Choosing the right laptop as a data scientist is an important step. From accessing and hosting databases to running queries and code, you will need a laptop that’s powerful, durable, reliable, and portable. In this guide, I ranked and reviewed the 14 best laptops for data science, along with our top 5 choices, so you can pick the best one for you.
The Lenovo Legion 5 Pro is my top pick because it packs power, speed, image quality, a full stack of common ports (USB, HDMI, etc.), and a full keyboard (with number pad), all in the mid-tier $1,500 price point.
Most Powerful for AI & ML
An extremely powerful machine with 1TB of hard disk size, 16GB of RAM, a 12th Gen Intel i7 processor, and an RTX 3070 Ti graphics card that will carry the weight of any database or code execution. It also has a 17.3 inch screen for easy viewing.
Best Graphics Display +Touchscreen
With a display resolution of 3840×2400, the Dell XPS 17 is in a class of its own for crisp images while you work. With 32GB RAM and an Intel i7 processor, it packs 8 cores and 16 threads of processing power so your beautiful screen is also fast.
HP challenges the powerful-computer space with this affordable model that’s perfect for beginners or those who need slightly less processing power. It has a reasonable 16GB RAM and 512GB of hard drive but runs a slightly weaker Ryzen 5 CPU than its more expensive counterparts.
There really is no better than the MacBook pro for data scientists. The 2021 models have upgraded to M1 CPUs and boast 16GB of RAM and 512GB hard drive space. If you’re connected to the Apple ecosystem, we recommend this one.
Are you looking for a new laptop that can handle your work as a data scientist?
When it comes to data, things aren’t as simple as using a basic laptop to host heavy data, servers, and clients, as well as run advanced queries and code. You’ll run slow (and maybe damage a weaker computer, depending on what you process).
You need something more powerful: a laptop built for handling these system-demanding processes.
This guide covers the best options based on 25 criteria: price, screen resolution, screen size, screen refresh speed, operating system, SSD Storage, RAM, CPU (speed, cores, threads, and cache), GPU (cores and memory), weight, battery life, keyboard size (partial of full), and ports (ethernet, USB-C/USB-A, headphone/mic, HDMI), and Webcam.
Laptops have a number of specifications that drive performance and price. Here are the things you need to consider (and we review for each recommended laptop in this article).
Required specs for data science laptop (where choice is available):
Now that you know what to look for, let’s get started.
Here are my top picks for best laptop for data scientists:
The Lenovo Legion 5 Pro is an underestimated laptop in the powerful PC space. It’s powered by AMD’s Ryzen 7 CPU and a NVIDIA 3060 GPU, making it rare in the $1,500 price point. It’s 16 inch size makes it portable but doesn’t sacrifice resolution (2560×1600) nor refresh speed (165Hz). If you’re looking for a laptop to handle data science work that will last and provides upgradability for a reasonable price, I recommend this Lenovo. What’s more, Lenovo’s customer service is decent, which can’t be said for many other brands.
Our Rating: 9.6 / 10
Rating: 9 out of 10.
Best For | Best Overall Laptop |
Price | $1,500 – $1,550 |
CPU Rating | Very Strong (Ryzen 7 5800h – 4.6GHz, 8 Cores, 16 Threads) |
RAM Rating | Strong (16GB) |
GPU Rating | Very Strong (NVIDIA GeForce RTX 3060, 3584 cores) |
The Legion 5 Pro is essentially a hard copy of the IdeaPad i3, but with more power and increased image quality. It inherits a user-friendly ports system, and Lenovo’s support is usually good. You can think of it as a step-up from the Acer Nitro 5, though it comes at an increase in price of appx. $230, making it a good candidate for data scientists who are just past the beginner phase.
Our Rating: 9.6 / 10
Rating: 9 out of 10.
With Windows 11 bugs fixed, the Lenovo Legion 5 Pro has a quality user experience. Though not styled as “sexy” as its Acer Nitro and Predator counterparts, the Legion 5 Pro has better visuals, runs faster, and has all the legacy ports you need. At 16 inches, it’s easy to transport but nevertheless packs 2560×1600 resolution and 165Hz refresh speed, making it the best user experience for the size. What’s more, it has a full keyboard built in, so you won’t need to purchase an external keyboard or number pad when hooking up to a larger monitor.
