7 Tools I Cannot Live Without as a Data Scientist

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It's been almost three years since ChatGPT launched, and AI tools are slowly becoming an integral part of our workspaces. We use them as coding assistants, for improving grammar and writing style, conducting research, and so much more. I never thought in my life that I would become so dependent on these tools—and now, as a data scientist, it feels almost impossible for me to work efficiently without them.

In this blog, I will share seven tools I can't live without and would happily pay a premium to keep using. Most of them are AI-enabled, but not all. These tools help me with everything from experimenting with models and interacting with communities to writing, coding, organizing, and improving my overall workflow.

1. Google Workspace

Google Workspace is my go-to tool for everything—from storing documents to creating drafts for my projects, tutorials, and guides. I also use it for managing my to-do list, organizing tasks with the calendar, and holding meetings with clients using Google Meet. It serves as my email platform, a writing assistant, an invoicing tool, a project management system, and much more.  

While Microsoft provides similar services, I find that the process isn't as smooth as Google Workspace. I can add notes on my phone or iPad, and they automatically sync to my Workspace. I can view and comment on my documents from anywhere, meaning I can work on any device and from any location.

2. You.com

A friend introduced me to You.com, and I use it every day for researching my projects and learning about new technology. It's great for writing blogs, brainstorming project ideas, debugging code, and learning about cloud deployments. It truly feels like my sidekick.  

The best part of You.com is that they constantly update their models, giving you access to the latest from OpenAI, Anthropic, DeepSeek, Qwen, and other open-source models at your fingertips. It features agents, custom instructions, image generation, multi-document support, web access, and more.

3. Cursor

Cursor has completely replaced my need for VSCode and any other IDE. It's perfect for code editing, code generation, debugging, discussing ideas, and has an agentic approach that allows you to make edits to multiple files and folders. It can even execute commands in the terminal and build you a proper application if you provide a clear description.  

I use Cursor daily for working on my portfolio websites, business websites, machine learning and data science projects, cloud deployments, and testing code.

4. Grammarly

As someone with dyslexia, I struggle with reading and writing. I need assistance to improve my writing and understanding of text. For this reason, I use Grammarly for everything—from code documentation to blog writing, emails, and all professional writing tasks.  

Grammarly incorporates AI that helps with tone, style, and provides edits you might have missed. It is a lifesaver for someone with a disability, as it understands what you're trying to say and makes edits on the go without asking too many questions.

5. ChatGPT

You.com and ChatGPT are quite similar in terms of their functionality, so why should I pay for a ChatGPT Pro subscription? ChatGPT offers a superior experience for code editing, document revisions, and generating high-quality images, all while providing an excellent user interface.  

I use ChatGPT for generating blog ideas, editing legal documents, debugging code, brainstorming, data analysis, and improving the structure of my blogs. The team behind ChatGPT is tirelessly working to enhance the user experience, and I genuinely appreciate their efforts.

6. Kaggle

I love Kaggle! I primarily use it to access free GPUs, which are often better than those offered by Colab with fewer limitations. Beyond its Cloud IDE, I also use it to access various models and datasets. Additionally, I enjoy participating in machine learning competitions that challenge me and help me learn new techniques to improve my models.  

Kaggle is a community, a code editor, a repository for both data and models, a competition platform, and a place to showcase my portfolio to hiring managers.

7. Hugging Face

Hugging Face is also an open-source AI community, but it offers so much more. I use it to upload my datasets and models, as well as to deploy models for free using the UI or API endpoints through Docker. I can access model inference for free and integrate various models into my applications. I can also comment, fork, and contribute to open-source projects, similar to GitHub.  

I use this platform four times a week for various reasons: its ecosystem, model fine-tuning, accessing high-quality datasets, and showcasing my portfolio. People respect those who are actively contributing to open-source projects.

Conclusion

I know that in the future, more AI tools will become part of my workflow, and I will be using them daily to improve my efficiency and effectiveness. I am also producing original and high-quality work with the help of these tools. It's not that I am blindly copy-pasting responses generated by language models; I am making sure to learn from them and use their insights to enhance my work rather than simply copying and pasting.

I would love to know what kinds of tools you use daily and why you can’t live without them. Please mention them in the comment section.
 
 

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in technology management and a bachelor's degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.