and body, paste the dashboard image, attach the PDF report, and prepare the message automatically. To install pywin32, type: pip install pywin32 Press Enter, and Python will install the package.

Once these three packages are installed, Python becomes a complete automation system. Selenium handles the browser. WebDriver‑Manager manages the browser driver. Pywin32 controls Outlook. With all three working together, Python can perform end‑to‑end automation: logging into a website, downloading a report, updating Excel, generating a PDF, and preparing the final email. This setup allows Python to automate tasks that normally take several minutes, all with a single script.”

We’ll explore how Python interacts with the browser, how automation flows are structured, and how a single prompt can generate the entire script for you. It’s a very exciting part of the course, and once you understand it, you’ll be able to automate tasks that normally take several minutes — all with one command.

I’ll see you in the next video.”

Hello and welcome back, in this tutorial will learn how create prompt, and the entire prompt available in this section which you can download and use, so let’s get started.

I am starting with

Act as an expert Python Selenium automation engineer. I need a high-reliability script to automate downloading an Excel report from a MicroStrategy Web portal. The environment is highly dynamic, utilizes multiple hidden nested iframes, and uses hover-activated visualization containers.

Please write a complete Python script using Selenium WebDriver that implements the following technical specifications:

After that I have mentioned below.

The first is Chrome configuration. We maximize the browser so every button is visible, keep Chrome open after the script finishes so students can see what happened, and set the download folder so files save automatically without any popups. If we don’t do this, the automation may stop or wait for manual clicks.

The second is the iframe search system. Many websites hide buttons and fields inside iframes, which are like small pages inside the main page. If Python doesn’t switch into the correct frame, it won’t find the element and the automation will fail. The recursive iframe function searches every frame until it finds the right one, making the automation reliable even on complex websites.

These two steps make the automation stable, predictable, and ready for real‑world use

I have mentioned the entire flows which required step by step.

“These steps are necessary because the website needs the correct data, the correct date range, and the correct user login before it can generate the report. And once the report is downloaded, Outlook needs the right email details so the file reaches the correct people. Every action in this sequence is part of the daily workflow, and Python simply performs all of them automatically.

The automation opens the website, logs in, enters the dashboard, uploads the Excel file, selects the date range, refreshes the page, and downloads the report. Then it switches to Outlook, creates a new email, adds the To and CC addresses, writes the subject and message, attaches the downloaded file, and prepares everything automatically. Together, these steps complete the full daily routine from downloading the report to sending it by email.”

And this the command for creating batch file

“This small batch file is used to run your Python automation with just one click. Instead of opening Command Prompt, typing the folder path, and typing the script name every time, the batch file does all of that automatically.

The first line, ‘@echo off’, simply hides extra command‑line text so the window looks clean. The title line sets a name for the window so students know the automation is running. The echo line shows a friendly message before the script starts.

The most important part is the Python command. Here you place your folder path and the Python file name. When the batch file is double‑clicked, it immediately runs your automation script from that location. The last line, ‘pause’, keeps the window open so students can see the final message instead of the window closing instantly.

In simple words, this batch file turns your entire automation into a one‑click shortcut. It saves time, avoids typing errors, and makes the automation easy for anyone to run.”

Hello, and welcome back.

In this tutorial, we'll learn how to convert a numeric value into words using Python directly inside Excel.

This is a very common requirement in business documents. For example, when creating an invoice, purchase order, quotation, or payment voucher, you often need to display the total amount in words below the numeric value.

Unfortunately, Microsoft Excel doesn't have a built-in formula to convert numbers into words. However, with Python, we can accomplish this in just a few lines of code.

Let's see how easy it is.

Before we begin, we need to install a small Python library called num2words.

To install it, open the Command Prompt and type the following command:

Pee I pee install num2words

Then press Enter.

Python will automatically download and install the required package on your computer. This is a one-time installation, so you won't need to install it again unless you set up Python on another computer.

Once the installation is complete, open Microsoft Copilot and enter the prompt provided in this lesson. You can also download the prompt from the course resources and use it directly.

After you click Send, Copilot will generate the complete Python script for us within a few seconds.

Now simply copy the generated script.

Next, open your Excel workbook.

In the cell where you want the result, type =PY and press the Tab key.

Now paste the Python code into the Python editor.

To execute the code, press and hold the Ctrl key, then press Enter.

Remember this shortcut because the Python formula will not execute unless you use Ctrl + Enter.

As you can see, Excel immediately converts the numeric value into words.

The result matches the amount shown in the adjacent cell.

You may also notice a small PY indicator beside the cell. This simply shows that the result was generated using Python.

If you'd like to hide this indicator, press Ctrl + Shift, + Alt + M, and the indicator will disappear.