The Lenovo Legion 5 Pro 16 inch is priced at $1,500 – $1,550 on Amazon (tip: add each laptop to you shopping cart to easily compare later).
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It’s rare to find a powerful laptop in the $1,500 range with so much power, image quality, and decent customer service. I recommend the Lenovo Legion 5 Pro for beginners and experienced data scientists alike.
The Razer Blade 17 is the most powerful machine on our list. It will handle even the most advanced evolutionary programming, fuzzy logic, artificial intelligence, and machine learning programming with ease. And with 2560×1440 resolution backed by 144Hz refresh speed, the hardware is capable of fully levering NVIDIA’s 3070 Ti GPU, delivering a beautiful image quality.
Our Rating: 9.4 / 10
Rating: 9 out of 10.
Best For | Most Powerful Laptop for AI & ML |
Price | $3,100 – $3,200 |
CPU Rating | Strong (Intel i7 – 12800H (4.8GHz, 14 Cores, 20 Threads) |
RAM Rating | Strong (16GB) |
GPU Rating | Strong (NVIDIA GeForce RTX 3070 Ti, 6144 cores) |
If money is no object, the Razer Blade 17 is the best machine on our list. The specs speak for themselves — it’s loaded from start to finish with 144Hz refresh and 2560×1440 resolution, 1TB storage, 12th Gen i7 CPU and a NVIDIA 3070 Ti PLUS a coprocessor . The only way to make this machine better is more storage and upgrading to an i9 processor… but in truth, you won’t need to.
Our Rating: 9.4 / 10
Rating: 9 out of 10.
With the exception of a full keyboard with number pad, the Razer Blade 17 is a powerful machine that delivers high-quality imagery, allows for easy connectability through its multiple ports, and runs fast and smooth. They’re called Razers for a reason!
All its power comes at a price – the Razer Blade 17 comes in at $3,100 – $3,200 on Amazon.
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All in all, the Razer is the highest performing machine on the list. Like most computers in this article, the Razer is originally built for gaming. It’s top-tier technology is needed for that kind of intensive load, and many data science tasks have demand on image quality, making this a great choice for analysts looking at machine learning and artificial intelligence programming (Python, R, SQL, etc.)
If you want the best display quality and interaction, then Dell’s XPS17 is the right machine for you. It has a large 17 inch display with 4k ultra HD screen with 3840×2400 resolution that produces an unmatched image quality, powered by a NVIDIA 3050 graphics processing unit. Plus, it’s touchscreen. Definitely consider this machine if your goal is image quality and you can forfeit some power. Just make sure you get this one with 1TB SSD and Windows 10 (Windows 11 performs less well).
Our Rating: 9.0 / 10
Rating: 9 out of 10.
Best For | Visual Performance and Graphics |
Price | $1,500 – $1,600 |
CPU Rating | Strong (Intel i7-11800H (4.6GHz, 8 Cores, 16 Threads) |
RAM Rating | Super Strong (32GB) |
GPU Rating | Strong (NVIDIA GeForce RTX 3050, 2304 cores) |
The touchscreen technology on the Dell XPS17 takes some getting used to, but it’s easier to scroll and improved overall interaction with the screen. The image quality on the XPS17 is by far the best on our list. I like this one for data scientists who need to work long hours but don’t need to host databases or servers themselves (so it’s not recommended for freelancers).
Our Rating: 9.0 / 10
Rating: 9 out of 10.
The Dell XPS 17 user experience is best on our list. Given the best-in-class resolution and 4k UHD screen, the experience is comparable to Apple (see here for more information). That said, the computer will run slightly slower than other powerful Windows-based computers because of the i7 processor and NVIDIA 3050 GPU. For freelancers who need to do back-end hosting work, the tradeoff may not be worth it.
The Dell XPS 17 with these specs is priced at $1,500 – $1,600 on Amazon, or get it directly from Dell.
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All in all, the best way to decide on the XPS 17 is to ask yourself how important a high-quality screen is to you. If it’s not critical, you can get an equally-powerful machine with many more ports and functionalities, including a full keyboard (very important for me using data), in the Lenovo Legion 5 Pro .
