How ChatGPT is Revolutionizing Data Science and AI: A Guide for Data Scientists and AI Enthusiasts
“Change is the end result of all true learning.” – Leo Buscaglia. You might wonder, what could possibly change in the established field of Data Science? Well, “here” is where ChatGPT comes into play, offering a paradigm shift you won’t want to miss.
In this digital age, staying updated on Artificial Intelligence (AI) and Data Science tools is not just optional—it’s essential, because of its power to automate mundane tasks, refine data analysis, or even aid in machine learning projects.
I’ll walk you through how ChatGPT is making significant contributions to Data Science and AI. We’ll look through specific plug-ins, ChatGPT Advanced Data Analysis, or prompts that can elevate your work to new heights. Curious about whether ChatGPT might ultimately replace traditional Data Science methods? I’ll touch on that too. Buckle up and let’s get started!
What is Data Science?
In today’s digital age, we generate an enormous amount of data every minute. Data Science is the discipline that makes sense of this vast amount of data. For instance, through analyzing various data points, a retailer can predict which products will sell well in the coming season.
Now, let’s ease into a more casual chat about this intriguing field. Data Science is like a big playground where different skills come together to find answers hidden in data. It’s a bit like being a detective but for numbers and trends.
To do that, You’ve got a mix of methods used here like web scraping, which is about collecting data from websites, and data exploration, where you dig into this collected data to find useful insights. Then there’s machine learning, a way to teach computers to learn from the data to make predictions or decisions.
Whether it’s predicting the next big movie hit, or helping cities manage traffic better, Data Science is in the mix, making our lives smoother. It’s a realm where curiosity meets technology, leading to discoveries that can truly change the way we see and interact with the world. In the next sections, we will see how ChatGPT affects these subsections.
How to Benefit from ChatGPT in Data Science?
Did you know that the volume of data created worldwide is expected to rocket to a whopping 175 zettabytes by 2025? In such a data-driven era, accuracy and efficiency are really important.
ChatGPT here will be one of your servants, that can significantly help you. For instance, by using ChatGPT Advanced Data Analysis you can swiftly analyze a dataset to predict customer behavior, aiding a business in tailoring its strategies.
Moreover, ChatGPT comes with cool plug-ins, which makes ChatGPT 10x powered, like notable, scraper, access links, and more.
If you don’t have ChatGPT Plus, you can simply use prompts wisely, which can guide you through complex data problems. In the upcoming sections, we will uncover the specifics of ChatGPT Plug-ins, ChatGPT Advanced Data Analysis(Code Interpreter), and ChatGPT Prompt.
These segments will provide a closer look into how each feature can be a game changer in handling data exploration, web scraping testing different machine learning models, making the data scientist’s life a tad easier and the data analysis process a lot more engaging.
ChatGPT Plug-ins
Did you know you can easily collect data with ChatGPT plug-ins? Yep, it’s not just about asking questions and getting text replies anymore.
Let’s talk web scraping. The browser plug-ins like WebPilot, Scraper, AccessLink, and BrowserOp can make your life so much easier. With a simple prompt like below, you can gather web information right into a neat table.
Collect data from this website:
<Link to the Website>
After that, it’s your choice. You can send the table to ChatGPT Advanced Data Analysis to get it back as a CSV file. Or save it to an Excel file through Google Docs or on your local computer. Even a basic notebook can do the job.
Moving on to Machine Learning. There might not be a ton of plug-ins here, but you can use the above one to read ML papers. The code interpreter already does a great job on Machine Learning, but if you want to do a bit of research, see the example prompt below.
Find the latest machine learning papers about Gradient Boosting.
And let’s not forget Data Visualization. Ever want to see your data in a graphic form? You can use the Visualize Your Data Plug-in below and provide a Google Sheet link. Easy as pie, here is the prompt:
Visualize this data:
<Google sheet link here>
Next one is the most important one can do all of them at once, Notable. If you are curious about Data Science applications with ChatGPT and don’t know of Noteable, I highly recommend you research it. It is like a ChatGPT Advanced Data Analysis but at higher levels.
After loading notable, and opening an account through, their website, which is for free, you can use the following prompt:
Load this dataset:
Use this as my default project: "Link from their website"
Act as a data scientist and analyze this dataset
After this prompt, it will start analyzing your dataset, continue running code, and sometimes ask you questions about it. Then it will create a jupyter notebook containing these codes, which is pretty amazing.
So, the next time you’re diving into Data Science, remember these ChatGPT plug-ins. They can save you time, help you collect data, and even visualize it for you. Why not give them a spin?
ChatGPT Prompts
So, what if you don’t have access to all the fancy plug-ins or advanced features? Can you still use ChatGPT for Data Science? Absolutely! ChatGPT prompts have been around since the beginning, and they’re still a solid tool for data tasks.
In the early days, all we had were these prompts. And guess what? They still do the job. For example, are you trying to learn web scraping using Python? Just use the prompt below, and you’ll get the code you need, and then you can move on to gathering your data.
