Anyone who works on data science projects needs a powerful laptop to gather, prepare, and process large data sets for advanced implementation. With so many options available, it can be difficult to know where to start looking for one. In this article, we’ve curated a list of the best laptops for data science available on the market right now.
Many of these laptops are expensive, but you can find cheap laptops for data science with advanced computing capabilities for optimizing complex algorithms. We’ve included the best laptops for data science under $1,000 to help with your data science and deep learning tasks. We also cover the features of a perfect laptop such as battery life, display resolution, storage capacity, CPU cores, graphics processor memory, and screen size.
How to Choose the Best Data Science Laptop
The key to choosing the right data science laptop is first defining your workflow and your budget. This will help you properly define the essential components your data science and analysis laptop needs. Below is a list of the ideal features a decent laptop for data science should possess.
The best CPUs for data science are AMD and Intel core processors. A data science laptop should not be less than an Intel Core i5 7th generation. You’re going to be running lots of applications simultaneously so you need a laptop with excellent performance.
If you can afford it, go for a 9th generation Intel Core i9, Intel Core i7, or an AMD Ryzen specially built for multitasking and computing speed. A powerful processor will make all the difference if you are aiming for faster performance.
You want at least 16GB of RAM or 32GB of RAM for data science laptops. With a lot of memory space, you can easily access thousands of files without experiencing delays, system glitches, or shutdowns.
If you’re a student, you can start with 8GB RAM, but you’ll most likely want to upgrade eventually. This memory size is also suitable for running multiple applications at the same time, including a deep learning library.
Although the operating system (OS) for data science is subject to the user’s preference, Windows, macOS, and Ubuntu are the most popular amongst data science professionals and students.
A macOS was designed with a simplified user interface and multitasking capabilities. It is secure and can be integrated with many data science tools. Ubuntu is also user-friendly and can be customized to suit your needs. Windows is the most popular OS overall.
Graphics Processor Core and Speed
The graphics processor’s speed and performance in data science laptops are very important. GPUs were built to offer better quality data computations and optimization, making them ideal for data science. Although the best graphics cards are found in gaming laptops, you can also find them in mobile workstations. Generally, NVIDIA Geforce GTX and RTX cards are the best.
Aside from the display advantages that larger screen laptops provide, they are generally accompanied by better hardware features, storage, and computing performance. However, even one with a slim design won’t be easy to move around if it has a large screen.
If you need a laptop for data science, go for larger screen laptops so you can optimize your laptop’s display features. You will definitely need a laptop that offers a decent display. What you lose in portability will be made up for by power and speed.
Whether or not it has an amazing battery life should be amongst the first factors you should consider when making a laptop purchase for data science. Most of the data computations, analysis, and software you’ll work with will require high power consumption. If your laptop battery capacity is suboptimal, it will affect your workflow. We recommend going for a laptop with up to 8 or 10 hours of battery life.
How to Find Cheap Laptops for Data Science
- Avoid Multi-Featured Brands. The more features a laptop comes with, the more money it’ll cost you. If you’re just starting, you don’t necessarily need a high-end laptop. You can stick to standard featured laptops that have 8GB RAM space, 512GB SSD or HDD storage units, and an Intel Core i7 processor for solid computing performance.
- Go for Fairly Used or Refurbished Laptops. Purchasing a fairly used or refurbished laptop is an ideal way to acquire a high-end laptop for a cheap price. Refurbished laptops have undergone maintenance by their manufacturers or retailers and as such have to be sold for much less than the market price. Used products are still completely functional, which makes them ideal for those on a budget.
- Wait for Special Offers. If you need to save some cash and have no urgency to own a laptop, you can wait for special sales such as discounts, coupons, holiday sales, promo deals, giveaways, and vouchers. Companies like Amazon occasionally have offers that last for short periods of time and are meant to encourage bulk purchases.
The Best Laptops for Data Science in 2023
|ThinkPad P15 Gen 2||Lenovo||$3,299||NVIDIA 4GB graphics card, 16GB RAM, and 512GB SSD|
|ZBook Fury G8||HP||$3,187||Intel Xeon CPU, NVIDIA RTX, 128 GB RAM and 8TB.|
|ZenBook Pro Duo UX581||Asus||$2,999.99||OLED HDR Panel, NVIDIA Geforce, intel core i9-8 core|
|Dell Precision 5760||Dell||$2,059||AI and VR optimizer, NVIDIA graphics, Intel Xeon or Core i9, and Windows11|
|MacBook Pro 14” or 16”||Apple||$1,999||Retina XDR display, M1 Pro or Max, 21 hours of battery life|
|MacBook Air||Apple||$999||M1 chip, 8-core CPU, 8-core GPU, and 18 hours of battery life.|
|Dell Inspiron 15||Dell||$968.99||11th Gen intel core i7, Windows, 16GB RAM, and 512GB SSD|
|Acer Swift X AMD||Acer||$949.99||AMD Ryzen 5000, NVIDIA Geforce RTX graphics, and 8GB RAM|
|Asus VivoBook Pro 15||Asus||$919.99||15.6-inch screen, core i5, 8GB RAM, and NVIDIA Geforce GTX|
|IdeaPad 3||Lenovo||$724.99||Intel iris plus graphics, 8GB RAM, 512GB SSD, and fingerprint reader.|
Top Rated Laptops for Data Science: In Detail
ThinkPad P15 Gen 2
- Best for: Those looking for a mobile workstation
- Price: $3,299
Built for large-scale multitasking, professional data scientists will find this mobile workstation suited to all types of data analysis tasks. Its base model comes with an 11th generation Intel Core i7 processor, a Windows 10 Pro 64bit operating system, NVIDIA T1200 4GB graphics card, 16GB of RAM, and a 512GB SSD. This system with a 15-inch screen has 10 hours of battery life and is known for its incredible performance.