At roughly $860, the HP Pavilion is our budget-friendly pick on the list. If you plan to work primarily at the office with limited local storage and host only partial local data, then this laptop may be the write choice for you. Just note that you may need an upgrade. Even basic laptops use the i7 processor because the i5 is simply too weak to handle big data. If you’re truly a beginner and just want to get your feet wet with data science, then I highly recommend going with the HP Pavilion if you don’t want to fork out a few more hundred for the Acer Nitro 5.
Our Rating: 7.5 / 10
Rating: 7 out of 10.
Best For | Budget Laptop |
Price | $850 – $990 |
CPU Rating | Mediocre (Intel i5-9300h (4.1GHz, 4 Cores, 8 Threads) |
RAM Rating | Mediocre (12GB) |
GPU Rating | Mediocre (NVIDIA GeForce RTX 1650, 896 cores) |
I like the HP Pavilion for starters who are in the discovery phase of data science. However, I don’t recommend it for professionals who want a home computer for practice.
Our Rating: 7.5 / 10
Rating: 7 out of 10.
The pavilion is a user friendly laptop. It has an industry-standard 1920×1080 display resolution, a number of USB ports, HDMI, Ethernet, and a full size keyboard. However, the 60Hz refresh speed is notoriously low, which will hurt the image quality. And it’s i5 Intel processor and combined with the NVIDIA 16 series will run slow in high-performance scenarios.
The HP Pavilion is affordably priced at about $860 on Amazon.
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The HP Pavilion is a great choice for beginners who want a budget PC to explore data science at home.
If you’re looking for an Apple product, there are really only two choices: the MacBook Pro 14 inch or 16 inch. While most Window laptops on the list are 15.6 to 17 inches, I feel this is a bit excessive. The 14 inch Pro is an ideal size for comfort working and traveling. It makes the 2021 Pro not only my top pick for Mac, but also for size-to-value. Even going into 2024, this model is hard to beat. If you like smaller laptops, I definitely recommend the 14 inch MB Pro. That said, MacBooks come at a price!
Our Rating: 9.4 / 10
Rating: 9 out of 10.
Best For | Apple Product & Size-for-Value |
Price | $2,200 – $2,300 |
CPU Rating | Super Strong (M1, 10 Cores) |
RAM Rating | Strong (16GB) |
GPU Rating | Super Strong (M1, 32 Cores) |
Unlike Windows computers, the CPU and GPU on Apple products are so-called “integrated,” which means the M1 Max Chip processes system demand and graphics demand at the same time, producing a superior performance. It’s no secret that Mac products are one of the few machines on which you don’t sacrifice much. The 14 inch MacBook Pro has retina graphics, a super strong processor, beautiful display, and excellent storage (up to 8TB — yes, you read that right).
Our Rating: 9.4 / 10
Rating: 9 out of 10.
The MacBook Pro, and all Apple products for that matter, have the best user experience on the market. From image quality to performance, they are the best machines.
The 14 inch MacBook Pro is priced at $2,200 – $2,300 on Amazon.
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The 14 inch 2021 MacBook Pro is my top pick as the best Apple laptop for data science. If you’re already involved in the ecosystem, I definitely recommend it. Though expensive, MacBooks last for several years, and are an investment you won’tneed to replace for years to come.
The Acer Nitro 5 is a top pick for many reasons.
Acer invested more than $70 million on user experience and sold over $1 billion worth of performance machines in 2020, so they’re a trusted brand that you can count on to evolve in the future. The design is simple, with a backlit full keyboard and 144Hz (which means the page refreshes 144 times/second) HD display. And you have the choice of NVIDIA GPUs (I recommend the NVIDIA GeForce RTX 3050Ti) and either Intel’s i5 or i7 CPU (I recommend i7 — the i5 is not for people doing data science work).
The Acer Nitro 5 is VERY competitively priced for the power it delivers. Most power laptops in the $1000 – $1500 range give in on GPU or CPU to keep the price down, or they use a special operating system like the HP Pavilion that can’t keep up with Windows or macOS. The Acer Nitro hits a nice position of power, user experience, and price.
Our Rating: 9.5 / 10
Rating: 9 out of 10.
