10 Best Laptops for Data Science and Analysis [2022 Guide]

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Data scientists and people pursuing this career path require effective laptops throughout their learning process. It’s always better to have a laptop than a desktop PC in this line of work due to its apparent convenience and mobility. 

The data scientists of today work with vast amounts of data, converting, converting, and extracting relevant information from it. It is not easy to handle this much data on an everyday laptop, and no ordinary device can handle it. 

Also, the different stages of data science require various applications and tools. As such, I am not surprised you have a hard time picking the best laptop for your data science work. 

So, I’ve compiled a list of well-researched laptops for data scientists you can begin using right away.

Best Laptops for Data Science

1. Asus ZenBook Pro Duo 15

Asus ZenBook Pro Duo 15
CPU: Intel Core i7-10870H Processor (16M Cache, up to 5.0 GHz, 8 cores)
RAM: 16GB DDR4
Storage: 1TB PCIe NVMe M.2 SSD
Display: 15.6 inch OLED 4K UHD NanoEdge touchscreen + 14 inch 4K matte touchscreen
GPU: NVIDIA GeForce RTX 3070
PROS
  • NanoEdge touchscreen display
  • Detachable palm rest
  • Dual screen
  • Stylus support
CONS
  • Pricey

ZenBook Pro Duo 15 is a perfect laptop that you can use for data science. It has a dual-screen design that will allow users to multitask and get more done. Its display is really impressive, as well as its specifications and ergonomics. 

The launching of this laptop resulted in its immediate popularity among professionals such as artists, coders, etc. A dual-screen system allows for more efficiency and provides better performance for data science. 

The display size is 15.6 inches, with an OLED touchscreen panel that offers a 4K UHD resolution of 3840 x 2160 pixels. The best display panels utilize OLEDs that provide a rich contrast ratio and bright backlight. 

The screen-to-body ratio of the ZenBook Pro Duo 15 amounts to 89%. On top of that, the secondary display comes with a 14-inch diagonal screen size, featuring a touchscreen interface with a matte finish.


2. Razer Blade 14

Razer Blade 14
CPU: AMD Ryzen 9 5900HX 8 Core
RAM: 16GB
Storage: 1TB SSD
Display: 14 QHD 165Hz
GPU: NVIDIA GeForce RTX 3080
PROS
  • RGB key lighting
  • Vapor chamber cooling
  • Rapid refresh rate
  • Ultra-clear display
  • Powerful
CONS
  • Non-upgradeable RAM

If you are looking for a powerful laptop for data science work, you should choose Razer Blade 14. It comes with sufficient RAM and a powerful CPU so that it can handle data analysis well.

The laptop has a 14-inch display with thin bezels, which makes it both lightweight and portable. There are 2560 x 1440 pixels on this QHD display, which produces crisp, clear images. 

Further, it offers an IPS panel with 165Hz and 100% sRGB color coverage, so anything you project is displayed accurately and smoothly. It comes with 16 GB DDR4 RAM along with 1 TB of SSD storage.

Its AMD-powered CPU has impressive performance. The use of the Ryzen 9 5900X processor makes Razer Blade 14 a powerful machine. This processor has eight cores and a clock speed of 3.7GHz for high-performance computation. 

With a processor that runs at 4.8GHz, you will benefit from being able to handle heavy workloads. In terms of graphics, the laptop will be equipped with Nvidia’s RTX 3080, which comes with 8,704 CUDA cores, 10GB of memory, and a 320-bit memory interface.


3. Apple MacBook Air M1

Apple MacBook Air M1
CPU: Apple M1 chip; 8-core CPU with 4 performance cores and 4 efficiency cores
RAM: 8GB
Storage: 256GB or 512GB SSD
Display: 13.3-inch (diagonal) LED-backlit widescreen display
PROS
  • Optimal performance
  • Long-lasting battery
  • High-quality webcam
  • Runs quietly
CONS
  • Limited ports

The laptop that follows on the list is Apple’s MacBook Air that comes with the latest M1 processor. There is no fan on this laptop, and it has a solid aluminum build making it incredibly lightweight. 