Now let's test our solution.

I'll enter a few different numbers below and copy the same Python formula into the remaining cells.

As you can see, every number is converted into words accurately and instantly.

This is a simple but extremely useful automation for finance teams, accountants, invoice preparation, purchase orders, quotations, banking documents, and many other business reports.

Instead of manually typing the amount in words or searching for an online converter, Python performs the task automatically inside Excel, saving time and reducing the chance of errors.

I hope you found this tutorial helpful.

Thank you for watching, and I'll see you in the next lesson.

Hello and welcome back. In today’s video, we’re going to learn how to clean data using a Python script generated through Gemini. It’s very simple, very easy, and requires only one prompt — so let’s get started.

This is my dataset that needs cleaning. As you can see, there are missing amounts in the order value, column and the cost column. The date column also contains incorrect formats. I’ve already mentioned the corrections I want: proper day‑month‑year formatting, missing value handling, and basic data cleanup.

Here is the prompt I will copy and paste into Gemini. After clicking Send, Gemini immediately starts generating the Python script for us.

Below the script, Gemini also mentions that we need to install a Python package called pandas open pyxl. I’ll copy this installation command, press the Windows key, type CMD, and open the Command Prompt. Here, I’ll paste the command and press Enter. Python will download and install the package automatically.

Next, I’ll go to the folder where I want to save my script. I’ll copy the folder path, return to Command Prompt, type F colon and press Enter. Then I’ll type CD, paste the folder path, and press Enter again.

Now I’ll download the script from Gemini and move it into the same folder so I can run it easily from Command Prompt.

I’ll copy the script name, type it in Command Prompt, and add dot py, which is the Python extension. After pressing Enter, the script begins running.

You’ll notice a black status screen showing what’s happening behind the scenes. Python starts processing the data in the background without opening Excel. Once it finishes, it returns us to the Command Prompt.

Now I’ll open the folder where the cleaned Excel file is saved. Everything looks correct — the cost values are comma‑separated, the dates are in the correct format, and the customer name column no longer contains commas.

However, the script removed all values from the order value column. No problem — I’ll simply ask Gemini to revise the script. I’ll paste my correction prompt, click Send, and Gemini generates a new updated version.

I’ll download the revised script into the same folder, go back to Command Prompt, type the new file name with dot py, and press Enter.

Now I’ll open the Excel file again — and yes, this time everything is correct. That is amazing.

I hope you enjoyed this tutorial, and I’ll see you in the next lesson.

Hello and welcome back. In this tutorial, we’re going to learn how to use Google NotebookLM, one of the best free AI tools for research, summarization, and automation support.

First, open your browser and search for Google NotebookLM. Click on the first link. This will take you to the main landing page. Here, you’ll see a button that says “Try Gemini Notebook.” Click on it. Make sure you’re signed in with your Google account. I’m already signed in, so I’ll continue.

Now click “Create new notebook.” A window will pop up showing different options for adding sources. NotebookLM allows you to upload files, paste website links, import Google Drive documents, add YouTube videos, or simply paste text. I’ll close this window for now.

At the top, you can give your notebook a name. I’ll type “Automation” because our topic is related to automation. You can also expand the left panel using the small icon if you want more space.

Next, I’ll click the Sources button. The same window appears again. This time, I’ll choose Upload source and drag‑and‑drop my PDF file that contains an automation article. Once uploaded, you’ll see the file appear in the Sources panel.

Now I’ll click Add sources again. This time, I’ll select the YouTube option and paste a YouTube link related to automation. After clicking Next, NotebookLM adds it to the notebook.

I’ll repeat the process one more time and paste a web article link about automation. Finally, I’ll add a direct text search by typing: “AI automation full detail articles” and click Add. NotebookLM processes everything and shows all sources neatly in the Sources area.

If I click View, NotebookLM shows more details about each source. There’s also a small expand arrow — clicking it opens the webpage in a new browser tab.

In the center area, NotebookLM displays a short preview of the content from all sources. Below that, we can type our prompt — this is where we tell NotebookLM exactly what we want.

For example, I’ll type: “Summarize the main strategies about AI Automation 2026.” After clicking Send, NotebookLM analyzes all sources and generates a complete summary. You’ll notice small numbers like 1 and 2 beside the text. When you hover over them, NotebookLM shows a small preview window. Clicking on them takes you directly to the exact part of the source where the information came from. This is extremely impressive for research and verification.

You can also save any response by clicking Save to notes, and it will appear in the Notes section.

Now let’s explore one of the advanced features. I’ll select one of my sources and click Mind Map. A window pops up with an option to enter a prompt. I’ll leave it blank and click Generate. NotebookLM starts processing and creates a complete mind map. You can expand each branch to see more details. This is one of the best tools for creating presentation ideas, planning workflows, or understanding complex topics visually.