With Windows 10, you’re using some of the best operating system tech available. The full-size keyboard means you don’t need to buy an external keyboard, and you can connect to a larger monitor while using the built-in keyboard. The 17.3 inch screen size is industry standard, and I like the Nitro 5’s “cut” edges because it helps pack the laptop into backpacks and suitcases when moving between work and home or traveling.
The Nitro 5 with i7 processor, Nvidia 3050 Ti GPU, Windows 10 is priced in the $1,000 – $1,500 range on Amazon, and you can also get it brand-new from Acer directly with full-service support and different combinations of specs.
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Ultimately, the Nitro 5 is an all around powerful laptop in a reasonable price range, beat by the Lenovo Legion 5 Pro, which has slightly better power and screen quality. That said, if you want a cool-looking laptop in the same space, the Nitro 5 is recommended.
In many ways the Predator Helios 300 is similar to the Nitro 5 (both made by Acer). The key differences are that the Nitro 5 has 1TB of SSD while the Predator has only 512GB, the Nitro has a NVIDIA 3050 GPU while the Predator has a NVIDIA 3060 GPU, the Nitro uses Windows 10 while Predator uses Windows 11 — and of course, the Predator is 1.4 inches smaller.
Overall, this means the Nitro is more powerful while the Predator delivers better visuals and is easier to pack, but just slightly. Most people choose Nitro because they like the red backlight and the Predator because they like the multi-color backlight and the Predator Sense app, which gives you deep analysis on the machine.
Our Rating: 9.5 / 10
Rating: 9 out of 10.
With Windows 11, you’re using the best operating system tech available. However, the Predator has been reported to struggle to maintain its battery life. Other than that, the full-size keyboard is practical, and allows you to connect to a monitor without the need to for an external keyboard. The 15.6 inch screen size is on the high-end of industry standards, and I like the Predator’s “cut” edges because it helps to transport, as with the Nitro 5.
The Predator is available on Amazon with the recommend specs here for $1,200 – $1,300.
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While there were some problems with Windows 11, Microsoft seems to have fixed the bugs on the Predator.
All in all, the Acer Predator Helios 300 is a great choice for those not looking for cutting-edge tech. It’s also a good for data scientists who don’t need terabytes of data to store locally (only 512GB SSD), and provides a strong alternative to the Acer Nitro 5 for those who want slightly stronger visual performance and a more portable size.
The MSI GE76 Raider is a good mid-tier candidate for data scientists who like a colorful, stylish machine that sticks out from the Acer Nitro 5 & Predator with a slightly more powerful GPU, and for data scientist who like good customer service (MSI is much better than Acer).
Our Rating: 9.4 / 10
Rating: 9 out of 10.
Using Windows 10, the MSI GE76 Raider is on the more advanced OSs from Microsoft (which is as good or better than Windows 11 for performance operations). It has a cool color bar spanning the front of the lower plane, and it competes with the industry standards in terms of resolution and performance. The full stack of ports (USB, Ethernet, HDMI) and full keyboard make it easy to use. Plus, it looks really cool.
The MSI GE76 Raider is prices at $1,540 – $1,550 on Amazon.
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The MSI GE76 Raider is a good mid-tier laptop for data scientists who want a cool looking machine. My take is that the Lenovo Legion 5 Pro is a better performing machine, and it’s typically slightly less expensive.
The Asus ROG Strix 15 is a strong candidate for ML & AI because it has a strong combination of processors, memory, and cache of all laptops on the list, for a reasonable price. Against the obvious competitor in this level — the Acer Predator Triton 500 (not on our list) — the Asus ROG Strix 15 comes in 33% less expensive (~$1000).
Our Rating: 9.3 / 10
Rating: 9 out of 10.
With great power comes a lot of heat. The Asus’s cooling system uses 4 fan outlets to keep cooling noise down while youprocess large amounts of data. While it doesn’t have a full keyboard or webcam, the laptop has 4 USB ports (2 on the back) so you can connect devices at your home and workspace without much interference. As with most powerful laptops, it’s a bit clonky, but this is counteracted by the standard 5 lbs weight. At 15.6 inches, the ROG Strix G15 is on the low end of industry standard sizes, and the 165Hz screen refresh speed makes it one of the more enjoyable user experiences.