Data scientists frequently use Linux-based laptops or consider MacOS, so MacBook Air is our recommendation for those data scientists. Besides, with a resolution of 2560×1600, Apple MacBook Air M1 features a 13.3-inch retina display. 

A 16×9 display with an IPS LED backlight and 227 pixels per inch is available. A significant advantage of this laptop is its color calibration, offering a wider P3 color gamut.  

The RAM is 8GB in the laptop, and the SSD storage is 256GB that ensures excellent performance with the macOS. It also offers a backlit keyboard with smooth key travel and an improved typing experience over its competitors. 

Further, Apple’s M1 chip drives the MacBook Air’s processing speed. The chip is usually found in smartphones, but it’s much faster and more efficient. With a 5nm lithography, this chip has various cores that have been integrated into one single chip.


4. Acer Swift X 

Acer Swift X 
CPU: AMD Ryzen 7 5800U
RAM: 16GB LPDDR4X
Storage: 512GB NVMe SSD
Display: 14 Full HD (1920 x 1080) IPS Widescreen LED-backlit 100% sRGB display with 300 nits brightness
GPU: NVIDIA RTX 3050Ti (4GB GDDR6 VRAM)
PROS
  • Biometric fingerprint reader
  • High-end color calibration
  • Lightweight
CONS
  • Does not have an SD card reader

You might want to consider the Acer Swift X if you want a laptop with good performance, battery life, build quality. Despite its mid-range price, it offers a premium appearance and excellent performance. 

At this price point, Acer Swift X will provide you with everything you need for data analysis. The screen has a resolution of 1920 x 1080 pixels and a size of 14 inches. The sRGB color space is 100% covered by this display which renders a color-accurate image. 

The laptop’s display is a strong selling point, thanks to its superior quality. Additionally, the laptop possesses 16 GB of RAM and 512 GB of SSD for super-fast multitasking. 

AMD Ryzen 7 5800U is the processor that has been used as its primary processing unit. It is regarded by many as one of the most efficient and high-performance AMD processors. 

The processor has eight cores and 16 threads and offers a base clock speed of 1.9GHz, which can go up to 4.4GHz. Apart from the CPU, it also has a powerful GeForce RTX 3050 Ti GPU offering 4GB of video memory. 


5. Asus ROG Zephyrus G14

Asus ROG Zephyrus G14
CPU: AMD Ryzen 9 5900HS Processor @ 3.1GHz (8 Cores, 16 Threads, 16M Cache, up to 4.60GHz)
RAM: 16GB DDR4-3200
Storage: 1TB M.2 NVMe PCIe 3.0 SSD
Display: 14 144Hz Full HD (1920 x 1080) IPS-Level PANTONE Validated Anti-Glare (100% sRGB)
GPU: NVIDIA GeForce RTX 3060 6GB GDDR6
PROS
  • Smooth performance
  • Lightweight
  • High refresh rate
  • Full HD display
CONS
  • No SD card reader

There is now a great deal of data analysis and processing work that is automated using artificial intelligence. When working with AI and machine learning, you also need a laptop capable of handling trillions of operations per second. 

As a result, we have added Asus Zephyrus G14 that will help you perform data analysis and other complicated tasks related to data science with ease. With a 14-inch display and slim bezels, this laptop boasts a sleek and modern appearance. 

It features an IPS-type display with anti-glare features, which prevent the display from hurting your eyes even after spending a long time looking at it. With a 1920×1080 resolution and 144Hz high refresh rate, this display has a high resolution and a smooth image. 

In addition to covering 100% color space, this display has outstanding color accuracy.

Further, the laptop runs on Ryzen 9 5900H processor, which is high-performing. The use of 8 cores and 16 threads enhanced the overall performance. You can increase the speed of this processor by 4.6GHz in boosted mode from a base clock speed of 3.0GHz.


