Data science is one of those sectors that has blown up in the past few years, with everyone jumping on the hype train. And choosing the right laptop for data science can be quite confusing since there are so many options. You’ve got gaming laptops, ultrabooks, workstation laptops, studiobooks, etc.
Things get even more complicated when you consider the fact that a lot of your work is done on a remote server or computer cluster with the laptop merely acting as an intermediary terminal.
Our top pick is the MSI GE66 Raider due to its exceptional performance and sleek design. This machine does cost a pretty penny, but it also performs better than any other laptop on the list.
Read on to learn more about how any why we selected the GE66 Raider as our champ, plus there are some other laptops that you might find interesting.
Here is our list of 7 best laptop for data science:
Is it a laptop? Is it a Christmas light show? Whatever it is, it is pretty fast thanks to Intel’s flagship laptop CPU and NVIDIA’s best laptop GPU- the RTX 2080 Super (Max-Q version). The GE66 Raider is a very flashy looking gaming laptop and it packs a 300Hz screen plus lots of RGB. Definitely not stuff you need in a laptop for data science.
But the hardware underneath? Now that’s what works for data science- a really fast processor in combination with plenty of fast RAM and a large PCIe NVMe storage drive. The build quality isn’t bad either and the overall design looks pretty sleek.
This laptops also functions excellently for deep learning and AI research, although we doubt the average student can afford one of these.
The display isn’t a true IPS panel, it is what MSI and others call “IPS level”, meaning it’s actually a TN panel with colors that are better than what you find on the average TN. The cooling system is solid, with plenty of thick and wide heat pipes carrying all the heat out of the laptop through strategically placed vents.
Great if you’re looking to do some machine learning and deep learning on a budget (relatively speaking). While most laptops with dedicated graphics cost far more, the GP65 Leopard stands out with an excellent price to performance ratio.
It packs the GTX 1660ti from NVIDIA which is by no means a powerhouse of a GPU, but it’s a solid lower mid ranger with more than enough CUDA cores for students and small enterprises.
The GP65 Leopard’s other selling point is of course the fact that it comes with a 10th generation Intel Core i7 processor and 16GB of DDR4 RAM, both of which are good if you work with large datasets.
It also has a 512GB NVMe drive which you can upgrade, so kudos to MSI. The laptop is actually not very thick or loud, and it is built well.
Plastic is going to feel like plastic, but the type and thickness of plastic used can have a big impact on durability.
This laptop uses quality stuff and has a great customizable RGB keyboard with a fairly large trackpad so you can use it without having to carry a mouse around with you.
The display is 120Hz, so if you ever feel like doing some gaming in between work, this machine will handle it very well.
The whole design vibe of this laptop screams “utilitarian and rugged”. It has no over-the-top fancy lighting (even though the keyboard is RGB backlit), nor is there any mention of aluminum, glass, magnesium, etc. being used for the chassis.
This is a simple plastic gaming laptop with a mediocre trackpad and webcam, designed to deliver an exceptional gaming experience for a relatively low price.
However gaming isn’t the only thing it does well. After all, any laptop can do anything provided it has the appropriate hardware.
Even though this is marketed towards gamers, it is secretly one of the best machine and deep learning tools you can buy.
And it has the AMD Ryzen 7 4800H processor which trounces even the Intel flagship Core i9-10980HK in certain tasks at half the power draw.
Talking of power, this laptop features a massive 90Wh battery which gives it a lot more runtime compared to the MSI GP65 Leopard that has a measly 51Wh battery.
The A15 is also MIL-STD 810H certified which means it is more resilient versus dust and physical shocks compared to regular laptops.
Are you a researcher or employee at some big company looking to purchase a powerful laptop for all your data science needs? The Dell XPS 15 7590 is designed for professionals looking to be at the top of their game, without sacrificing power for portability.
It features an Intel 9th generation 6 core i7 processor, paired with a NVIDIA GeForce GTX 1650 GPU.
This combination works perfectly with all major data science applications and libraries, delivering great performance without nuking the battery life.
And since this is an XPS laptop, you also get one of the best screens out there- 4k InfityEdge IPS panel with 400 nits brightness and 100% Adobe RGB coverage for when you need to edit photos or videos.
It also functions perfectly as a content consumption platform if you wish to watch your favorite movies and music videos in 4k with true to life colors.