The ROG Strix G15 with Ryzen 9 CPU, NVIDIA 3070 GPU, and 32GB ram is priced in the $2,000 – $2,200 range on Amazon.
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In the end, the ROG Strix G15 is a great laptop for those who need a powerful laptop for a slightly higher price. Comparable alternatives like the Acer Predator Triton 500 are often priced 50% more.
One of the few items on this list with both an AMD Ryzen 9 CPU and NVIDIA 3080 GPU, the ASUS ROG Zephyrus G15 is second only to the Razer Blade 17 in terms of processing power. It’s a good choice for those who already have standalone keyboards and webcams, because those are not built in.
Our Rating: 9.3 / 10
Rating: 9 out of 10.
The ASUS ROG Zephyrus G15 packs a lot of power, so it won’t run slow or glitch. The HD 2560×1440 screen is a pleasure to use. However, since this is a top-tier machine, the ports are lacking. It has no USB-A type slots, no ethernet, and no webcam. For those who don’t already have these adaptors and external devices, this means you’ll need to purchase them separately. That’s why we rank this machine lower than the Razer Blade 17.
Power comes at a price. The ASUS ROG Zephyris G15 is priced at ~$1,400 on Amazon.
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Like the Razer Blade 17, the ASUS ROG Zephyrus G15 is built for gaming. The NVIDIA 3080 GPU really isn’t necessary for data science unless you plan to run self-developed visualization software or host a company’s database locally. Otherwise, a more user-friendly alternative is the Razer Blade 17 (though it is ~$1,000 more expensive).
While larger screens are normal for Windows machines, this is a BIG screen for Apple. It’s the only reason why we pick the 14 inch over the 16 inch, but if you’re into the larger size and feel comfortable transporting 1 more pound of Mac, then you won’t find better than the 16 inch.
Our Rating: 9.3 / 10
Rating: 9 out of 10.
Just like the 14 inch, the MacBook Pro 16 inch has the best user experience on the market. From image quality to performance, they are the best machines. In our take, the 16 inch is quite large, so be sure you’re want a big screen.
The 16 inch 2021 MacBook Pro is available on Amazon for $2,400 – $2,500.
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If you’re in the market for an Apple computer and like the big screen, this one is for you.
Great Top-Tier Laptop for Those Who Want Market Leading Refresh Speed (360Hz)
The Alienware M15 R6 is another powerful laptop at a reasonable price that’s known for its command center technology that provide additional controls over the hardware. With 360Hz refresh speed, you won’t find other laptops to compete with the HD image quality for streaming or gaming. However, this is less important for data science work, so we don’t rank it in our top 5.
Our Rating: 9.2 / 10
Rating: 9 out of 10.
At 360Hz, the Alienware M15 R6 has the fastest screen refresh rates on the list, making it enjoyable to use. The keys are highly responsive and make for a durable interface with heavy-operations you’ll perform as a data scientist. The light blue backlighting and backside circle give the laptop a stylish look and feel. The only downside on user experience is the absence of a number pad.
The Alienware M15 R6 Gaming Laptop with 32GB RAM and NVIDIA 3070 GPU is priced at $1,940 – $1,950 on Amazon.
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The Alienware G15 R6 is a great laptop for those who want a portable, powerful machine for data science and would like to use it for streaming and other video-intensive operations. It’s 360Hz refresh speed is unmatched by competitors, and if you choose to upgrade the i7 processor to an i9, it’s arguably one of the best laptops for data science on the market.
Our choice of the Dell G15 is the only one of two mid-tier laptop with less than 1TB SSD. This laptop is rare in that it has the standard Intel i7 processor, a powerful NVIDIA 3060 GPU, and Windows 11, all on a hard disk of only 512GB. It’s a great data science laptop for those who are into Dell and don’t require heavy solid state storage because they’re on the cloud. However, it won’t be a great choice for those who want to host a lot of data locally.
Our Rating: 9.1 / 10
Rating: 9 out of 10.
The Dell G15 is a standard, mid-tier gaming laptop with Windows 11 that provides a basic 1920×1080 resolution and 120Hz refresh speed, so the interface will be industry-standard. It’s NVIDIA 3060 GPU carries a strong 3584 cores that delivery. It provides a full laptop and USB-A & USB-C ports, which means you can plugin older and newer devices.