6. Lenovo Legion 5

Lenovo Legion 5
CPU: AMD Ryzen 7 5800H 8 cores 3.2 GHz
RAM: 16GB DDR4 SDRAM
Storage: 512GB NVMe SSD
Display: 15.6 FHD (1920 x 1080) IPS
GPU: NVIDIA GeForce RTX 3050 Ti
PROS
  • Bluetooth 5.0 supported
  • 4-zone RGB backlight
  • TrueStrike keyboard
  • Minimalist design
CONS
  • Average battery life

Despite their gamer tag, Lenovo gaming laptops can be a great choice for your data science work. Lenovo Legion 5 is among those gaming laptops that will work fine for data science work as well. This laptop has a screen that measures 15.6 inches and has a resolution of 1920×1080 pixels. 

It also provides an IPS display panel with a 165Hz high refresh rate and a response time of 3ms. In addition, it includes color accuracy that meets 100% of the sRGB standard, resulting in vibrant and crisp images. 

Further, a 16GB DDR4 and 512GB SSD combination will provide you with enough memory and storage to store a lot of data. The Ryzen 7 5800H processor embedded within the laptop offers 16 threads for parallel computing. 

There is a maximum clock speed of 4.4GHz on this CPU, which is quite impressive. Although it’s an affordable gaming laptop, it still comes with a discrete GPU. It has an RTX 3050 Ti graphics card with 2,560 CUDA cores which render exceptional results. 


7. Dell XPS 13 9310 

Dell XPS 13 9310 
CPU: Intel Core i7-1185G7 Processor (12MB Cache, up to 4.8 GHz)
RAM: 16GB 4267MHz LPDDR4x
Storage: 512 GB M.2 PCIe NVMe SSD
Display: 13.4-inch FHD (Full HD 1920 x 1200) InfinityEdge Touch Anti-Reflective 500-Nit
GPU: Intel Iris Xe Graphics
PROS
  • Multiple Thunderbolt 4 ports
  • 500-nit brightness
  • Wi-Fi 6 supported
  • Full HD display
CONS
  • Small display

Dell XPS 13 9310 laptop is available for those interested in a laptop that matches the form factor of the Apple MacBook Air. The Dell XPS 13 9310 is intended for those looking for a premium-looking and feeling laptop. 

A powerful processor and long battery life make it an excellent option. With a resolution of 1920 x 1200 pixels, this laptop comes with a 13.4-inch display. Because this laptop has a touchscreen, it will significantly enhance productivity for you. 

Further, the display has a peak brightness of 500 nits, making it very bright and outdoor-friendly. The color gamut of this laptop is 100% DCI-P3, which results in better visuals. Featuring 16GB of RAM and 512GB of SSD, this laptop can handle any task you throw at it. 

The laptop comes with a Core i7-11857G processor, which boasts impressive performance. Featuring up to eight threads of multi-threading, it is a four-core processor from Intel. In boosted mode, the CPU can hit clock speeds of up to 4.8GHz due to the Turbo Boost technology. 

The use of a fast-processing unit can easily handle data science work. Unfortunately, this laptop does not include a dedicated GPU. Further, the Iris Xe Plus graphics are integrated into the Dell XPS 13 laptop. It is a perfect integrated graphics card, though it cannot match discrete GPUs for performance.


8. Microsoft Surface 4

Microsoft Surface 4
CPU: 11th Gen Intel Core i5
RAM:8GB
Storage: 512GB SSD
Display: 13.5 Touch-Screen 400 nits
GPU: Intel Iris Xe
PROS
  • Immersive Dolby technology
  • Sleek design
CONS
  • Not upgradable

The Microsoft Surface Laptop 4 is an excellent laptop for casual app development and data analysis. In the $1200 price range, this laptop offers high-end specifications. Despite its high resolution of 2256 x 1504 pixels, the laptop only offers a 13.5-inch display that is slightly smaller than its competitors. 