How do you install BeautifulSoup and its dependencies in a Python environment?
And what about data analysis? Imagine you need to explore and analyze a dataset. A simple prompt like will do the trick. You’ll get code that’s ready to run.
Act like a Data Analyst and send me Python codes for Data Exploration first, and data analysis afterward.
Now, let’s talk about Machine Learning. Working on a project and hit a snag with an imbalanced dataset? No worries. Use the following prompt, and just like that, you have your solution.
How do you handle imbalanced datasets in a classification problem using scikit-learn?
See, ChatGPT prompts can handle a lot. They might not have the bells and whistles of plug-ins, but they get you where you need to go. So, why not give it a try?
ChatGPT Advanced Data Analysis
Ever wonder how you could streamline the process of data analysis, making it less daunting and more straightforward? Well, ChatGPT’s Advanced Data Analysis might just be the tool you need. It simplifies tasks right from the initial stage of data scraping to the advanced stage of applying machine learning for predictions.
For instance, imagine being able to predict a movie’s success based on various factors like the genre, the director, and the cast, just by feeding the related data into ChatGPT. Sounds exciting, doesn’t it?
Web Scraping With ChatGPT Advanced Data Analysis
Now, let’s break down how this works. Initially, you would need to scrape data.
With ChatGPT Advanced Data Analysis, you can download the HTML file of the webpage you want to scrape data from, and use a simple prompt to extract the information you need, saving it into a CSV file.
Let’s say you want to create a dataframe containing IMDB Movie Name, Rating, and Year. Download the HTML file from there. But don’t forget to download two of them because the first HTML file contains 50 rows. Here is an example prompt:
Scrape IMDb top 100 list from the HTML files I uploaded. The final dataset should include Movie Name, Year, and Rating. And save it as "imdb_rating.csv". Send me the final CSV file, but first show me the content for approval.
Here is the output.
Actually, before saving the end file, it will always be good to double-check, and as you can see we can scrape the data, after my approval, here it sends me the final CSV file with the link that I can download, pretty amazing isn’t it?
Data Analysis with ChatGPT Advanced Data Analysis
Next up is diving into the data to find some hidden treasures. With another prompt, now you are going to hire a data analyst, for just $20 per month! Here use this prompt, with your data and observe the result.
To test the abilities of ChatGPT Advanced Data Analysis, I am going to use data from Kaggle, here.
Act like a Data Analyst, explore & analyze the data that I uploaded.
After loading the data, and using the prompt above, let’s see some of the results.
Machine Learning with ChatGPT Advanced Data Analysis
And then comes the thrilling part – machine learning. Predicting unknown values based on the known ones is a pivotal aspect of data science. With ChatGPT, you simply need to specify the column you want to predict and ask it.
Now, let’s test it by using our movie dataset.
Act like a Data Scientist and build 3 different regression models by using sci-kit learn to predict movie ratings.
Evaluate the model by using Root Mean Squared Error.
Assign the results to the result_df, and visualize the results by using a bar plot afterward.
First, it asks me to select just relevant fields due to memory issues.
After my approval, here is the end result, which is really perfect.
Through this simplified, conversational interaction with data analysis tasks, ChatGPT not only makes the process less intimidating but also more engaging. Whether you are predicting movie success or anything, ChatGPT’s Advanced Data Analysis is here to make your data science journey a lot more manageable and fun.
If you want to know more about the Data Science path, here is a complete guide to data scientist career path.
Do these tools finish Data Science?
Did you know that there’s a buzzing debate about whether AI and Data Science tools like ChatGPT could one day replace human data scientists? Yeah, it’s a hot topic. But let’s get real. If you’ve ever worked on a data project from start to finish, you know the deal.
Sure, ChatGPT and similar tools are incredibly helpful. They can catch a syntax error in a 150-line code faster than you can say “debug.” But these tools are not flawless. They need a human to spot the kinds of errors they can’t see. And we humans can learn a lot from the mistakes these tools point out.
So, where does that leave us? In a pretty good place, actually. The way I see it, these tools won’t take over Data Science. They’ll make it better. It’s like a buddy movie where each character has their own skills, and together they solve the case. Neither is going anywhere, and they’re better together than apart.
If you need more information about how you can take advantage of ChatGPT, here is How ChatGPT Will Help You Be a Better Data Scientist.
Final Thoughts
So, what have we learned? ChatGPT isn’t just a chatbot; it’s a flexible tool that can elevate your data science game. From plug-ins that assist in web scraping to prompts that help with machine learning, ChatGPT offers a range of solutions that can make a data scientist’s life easier.
Now, here’s the kicker: knowing all this isn’t enough. Data science is a field where practice makes perfect. Want to master it? Then go on. Use ChatGPT and its features to work on real projects. You learn the most when you’re hands-on, working with data and writing code.
Ready to get started? Head over to StrataScratch platform where you can engage in hands-on data projects and interview questions. It’s the perfect practice ground to prepare for a career in data science. Don’t just stand on the sidelines, jump in and start practicing today!
