Data science is a demanding field, requiring powerful laptops that can handle large datasets, complex algorithms, and intensive processing.
Choosing the right laptop can make all the difference in your productivity and overall success in the field.
In this article, we will take a look at the 7 best laptops for data science, each with their own unique features and specifications.
What are the Best Laptops for Data Science Right Now?
I updated this post in April 2023 so everything is current and relevant for you!
Apple M1 MacBook Pro (16-inch, 2021)
The Apple M1 MacBook Pro is a powerful and reliable laptop, making it an excellent choice for data scientists. Its M1 processor ensures blazing fast performance, while its 32GB RAM (provides ample memory for processing large datasets. With a long-lasting battery life of up to 21 hours and a storage capacity of 512MB SSD, this laptop is perfect for data science professionals who value speed and reliability.
Although I like all the laptops in this list, this MacBook Pro is the best laptop for data science if your partial to the Mac OS.
ASUS ROG Strix G17
The ASUS ROG Strix G17 is a high-performance gaming laptop that is also well-suited for data science tasks. Featuring an AMD Ryzen 9 7945HX processor, this laptop provides exceptional processing speeds. The 16GB RAM, upgradable to 64GB, and a 1TB PCIe SSD offer plenty of memory and storage for handling complex data science projects. However, its gaming pedigree makes it a more expensive option.
Right up there with the best laptops for data science, the G17 is a solid pick to handle your data science needs.
Legion 5 (15″ AMD) Gaming Laptop
The Legion 5 is a hidden gem for data scientists on a budget, and that a big reasion why it’s made it onto my list of best laptops for data science.
Equipped with an AMD Ryzen 7 5800H processor, this laptop provides excellent processing power at an affordable price. Its 16GB DDR4 RAM, high resolution, and a 512GB PCIe SSD offer sufficient memory and storage for most data science tasks. With a battery life of up to 8 hours, this laptop is perfect for students and professionals alike.
Alienware x14 Gaming Laptop
The Alienware x14 is a great option for those seeking a balance between gaming and data science capabilities. Its 12th Gen Intel® Core™ i7-12700Hprocessor and NVIDIA GeForce RTX 3060 graphics card make it perfect for both gaming and data analysis tasks. With highly customizable RAM and storage options, the Alienware x14 can be tailored to suit your specific data science needs. However, its price tag may be a deterrent for some.
M2 MacBook Air (2022)
The M2 MacBook Air is another excellent option for data scientists, offering a powerful M2 chip with 8-core CPU and 10-core GPU for fast processing. Its 8GB RAM and 512GB SSD provide ample storage for most data science tasks. With a sleek design and lightweight build, the M2 MacBook Air is perfect for those who value portability and performance.
Dell XPS 15
The Dell XPS 15 is a popular choice for data scientists, thanks to its powerful 11th Gen Intel Core i7 processor, 32GB RAM, and 1TB SSD. The NVIDIA GeForce RTX 3050 Ti graphics card ensures smooth performance for data visualization tasks. Its 15.6-inch 4K UHD+ display offers excellent color accuracy and clarity, making it perfect for data analysis and presentation.
Laptop Requirements for Data Science
When searching for the perfect laptop for data science, it’s essential to understand the minimum requirements for effectively running data analysis and machine learning algorithms. Here are the key factors to consider when choosing a laptop for data science:
Processor: A powerful processor is crucial for handling large datasets and running complex algorithms. Aim for a laptop with a minimum Intel Core i5 or AMD Ryzen 5, but for optimal performance, opt for an Intel Core i7 or AMD Ryzen 7.
RAM: At least 8GB of RAM is necessary for basic data science tasks, but for more demanding projects, 16GB or more is recommended.
Storage: A solid-state drive (SSD) is preferred over a hard disk drive (HDD) for faster data access and better performance. Aim for at least 256GB of storage, but 512GB or more is ideal for handling large datasets.
GPU: A dedicated graphics card can significantly speed up tasks such as deep learning and data visualization. Look for laptops with NVIDIA GeForce or AMD Radeon graphics cards.
Laptop vs. Desktop
Laptops offer portability, allowing you to work on your data science projects from anywhere. However, desktop computers typically provide more processing power and customization options, which can be beneficial for advanced data science tasks.
Consider your specific needs and work habits when choosing between a laptop and desktop. If you require flexibility and the ability to work on the go, a laptop may be a better choice. On the other hand, if you’re dealing with large datasets and need more computing power, a desktop computer might be more suitable.
Mac vs. Windows
The debate between Mac and Windows for data science can be a matter of personal preference. Both operating systems have their own advantages and disadvantages:
Mac:
macOS is known for its stability and reliability.
Mac laptops generally have a longer battery life.
Macs have a more consistent user experience, making it easier to find and use data science tools.
Windows:
Windows laptops offer a wider range of hardware options and configurations.
Windows has a larger user base, which can translate to better support and a larger community for troubleshooting issues.
Many data science tools and libraries are natively supported on Windows.
Ultimately, the choice between Mac and Windows comes down to your individual preferences and the specific tools you’ll be using for data science. Both platforms are capable of handling data science tasks, so choose the one that best aligns with your workflow and personal preferences.
Other Considerations: Cloud Computing and External GPUs
As data science tasks become increasingly resource-intensive, it’s worth considering alternative solutions such as cloud computing and external GPUs.
Cloud computing services like Google Colab and Amazon Web Services allow you to run complex data science tasks on powerful remote servers, which can save you from having to invest in a high-end laptop or desktop. This approach can be particularly helpful for those on a budget or those who only occasionally need access to powerful computing resources.
An external GPU is another option that can boost your laptop’s performance for data science tasks. By connecting an external GPU to your laptop, you can significantly enhance its graphics and processing capabilities. This can be a cost-effective solution if you already own a laptop with a decent processor and RAM but lack a dedicated graphics card.
Final Thoughts
Choosing the best laptop for data science can be a daunting task, considering the wide array of options available. However, the six laptops listed above cater to a variety of needs and budgets, ensuring that you can find the perfect match for your data science projects.
We also often use Hobby Scoop to research the latest trends.
We also recommend checking out our post on the best data science bootcamps.
Whether you value processing power, portability, or versatility, there’s a laptop on this list that will suit your requirements and help you excel in the world of data science.
Ben is a full-time data leadership professional and a part-time blogger.
When he’s not writing articles for Data Driven Daily, Ben is a Head of Data Strategy at a large financial institution.
He has over 12 years’ experience in Banking and Financial Services, during which he has led large data engineering and business intelligence teams, managed cloud migration programs, and spearheaded regulatory change initiatives.