The battery on this laptop is absolutely massive- 97Wh, it pretty much guarantees 8+ hours of backup so you don’t need to carry your charger around wherever you go.
Performance is further boosted by 16GB of DDR4 RAM, and a large 1TB PCIe NVMe SSD.
The laptop chassis is made from premium materials like aluminum and magnesium alloy, with glass on the trackpad.
The palm rest is made from carbon fiber, so it is light and extremely rigid (you also don’t feel the palm rest getting warm).
Another laptop from Lenovo’s business line targeted at professionals with no time to waste who need to be at meetings, make video calls, and do a lot of data analysis.
This is no ordinary ThinkPad, it’s an ultrabook with the power of a workstation. At first glance you can’t tell that this sleek machine is basically a Lenovo.
It is expensive, yes. But it’s well worth it, just for the processing power and keyboard. Lenovo laptops have always had excellent keyboards, and this is no exception.
We were curious to see if they could manage to deliver a satisfying typing experience even with such a thin laptop where you can’t have much key travel.
But surprisingly, the keys are tactile with just the right amount of audio feedback when you press them. Not too loud, not completely silent either- just perfect.
Unlike other thin and light models, the X1 Carbon actually packs a surprisingly large amount of ports- 2x USB 3.1 Type A, 2x USB 3.1 Type C with Thunderbolt 3, HDMI 1.4, etc.
And it even has a special feature- network extension Ethernet passthrough for Lenovo’s proprietary dock, it lets you access your corporate network when docked (giving additional security and access to files/ computers only available on your corporate network).
A true mobile workstation, the MSI WS75 10TK-468 is one of the best laptops for data science that money can buy. And yes, you’ll need a fat chunk of change for this beast.
It is powered by Intel’s flagship 8 core processor for laptops, the Core i9-10980HK which boosts up to 5.3GHz and has a massive 16MB of cache allowing it to decimate whatever you throw at it.
And since this is a workstation, it comes with a professional grade GPU in the Quadro RTX 3000. The RTX 3000 is based on the same TU106 chip used in the RTX 2070 but it has fewer shaders, less memory bandwidth, and slower clock speeds.
This GPU is designed mainly for professional workloads involving CAD, data science, AI, visualizing, and medical prospection.
Its drivers are professionally validated and thoroughly tested for mission critical tasks that can’t afford to crash or fail.
And since this is a workstation, it has twice the RAM of a standard gaming machine (32GB). Oh, and you can even upgrade it to 64GB if you need to.
Pretty impressive, considering the fact that this is not a very heavy or thick laptop despite being a mobile workstation. Shows you how far we have progressed in terms of cooling technology and processor nodes.
A contender to the MSI Raider and Stealth series, the ROG Strix Scar 17 is a gaming laptop at heart but can double as a monster of a workstation if you want it to.
Since the Core i7- 10875H is such a fast processor, it can crunch through even the most demanding datasets with ease. There is a RTX 2070 Super onboard this juggernaut which means it can do pretty much everything.
Visualization, neural networks, image processing, gaming- there’s nothing this laptop can’t handle. And with all those ports, you can hook up to 2 or 3 external displays for extreme productivity when you’re at office.
In terms of looks, it has the bold and slightly flashy styling typical of gamer laptops. If that is something you care about and don’t want your clients to sneer at, then we suggest you turn of all the RGB stuff before taking it to work.
If we ignore the tacky styling and heavy marketing towards gamers, this is a very good all rounder with great cooling and excellent build quality (even though the body is plastic).
ASUS ensured that the cooler doesn’t let this laptop heat up too much, even when you’re slamming the GPU and CPU simultaneously.
For data science, you want a laptop that has a fast processor, preferably an Intel 9th or 10th generation i7.
AMD Ryzen also works, and in some cases beats Intel’s best. Just make sure you’re purchasing a laptop equipped with the new Ryzen 4000 series processors. We recommend a Ryzen 7 4800H for serious enterprise work.
You’ll also need lots of RAM to load big datasets. We recommend at least 8GB if you’re on a budget, but 16GB is the standard amount. Anything more is always better, provided you do the sort of work that can use 32 or 64GB of RAM.
More RAM results in a smoother, more reliable experience since your programs won’t have to swap out stuff from memory which will result in a jittery experience (and even crashes in some extreme cases).