ZBook Fury G8
- Best for: visualizing complex datasets
- Price: $3,187
The ZBook series was designed for data science and machine learning tasks. It can be used to scrape, organize, edit and visualize large datasets on the go. It was designed with the same computing capabilities and battery efficiency as desktops and comes with an Intel Core CPU for computing and the option of an NVIDIA GeForce RTX or AMD Radeon for the graphics processing unit.
Asus ZenBook Pro Duo UX581
- Best for: display resolution
- Price: $2,999.99
The Asus ZenBook Pro series is also an excellent choice for data scientists. Designed to facilitate workflow efficiency, this sleek design laptop comes within advanced features such as a 4K UHD display and screen pad, plus a numeric keypad solution, an NVIDIA Geforce RTX 2060, Windows 10 Pro, and an Intel Core i9 for optimal CPU computing and graphical performance.
Dell Precision 5760
- Best for: data optimization
- Price: $2,059
If you like Dell’s laptops, you’ll appreciate the computing performance and modern design of the Dell Precision 5760. Specially designed for data scientists and machine learning engineers who wish to construct neural networks and optimize deep learning algorithms, this lightweight laptop offers users the latest Intel Core or Xeon processors and amazing graphics.
MacBook Pro 14” or 16”
- Best for: data science
The MacBook Pro 14” and 16” were built for professional developers, scientists, and engineers. It comes with an in-built M1 Max chip for faster computing and graphics performance. You also get between 17 and 21 hours of battery life, an impressive retina display and camera, and audio and USB ports to facilitate all forms of large-scale data analysis and collaboration between teams.
Best Laptops for Data Science Under $1,000
- Best for: learning data science
- Price: $999
The MacBook Air offers data scientists advanced computing at an affordable price. Just like the Pro, it was built with the Apple M1 chip which ensures faster CPU processing and performance. It also comes with an advanced neural engine for your machine learning needs. Its lightweight design and 18 hours of battery life make it the perfect classroom accomplice for beginners.
Dell Inspiron 15
- Best for: those looking for a budget laptop for data analysis
- Price: $968.99
Dell Inspiron 15 is another smart choice for science or data analysis students who wish to learn using advanced systems. This laptop model can be configured with an Intel Core i7 or AMD processor to suit your high-speed computing needs. It comes with the latest Windows 11 version, a 15.6 FHD display with a 60Hz refresh rate, 16GB of RAM, a 512 HDD, and an Intel Iris Xe Graphics Core.
Acer Swift X AMD
- Best for: multitasking
- Price: $949.99
The Acer Swift X AMD was designed for multitasking, which makes it one of the best data science and deep learning tools. This sleek laptop has an impressive 6-core AMD Ryzen 5 processor and the latest NVIDIA Geforce graphics controller model. If you’re interested in writing efficient code and building innovative AI programs, this modern laptop is everything you need.
Asus VivoBook Pro 15
- Best for: data computing
- Price: $919.99
If you can’t afford the Asus ZenBook Pro, the Asus Vivobook is also an ideal purchase. Originally designed as a gaming laptop, it can be used for multiple data science tasks. It is built with a 15.6-inch OLED FHD, an Intel Core i5 processor, an NVIDIA Geforce graphics card for advanced graphics performance, and an ergonomic backlit display design.
Lenovo IdeaPad 3
- Best for: those looking for a budget laptop for data science
- Price: $724.99
The Lenovo Ideapad 3, although the cheapest on the list, is amongst the top contenders for data science laptops. This smart system comes with the latest version of the Windows operating system. The graphics core is the Intel Iris Plus and has a 17.3-inch screen. Although the 8GB of RAM is not that big, it makes up for it in storage space with a 512GB SSD.
Should I Use a Laptop for Data Science?
Yes, you should. If you’re planning on learning data science or working in the machine learning field, you need a laptop for when you’re working on the go. More specifically, you need a workstation laptop designed with high computing capabilities, an excellent graphics cards, and a storage unit for reliably processing large workloads.
The batteries usually have standard voltage. Ordinary laptops may not have the processing power, roomy storage, or brilliant display you will need if you want to break into the tech field and become a data scientist or enroll in a data science bootcamp.
Best Laptops for Data Science FAQ
To efficiently perform your data science and analysis tasks, you need a RAM size of at least 16GB, especially if you’ll be building data models. If you can’t afford a system with 16GB of RAM, 8GB RAM can also serve your computing needs. Generally, systems with more RAM offer faster system start-up and ensure you can run several software applications at the same time.
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Yes, it is. Owning a laptop ensures you can accomplish a lot of computing tasks within a short time frame at your own convenience. Laptops offer the portability that desktops can’t offer. You can easily move around with your laptop. They come with advanced features for writing code and processing deep learning algorithms.
Yes, it is. The AMD Ryzen is an advanced CPU processor. Its multi-core processor provides excellent performance and speed for data computing tasks. Most of your data science tasks may need to be performed sequentially, so a high-end processor like an AMD Ryzen ensures the powerful performance of your mobile or desktop workstation.
Many data scientists prefer using Ubuntu-Linux because of its speed in analyzing data sets and how user-friendly it is. Others prefer the macOS, which has been known to possess advanced UNIX features that facilitate data manipulation and multi-tasking. You can also use Windows for data science in place of the other two.
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