Next, I’ll select my PDF file again and click Audio Overview. This feature allows NotebookLM to generate an audio summary of your document. You can choose what type of audio you want — for example, Beginner Road Map. I’ll leave the prompt blank and click Generate. NotebookLM takes a couple of minutes to process, and then your audio podcast is ready. You can click Play to listen to it.

Finally, NotebookLM also has an Explainer Video option. Just like the audio feature, it can generate a complete explainer video based on your source. This is an amazing free tool for content creators, students, and automation learners.

NotebookLM is powerful, simple, and completely free — and it can save you hours of manual research.

I hope you enjoyed this tutorial, and I’ll see you in the next lesson.

Hello and welcome back. In this short video, we’re going to understand one simple question: What is NotebookLM?

NotebookLM is Google’s free AI‑powered research and learning assistant. Think of it as a smart notebook that doesn’t just store information — it actually understands your content, analyzes it, and helps you learn from it. Instead of searching through multiple documents, articles, or videos, NotebookLM brings everything together in one place and gives you clear, structured insights.

At its core, NotebookLM is designed to help you work faster with information. You can upload PDFs, paste website links, add YouTube videos, import Google Drive files, or even paste plain text. Once your sources are added, NotebookLM reads all of them and builds a personalized AI model based entirely on your content. This means every answer you receive is grounded in your own sources, not random internet data.

So what makes NotebookLM special? First, it can summarize large documents in seconds. Whether you have a long article, a research paper, or a technical guide, NotebookLM extracts the key points and presents them in a clean, easy‑to‑understand format.

Second, it can explain complex topics. If something feels confusing, you can simply ask NotebookLM to break it down, simplify it, or rewrite it in a beginner‑friendly way.

Third, NotebookLM helps you explore ideas visually. With one click, it can generate a complete mind map based on your sources. This is extremely useful for planning projects, understanding workflows, or preparing presentations.

Fourth, NotebookLM can create audio overviews and explainer videos. These features allow you to turn your documents into podcasts or short videos automatically — perfect for learning on the go or preparing content for your own students.

But the most powerful part of NotebookLM is its ability to cite its answers. Whenever NotebookLM gives you information, you’ll see small numbers beside the text. Clicking them shows exactly which source the information came from. This makes NotebookLM reliable, transparent, and ideal for research, automation learning, and professional work.

In simple words, NotebookLM is your personal AI research assistant. It helps you understand information faster, organize your ideas, and generate summaries, mind maps, audio content, and explainer videos — all from the sources you provide. And the best part is that NotebookLM is completely free.

Throughout this course, you’ll see how NotebookLM can support your automation learning, help you analyze documents, and make your workflow smarter and more efficient.

Thank you for watching, and I’ll see you in the next tutorial.

“As we wrap up this course, let’s take a moment to reflect on everything you’ve learned. You started with the introduction, where we set the foundation for your automation journey. Then, you explored what AI automation truly means and why it matters so much in 2026 — a year where automation is no longer optional, but essential for productivity and career growth.

You learned how to create effective prompts for HTML, giving you the ability to communicate clearly with AI tools. You installed Power Automate Desktop and built your first automated workflow. You created Excel dashboards, learned how PAD interacts with Excel, and saw how VBA scripts can refresh reports, update formulas, export PDFs, and even prepare emails automatically.

You installed Python from the Microsoft Store and learned how to generate Python scripts using AI prompts. You saw how Python can automate tasks silently in the background without touching the screen, making it perfect for fast, reliable, end‑to‑end automation.

You also built a complete automation workflow — from downloading files, cleaning data, refreshing dashboards, exporting reports, and sending emails — all without manual effort. Along the way, you picked up useful Excel tips, like converting numeric values into words and cleaning messy data with precision.

Then, you explored NotebookLM, one of the most powerful free AI tools available today. You learned what NotebookLM is, how it works, and how it can summarize documents, generate mind maps, create explainer videos, and help you understand complex topics instantly.

Across all these lessons, you used only free tools: Power Automate Desktop, Excel VBA, Python, Copilot, Gemini, Claude, and NotebookLM. Together, these tools give you everything you need to automate your daily workflow from start to finish — without subscriptions, without expensive software, and without advanced programming experience.

You now have the skills to build your own end‑to‑end automation system, just like the ones used in real corporate environments. And once you experience how much time automation saves, you will never want to go back to doing repetitive tasks manually again.

Thank you for completing this course. I hope you enjoyed the journey, and I’m excited to see how you apply these skills in your daily work. Best of luck, and I’ll see you in the next tutorial.”