The G15 is priced at ~$1,300 on Amazon.
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If you like dell and are looking for a strong, standard laptop that you can use for data science and as a home computer, the Dell G15 is a solid choice.
Best for Those Who Want a Budget Laptop that Packs 1TB Storage
The Lenovo IdealPad 3i is a budget laptop similar to the HP Pavilion. At $880, it’s an accessible laptop for data science. I rank the HP Pavilion higher for one reason: it’s Intel i5 processor is slightly more advanced and delivers better speed. It’s a nuance, but why not take more speed at a comparable price? Both have full keyboards, HDMI, Ethernet, and the same USB ports. There is one caveat: at 120Hz refresh speed, this Lenovo outperforms the HP Pavilion’s 60Hz, making the image quality slightly superior. For data science, I recommend speed over image quality.
Our Rating: 7.4 / 10
Rating: 7 out of 10.
As far as budget laptops go, the Lenovo IdeaPad has a standard user experience. With Windows 11, you have a familiar operating system, and the full keyboard makes data input easier. However, because of the weaker i5 processor, you will move slower on heavy data science analyses.
The Lenovo IdeaPad is priced at $880 on Amazon.
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All in all, the Lenovo IdeaPad is a strong candidate for beginners who want a budget data science laptop. However, like the HP Pavilion, you should be prepared to upgrade when you start performing advanced operations because the CPU and GPU will run slow.
This table provides a side-by-side comparison of each model on the list so you can easily see which is best for you. Scroll right to see all, or download the Excel here.
Spec | Lenovo Legion 5 Pro | Razer Blade 17 Gaming Laptop | Dell XPS 17 | HP Pavilion Gaming Laptop | MacBook Pro 14-Inch (2021) | Acer Nitro 5 | Acer Predator Helios 300 | MSI GE76 Raider | Asus ROG Strix G15 | Asus ROG Zephyrus G15 | MacBook Pro 16-Inch (2021) | Alienware M15 R6 | Dell G15 | Lenovo IdeaPad 3i |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Leader category | Best Overall | Most Powerful | Best Display | Most Affordable | Best Mac | – | – | – | – | – | – | – | – | – |
Rating (out of 10) | 9.6 | 9.4 | 9.0 | 7.5 | 9.4 | 9.5 | 9.5 | 9.4 | 9.3 | 9.3 | 9.3 | 9.2 | 9.1 | 7.4 |
Tier | Mid-tier | Top-tier | Mid-tier | Budget | Top-tier | Mid-tier | Mid-tier | Mid-tier | Top-tier | Top-tier | Top-tier | Top-tier | Mid-tier | Budget |
Price (USD, $) | $ 1,529 | $ 3,199 | $ 1,665 | $ 858 | $ 2,299 | $ 1,340 | $ 1,170 | $ 1,549 | $ 2,099 | $ 2,249 | $ 2,299 | $ 1,949 | $ 1,299 | $ 879 |
Screen Size (inch) | 16 | 17.3 | 17 | 15.6 | 14.2 | 17.3 | 15.6 | 17.3 | 15.6 | 15.6 | 16.2 | 15.6 | 15.6 | 15.6 |
Screen Refresh Speed (Hz) | 165 | 144 | 120 | 60 | 120 | 144 | 144 | 144 | 165 | 165 | 120 | 360 | 120 | 120 |
Screen Resolution | 2560×1600 | 2560×1440 | 3840×2400 | 1920×1080 | 3024×1964 | 1920×1080 | 1920×1080 | 1920×1080 | 1920×1080 | 2560×1440 | 3456×2234 | 1920×1080 | 1920×1080 | 1920×1080 |
