Welcome to this third of four short courses on Python. You just pass a halfway mark to the finish line. In this course, you'll see how to work with your own files, including both text files as well as data stored in a spreadsheet that is data stored in a table. In the first two courses, you learned some of the basic features of Python, including the types of data like integers and strings you can work with, and how to use functions to interact with AI. You then learned on how to use Python to automate tasks and make decisions using special code patterns like for loops, which let you repeatedly take the same action over and over. And if statements that help a program make a decision about what to do next. In the examples so far, the data you worked on was created or coded right inside the jupyter notebook. For example, we typed the list of friends names or the food ingredients or the to-do lists right there into the Jupyter notebook. It turns out Python can also work with data stored in the files on your computer, and just let you work with your own data. It turns out you probably have a lot of data whether you realize or not. Your to do lists your emails. Even family recipes or spreadsheets with your personal budgets. Pretty much all the files you generate on your computer or stored in the cloud. Are data. In this course, we'll use an example of finding a dream vacation. I know I'm not great at taking vacations myself, but people that plan vacations and I should get better at this would sometimes keep spreadsheets of places they want to visit. Or see articles and blog posts about things you want to do or places you'd like to eat. In this short course, we'll go through an example of how to take all this raw data of ideas a great vacation, and use AI to help plan out the actual vacation. You'll see that AI large language models can help you do things like look at all this data and summarize it to extract key information about what would be fun to do. And then writing Python code around that can help you manage a lot of data at once. For example, if a coworker sends you ten transcripts of user interviews and you want to quickly read or have AI read each of these interviews to inform a marketing plan or product design. Well, you could use AI to read all ten transcripts, but maybe you end up copy/pasting ten times into some sort of AI chatbot. Python lets you automate the process of reading and analyzing all of these ten transcripts, one at a time, for example, using a for loop. In this course, you see, how to work with your own files, including both text files and data stored in a spreadsheet that isn't a table of numbers. And you see how to process that data using Python and AI to perform tasks quickly and repeatedly. So for example, you see how to use Python in AI to look at a piece of text and decide if it talks about a particular topic, or you see how to use it to highlight key information within a file. A fun example we'll use as a running example throughout the short course is: Let's say you plan a trip or you're thinking of a dream vacation with seven destinations, you know, New York, Sydney, Tokyo, and many other fun cities. And maybe you've saved a bunch of documents about this, like food critics journals and lots of other documents about will be fun to do. Then you can write a reusable piece of code to create a detailed itinerary for each of those cities you want to visit. Using all of this information you might have gathered. And while planning a fun vacation is just one example. You see that the patterns we go through will be useful for processing many other sorts of data you may have in your personal life or at work. Let's go on to the next video to dive more into data and how you may have data that you can get AI to help you process.
AI Python for Beginners: Working with Your Own Data and Documents in Python