You definitely want an SSD. Having a super fast Core i7 or Ryzen 7 processor along with tons of RAM won’t matter when the entire pipeline is slowed to a crawl by spinning disks in your HDD.
It would be like having a sports car with an excellent engine and great transmission, but the gas tank from a lawn mower. You want a fast drive to feed all that data in time, and your laptop will feel snappier in general.
Everything from web browsing to booting up is many times faster with a SSD.
We recommend a minimum of 512GB when it comes to built-in storage, although you can always upgrade later down the road if your laptop has a free M.2 slot (or just replace the default SSD with a higher capacity model).
Frequently Asked Questions
Q. Can I use a MacBook?
A. Yes, Apple makes some really fast and well-built machines that feel good to work with. Everything on a MacBook is designed to deliver a fluid, intuitive, and premium experience. The keyboards are crisp and light, the trackpads are honestly unrivalled, and the displays are really color accurate with high resolutions. But do you care about that stuff as a data scientist? Because the more important thing is being able to run the applications that your enterprise uses.
While OSX is built on top of a Unix core and Unix is a very robust system, there are many software packages that isn’t available on Mac. Like the full-version of Excel, which MacBooks don’t get. You can’t run some really popular finance and trading applications on your MacBook. Power Query and Power Pivot are locked out of MacBooks since they run a cut down version of Excel.
Q. What if I’m a student on a budget?
Two of the most popular data processing tools- Python and R can really benefit from multicore performance, especially if you use libraries like R data.table which is a multi-threaded data frame that can use up all available cores in your system if allowed. A cheaper laptop will also come with 8GB of RAM, which is the bare minimum we recommend for data analysis and machine/ deep learning.
Q. What is the advantage provided by a dedicated GPU?
A. If you’re working with deep learning and machine learning, it exponentially speeds up the process in certain tasks like image processing (as compared to just using your CPU).You don’t need a laptop with a dedicated graphics processor unless you’re interested in deep learning. Only purchase a laptop with a RTX GPU if you are working with neural networking and GPU modelling.
And if you do get a laptop with a dedicated graphics card for AI and neural networks, make sure it is a NVIDIA GPU because their CUDA libraries are perfect for TensorFlow and PyTorch.
Q. Are gaming laptops good for data analysts and scientists?
A. Definitely, as they have more processing power than similarly priced ultrabooks or thin & light laptops. Plus, they tend to be more easily upgradable. Their thick design means the RAM and storage is usually not soldered to the mainboard and user replaceable. And they have better cooling systems to dissipate all the heat generated during intense computational workloads.
Gaming laptops are thicker and heavier. Plus, they come with dedicated graphics cards which you may or may not use for your specific data science applications. And you need to think if you’re comfortable showing up to a client meeting with a shiny “gamer” laptop that looks an oversized McDonald’s toy with RGB splattered all over it.
The MSI GE66 Raider is our unrivalled champion in terms of raw processing power. It has the fastest laptop processor Intel currently makes. The Core i9-10980HK is a 45W TDP part with 8 cores and hyperthreading, plus a 5.3GHz turbo boost frequency.
Another thing to note about these Core i9 chips is their cache size- it’s much larger than what you’ll find on an i5 or even i7 processor. More cache allows the processor to go through calculations faster since this memory is located on-chip for near zero latency and is much faster than RAM.
The GE66 is also equipped with an RTX 2080 Super graphics card and 8GB of GDDR6 VRAM, which makes it perfect for deep learning and image processing. There is no consumer-grade GPU on laptops that is faster than the RTX 2080 Super, and the only solutions more powerful are high-end RTX Quadro cards which are much more expensive.
That said, not everyone has several thousand dollars laying around to spend on a new laptop. Which is why the MSI GP65 Leopard is our “value champ”. It provides excellent processing power and a dedicated GPU alongside 16GB of RAM, all for a relatively low price that most people can afford.
Plus, it isn’t even that thick or heavy like most gaming laptops. If you want a low budget option for deep learning, the ASUS TUF Gaming A15 would be perfect with its RTX 2060 graphics card.
Don’t need a dedicated GPU? The Lenovo X1 Carbon is a laptop designed with professionals in mind, people who want a no-nonsense machine that is both extremely portable yet powerful.
And if you want a 4k display, there’s the Dell XPS 15 7590.