Operating System | Windows 11 | Windows 11 | Windows 10 | Windows 10 | macOS | Windows 10 | Windows 11 | Windows 10 | Windows 10 | Windows 10 | macOS | Windows 11 | Windows 11 | Windows 11 |
SSD Storage (TB) | 1 | 1 | 1 | 0.512 | 1 | 1 | 0.512 | 1 | 1 | 1 | 0.512 | 1 | 0.512 | 1 |
RAM (GB) | 16 | 16 | 32 | 12 | 16 | 16 | 16 | 16 | 32 | 16 | 16 | 32 | 16 | 16 |
CPU | Ryzen 7 5800h | i7 – 12800H | Intel i7-11800H | Intel i5-9300h | M1 | Intel i7 11800H | i7-11800H | Intel i7-11800H | Ryzen 9-5900HX | AMD Ryzen 9 5900HS | M1 | Intel i7-11800H | Intel i7-11800H | Intel i5-11300H |
CPU Speed (GHz) | 4.4 | 4.8 | 4.6 | 4.1 | n/a for mac | 4.6 | 4.6 | 4.6 | 4.6 | 4.6 | n/a for mac | 4.6 | 4.6 | 3.1 |
CPU Cores | 8 | 14 | 8 | 4 | 10 | 8 | 8 | 8 | 8 | 8 | 10 | 8 | 8 | 4 |
CPU Threads | 16 | 2 | 16 | 8 | n/a for mac | 16 | 16 | 16 | 16 | 16 | n/a for mac | 16 | 16 | 8 |
CPU Cache (MB) | 16 | 24 | 24 | 8 | n/a for mac | 24 | 24 | 24 | 16 | 16 | n/a for mac | 24 | 24 | 8 |
GPU | NVIDIA GeForce RTX 3060 | NVIDIA GeForce RTX 3070 Ti | NVIDIA GeForce RTX 3050 | NVIDIA GeForce RTX 1650 | M1 | NVIDIA GeForce RTX 3050 Ti | NVIDIA GeForce RTX 3060 | NVIDIA GeForce RTX 3060 | NVIDIA GeForce RTX 3070 | NVIDIA GeForce RTX 3080 | M1 | NVIDIA GeForce RTX 3070 | NVIDIA GeForce RTX 3060 | NVIDIA GeForce GTX 1650 |
GPU Cores | 3584 | 6144 | 2304 | 897 | 16 | 2560 | 3584 | 3584 | 5888 | 8704 | 16 | 5888 | 3584 | 896 |
CPU Memory (GB) | 12 | 8 | 8 | 4 | n/a for mac | 8 | 12 | 12 | 8 | 10 | n/a for mac | 8 | 12 | 4 |
Weight (pounds) | 9.78 | 10.33 | 5.53 | 4.92 | 3.52 | 4.85 | 5.07 | 6.5 | 5.07 | 4.3 | 4.62 | 5.93 | 5.37 | 4.96 |
Battery Life (avg hours) | 6 | 6 | 9 | 8 | 17 | 8 | 7 | 6 | 8 | 8.5 | 21 | 4 | 8 | 9 |
Battery Life (performance hours) | 2 | 3 | 9 | 6.5 | 17 | 4 | 5 | 1.5 | 8 | 8.5 | 21 | 2 | 2.5 | 8 |
Keyboard | Full | Partial | Partial | Full | Partial | Full | Full | Full | Partial | Partial | Partial | Partial | Partial | Full |
Ethernet port | Yes, RJ45 | Yes, RJ45 | No | Yes, RJ45 | No | Yes, RJ45 | Yes, RJ45 | Yes, RJ45 | Yes, RJ45 | No | No | Yes, RJ45 | Yes, RJ45 | Yes, RJ45 |
USB-A Ports | 3 | 2 | 0 | 3 | 0 | 3 | 3 | 3 | 3 | 0 | 0 | 3 | 3 | 2 |
USB-C Ports | 1 | 2 | 4 | 1 | 4 | 1 | 1 | 2 | 1 | 2 | 4 | 1 | 1 | 1 |
Headphone port | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
HDMI port | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Webcam | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No | No | Yes | Yes | Yes | Yes |
To perform advanced operations in python, SQL, and advanced Excel, data scientists need a minimum RAM of 16GB, but 32GB would be better. All the the laptops we recommend have 16GB or more, even the budget HP Pavilion.
Some MacBooks before the 2021 MacBook Pros have less than 16GBs of RAM, including the MacBook air. This is not enough to perform advanced data science tasks. We recommend buying the MacBook Pro 14 inch (2021) or later.