By using a 3:2 aspect ratio, the laptop display provides more vertical space for work. Besides, it offers a touchscreen display, so you can use a stylus or your hands to use it. 

The maximum brightness of this display is 400 nits, which makes it suitable to use outdoors as well. In terms of memory and storage, Microsoft provides 8GB RAM and 512GB SSD.

As a result of the Core i5-1145G7 processor, the laptop has a high level of performance. It utilizes Intel’s Turbo Boost technology, so its top speed is 4.2 GHz, which is quite impressive. Further, you will experience an enhanced performance because of 4 cores and eight threads. 


9. Asus VivoBook 15

Asus VivoBook 15
CPU: AMD Ryzen 7 5700U Processor (8M Cache, up to 4.3GHz, 8 cores)
RAM: 8GB DDR4
Storage: 512GB PCIe NVMe M.2 SSD
Display: 15.6 inch IPS Full HD NanoEdge
PROS
  • Fingerprint sensor
  • Wi-Fi 5
  • Connectivity
CONS
  • Outdated Bluetooth version

Data scientists might also prefer the Asus VivoBook 15, which is even more budget-friendly. Under $800, this laptop offers great value considering its price. Data scientists who perform causal data analysis can use it because it is an affordable option.

This laptop has a display that measures 15.6 inches with a high resolution of 1024×768 pixels. There are 1920 x 1080 pixels in its Full HD resolution. Considering the display’s size, brightness, and color accuracy, this is an excellent display for a data science user.

Further, the 16GB of DDR4 RAM included by Asus is quite impressive considering its price. The 512GB SSD provides fast data read/write speeds thanks to its SSD-based storage. Besides, Asus VivoBook 15 includes a powerful Ryzen 5 5500U processor that results in high-end performance. 

With six cores and 12 threads, this CPU can deliver decent performance. With its base clock speed of 2.1GHz and maximum boosted clock speed of 4.0GHz, the laptop has impressive performance. So, a laptop like this one is a good option for an amateur getting started in this field.  


10. Lenovo Chromebook Flex 5

Lenovo Chromebook Flex 5
CPU: Intel Core i3-10110U Processor
RAM: 4GB DDR4
Storage: 64GB eMMC
Display: 13 Laptop, FHD (1920 x 1080) Touch
GPU: Intel Integrated Graphics
PROS
  • Good build quality
  • 360° convertible
  • Narrow bezels
CONS
  • Might run noisy

Lenovo Chromebook Flex 5 is among the least expensive laptops on our list that you can also use for data science work. With a price of less than $400, this Chromebook is budget-friendly. 

Lenovo Flex 5 runs on ChromeOS rather than Windows, which is what a Chromebook does. Data science work at the professional level is not possible with this laptop as its specifications are also low. 

The laptop is only suitable for simple data science work, making it ideal for beginners. It comes with a 13.3-inch display that will help you enjoy Full HD images. Further, the display is an IPS with LED backlighting and touch functionality. 

It also supports a stylus pen, so you can use it as a tablet. The 2-in-1 convertible nature of the device allows the screen to be rotated completely, allowing it to be transformed into a tablet—a durable i3-10110U processor powers the laptop, which is dual-core. 

In addition, the processor runs four threads and can easily handle routine processing tasks.

Overall, Lenovo Chromebook Flex 5 is a worthy laptop to try for data science work. 


Laptop for Data Science Buying Guide

CPU

Every operation on a laptop or PC is performed by the CPU, which serves as the central processing unit. Having a fast, efficient CPU is essential for providing long-term performance.

When you do data science, you have to regularly process a lot of big data. Therefore, a CPU with multiple cores is necessary for a smooth and efficient experience in data processing. 

You should choose a processor with a minimum of 4 or 6 cores from Intel or AMD. An 8-core processor might be best if you have a larger budget.