In short, you need a powerful laptop for data science if you’re running advanced queries and code in SQL and Python, building AI & ML models, or hosting other data clients such as Tableau for visualization or R for statistical analysis. Advanced CPUs and GPUs are import for tactics like neural networks, fuzzy logic, decision tress, and evolutionary programming, and only powerful gaming-style laptops will have what you need.
The most powerful CPU for a data science laptop (not PC) is the AMD Ryzen™ 9 6980HX. However, very few data professionals need as much power as it provides. The best CPUs in machines we recommend are the AMD Ryzen™ 9 5900HS and the AMD Ryzen™ 9 5900HX. We recommend these in some of the laptops on our list.
Generally speaking, AMDs processors are better. If you’re look for top-tier performance, we recommend you choose a laptop with the AMD Ryzen 9 (such as the ASUS ROG Strix or the ASUS ROG Zephyrus). However, Intel’s i7 processors are also a strong option.
No, the Intel i5 is not a powerful enough CPU to handle data science work.
No, the Intel i3 is not a powerful enough CPU to handle data science work.
Yes, a graphics card is necessary in data science because you will need one to accompany a powerful CPU. That said, CPUs are more important than GPUs (graphics cards).
The most powerful GPU for a data science laptop (not PC) is the NVIDIA GEFORCE RTX 3090 Ti. However, most data professionals will not need the power it delivers. The best GPU for laptops we recommend is the NVIDIA GeForce RTX 3080, which is found only in the ASUS ROG Zephyrus on our list.
The best operating system for a data science laptop is Windows 10. Windows 11 has had early problems handling high-performance operations, though these will likely be resolved with update rollouts.
If you’re in the Apple ecosystem, then the newest macOS is your best bet. This is the case for me, since I have all my data wrapped up in the Apple cloud and store all files on my computer and phone at the same time.
Our top pick for the best overall laptop for data science is the Lenovo Legion 5 Pro.
The newer Apple laptops (from 2021) have stepped ip processing and graphics power with their M1 units, making them strong candidates fro data science laptops, particularly if you’re already involved with the Apple ecosystem and store data on the Apple cloud.
We recommend the 2021 14 inch MacBook Pro. You will want to avoid older models because they don’t pack the processing power found in Apple’sM1 CPU and M1 GPU. While the MacBook Air can seem attractive because of its small size, it won’t perform on advanced functions in python, visualization software like Tableau and PowerBI, SQL, and overall AI & ML operations.
Our pick as the best budget laptop for data science is the HP Pavilion.
Beyond specs and price, you should always consider brand when buying a laptop, especially when it will be used for heavy operations like AI & ML, or even just data visualization with big apps like Tableau or Power BI. The key brand-concerns are customer service, and upgradability.
Customer service is important at the time of purchase. If there is a problem with the computer or it was damaged during shipping, you’ll want to be able to discuss with the customer service to fix the problem. The good news is Amazon typically handles these complaints well. That said, when you’re buying brand-new products directly from the source, make sure to check customer service.
We provide a customer service score for recommended laptops in our guide.
How easy is it to upgrade components in your laptop, such as the CPU or GPU? How easy is it to transfer data from one computer to a newer version. Each laptop has a degree of installation difficulty, so if you plan to do manual upgrades, keep this in mind. When upgrading to a new computer, is there anything preventing a cloud data transfer or external hard drive transfer?
We review upgradability for all recommended laptops in this article.
Buying a laptop for data science is a big decision. You need to find the right balance of power, style, and price. For data science, the most important elements are functionality. The best way to approach your purchase is to first determine your price cap, then think about whether you will host data locally on your machine. Finally, think about how you will be using your laptop (traveling often, leaving it at home). Once you have an idea, it will be much easier to choose the best one for you. One thing is sure, your standard home laptop probably can’t handle the data-heavy processes required in data science — so you can rely on this review to get your upgrade.
Happy data wrangling!
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Noah is the founder & Editor-in-Chief at AnalystAnswers. He is a transatlantic professional and entrepreneur with 5+ years of corporate finance and data analytics experience, as well as 3+ years in consumer financial products and business software. He started AnalystAnswers to provide aspiring professionals with accessible explanations of otherwise dense finance and data concepts. Noah believes everyone can benefit from an analytical mindset in growing digital world. When he's not busy at work, Noah likes to explore new European cities, exercise, and spend time with friends and family.