GPU

Today’s AI and machine learning technologies cannot escape the data science stream. There are many instances in data science where it is necessary to process millions, if not trillions of rows of data, and even the most advanced software cannot handle it. 

An average CPU has six to eight cores, while an average GPU has 700 CUDA cores, with high-end GPUs having up to 2,000 cores. What is the point of speaking about cores? These cores are beneficial for executing algorithms that require parallel processing power, such as AI and machine learning. 

To put it briefly, GPUs provide many more processing cores, which makes them perfect for AI and machine learning applications. Therefore, the more cores a GPU has, the better. A higher number of CUDA cores or shaders will make it better. AMD or Nvidia are both good options while choosing GPU.

RAM

When it comes to data science, RAM is one of the most critical components of a laptop. The amount of RAM you have available can restrict your work when dealing with vast amounts of data. Just like in a laptop for programming, a high-speed RAM that is ample will ensure smooth multitasking and fluent processing.

If you purchase a data science laptop, 16GB of DDR4 RAM is ideal. It is essential to make sure the laptop has at least 16GB of RAM. In mid-range laptops, however, 16GB of RAM becomes somewhat problematic. 

You can get by with 8GB of RAM in such a situation, and if you need to upgrade your RAM later, you can do so. In that case, ensure the laptop you decide on has upgradeability.

Storage

Many data-related tasks occur on remote servers, where your laptop serves as a middleman. However, this does not mean you should disregard your laptop’s storage capability and speed.

On your laptop, choose a storage option that is fast and reliable. SSD storage is, therefore, essential to meet the requirements for high-performance processing. 

SSDs are much faster when compared with HDDs at reading and writing data. It means that keeping the entire operating system, data, and applications on SSD-based storage will dramatically improve performance.

Frequently Asked Questions

How much RAM does a data scientist need when working with data?

It is recommended that you have a minimum of 8 GB of RAM on your laptop to run data science applications. But you may want to consider expanding your RAM capacity to 16GB, especially if your data analytics and statistics applications are graphically intensive.

Also, make sure to check out Ethernet connectivity. With poor internet connectivity, connecting with a nearby LAN port could take hours, so you should also focus on that.

Do you have any recommendations for a good data science processor?

When looking for a CPU that can reach speeds of up to 3.4GHz, the Ideapad 330 having Core i5 is one of the better options. Larger data sets will benefit from the dedicated 16GB DDR4 RAM.

Is coding a requirement for data science?

Yes, because data science includes coding, SQL, NoSQL, Python, etc. Using programming languages makes it possible to organize unstructured data.

Do gaming laptops serve the needs of data scientists?

It is up to the data scientist to decide how much processing power is needed for the tasks they intend to perform on the laptop. For example, if you plan to build basic data models with tools such as Keras and Tensorflow, the only requirement would be RAM, assuming the device already has a powerful processor.

How We Picked/Tested?

We have tested the laptop’s processing power and typing ability while picking a laptop for data scientists. A data scientist’s job requires a lot of typing, so testing the laptop typing skills is vital. 

We ensure that touchpads and keyboards need to be ergonomically designed so users can type for extended periods. We also use an infrared thermometer to inspect the touchpad and keyboard. It allows us to determine which parts of the laptop are hot.

Conclusion

Buying a laptop as a professional is not always easy since many options are available. You should avoid laptops that freeze your system when doing heavy graphics-intensive tasks when buying laptops.

As a new buyer, if you’re interested in buying a laptop, see the product list prepared by us to determine which laptops are best suited for data science. Take the time to learn about the most important features to look for when you’re shopping for a laptop for data science work.

Therefore, you will select the most suitable laptop for data scientists. However, if you have any questions regarding the listed laptops, feel free to ask in the comments.

Alex Berg

Alex Berg

Founder, writer, editor-in-chief at LaptopTalks. Starting LaptopTalks is like a dream come true, combining two of his passions – writing and technology. Even in his free time, you can often find him by his gaming laptop playing the latest video games.

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