Finding the best laptop for data science can be more complicated than most people seem to think. There are a lot of things to keep in mind. OS, display, components, portability, battery life, and more.
That’s why we decided to help you out by sharing our experience with this article! So, without any further ado, let’s check out your best options – and also why they are the best!
Best Laptop For Data Science: Before You Buy
Before we start checking out laptops, there are a few things that you must keep in mind:
- OS: Anything with Linux, macOS, or Windows will do. Each OS has its own pros and cons. Just do keep in mind that Linux can be installed on basically any modern computer
- CPU: A Core i7 or at least a quad-core Ryzen is recommended. If you can’t afford that, then do keep in mind that performance may suffer in specific scenarios
- GPU: Dedicated graphics are often not necessary in this field of work. But in some tasks, they are. If you find yourself in such a predicament, get at least an Nvidia 10xx card – they work well for both gaming and work
- Storage: Chances are that you won’t need a whole lot of storage. But you’re going to need speed. So, we’d personally choose an SSD over an HDD any day – even if it offers less storage for the same money
- RAM: A minimum of 16 is recommended for Data Science. Especially if you multitask a lot. Running out of RAM will make a PC feel extremely slow
- Display: Bigger displays with good viewing angles can help a lot in such cases. Most people prefer 17 inches – even if that means sacrificing a bit of portability
- Portability: Speaking of portability, always pay attention to the laptop’s size. Not only by looking at the display but also at the thickness and the overall weight of the device
- Battery life: If you need to work unplugged, then definitely pay attention to the overall battery life of your choice
Our 5 Best Laptops For Data Science
So, we’ve taken a brief look at what components are most important in a data science laptop, it’s now time to take a look at what we’ve chosen as our 5 best:
Best Laptop For Data Science On A Budget
If you can’t afford to get something that meets the recommended requirements, then we wouldn’t go any lower than the HP Pavilion 17. If you spend a tiny bit more money down the line to put an extra 8GB module in it, then it’s not a bad choice at all. Specs:
- CPU: Intel Core i5-9300H
- GPU: Nvidia GTX 1050 3GB
- RAM: 8GB
- Storage: 256GB SSD
- Display: 17.3 LCD IPS Display at 1920 x 1080 (The 144Hz refresh rate that Amazon mentions is false information that’s yet to be corrected. Source)
- Battery: 3-cell, 52.5Wh. Provides up to 8 and a half hours of usage under optimal conditions. But, under real-life usage, probably half of that
- Weight: 6.07 pounds
The big IPS display that it offers makes it a good choice for this line of work. But do keep in mind that it makes the computer noticeably larger and bulkier as well.
If there’s one downside then that’s definitely going to be the RAM memory. However, as we mentioned above, you’ve got the option of adding more to it down the road.
Fortunately, RAM memory is relatively cheap. Unfortunately, the Core i5 won’t be able to handle heavy workloads and multitasking without taking performance hits. So, do keep that in mind.
If you’re into gaming, the GTX 1050 offers an entry-level experience with low graphics and it should be able to handle non-demanding titles fairly well. Just don’t expect wonders from a budget machine. After all, what you pay is what you get!
- Relatively cheap
- Big IPS display
- Decent battery life (GPU and CPU aren’t very power-hungry)
- Aggressive, beautiful design (Could be a con for those who prefer something plainer)
- Good for entry-level gaming
- The base version comes with 8GB of RAM
- Not the most portable option
2: Asus ROG Zephyrus S (GX531GS-AH76)
If you’re looking for a laptop that can do it all, the Asus ROG Zephyrus S is one of the best VFM devices that you can get! It offers everything that’s necessary not only for Data Science but for gaming as well without sporting a premium price-tag!
- CPU: Intel Core i7-8750H
- GPU: Nvidia GTX 1070 Max-Q
- RAM: 16GB
- Storage: 512GB Nvme SSD
- Display: 15.6 LCD IPS Display at 1920 x 1080 with a 144Hz refresh rate
- Battery: 4-cell, 60Wh (Typically doesn’t last more than 2 hours under heavy use)
- Weight: 4.62 pounds
At 15.6 inches, this is a great balance between having a somewhat large display and portability in one package. However, the battery is extremely small for something so powerful and you can see that not only in gaming and heavy tasks, but also in day to day usage.
Other than that, the half-terabyte SSD, 16 gigs of RAM, and the powerful Core i7 should be more than enough to cover most of your professional and consumer needs alike.
- Powerful CPU and GPU
- Plenty of RAM out of the box
- The high refresh rate display along with the GTX 1070 make this ideal for demanding gamers
- RGB keyboard for those who like this sort of thing
- A bit more lightweight compared to the competition
- Renewed (Pay attention to the seller’s ratings)
- The battery is way too small for something that needs so much power
If portability is your main concern, then the Microsoft Surface Pro 7 is quite possibly the best laptop for Data Science that you can get! It’s actually more of a tablet/laptop hybrid. But a “normal” version of Windows 10 – just like every other computer.
- CPU: Intel Core i5
- GPU: Intel Iris Plus Graphics
- RAM: 8GB
- Storage: 256GB SSD
- Display: 12.3 LCD IPS display at 2736 x 1824
- Battery: Up to 10 and a half hours of usage (MS doesn’t mention technical details)
- Weight: 1.70 lbs
While this model comes with 8GB of RAM, there is another variant that offers 16 instead. So, we’d highly recommend getting that instead – if you can get your hands on it.
There are also other variants that bring a more powerful Core i7 which can be a huge plus for heavy multitaskers. But, not a single one of them comes with dedicated graphics.
So, if you’re interested in gaming as well, then we’d recommend looking at one of the other options.
Now, as far as portability is concerned, nothing beats the Surface Pro 7! It’s basically a big tablet with Windows 10 that can easily be transformed into a laptop with its detachable keyboard and stand.
- Extremely lightweight for a laptop
- Extremely portable
- Great battery life
- Offers a design that allows you to switch back and forth between tablet and laptop in one device
- Base versions come with 4 or 8GB of RAM – get the 16GB version if possible
- Small display
- No dedicated graphics
4: Great Value: Acer Predator Helios 300
Best Value For Money
If you need a brand-new laptop that’s great not only for working but also for mid-range gaming, then the Acer Predator Helios 300 is quite possibly your best bet!
- CPU: Intel Core i7-9759H
- GPU: GTX 1660 Ti 6GB
- RAM: 16GB
- Storage: 256GB Nvme SSD
- Display: 15.6 LCD IPS at 1920×1080 144Hz
- Battery: 68 Wh, up to 6 hours
- Weight: 5 pounds
The Core i7-9759H is one of the most powerful laptop processors that you can get your hands on. Second only to the Core i9. So, do understand that we’re looking at a powerful machine here.
Now, the 1660 Ti may not exactly be up there in terms of performance (The high refresh rate is mostly useful on competitive titles – don’t expect to hit 144FPS on modern AAA titles). But this list is mostly made with Data Science is mind and this is going to be more than plenty for such tasks.
There is a chance that you may need more than the 16GB of RAM that the Helios 300 offers out of the box. But, upgrading to 32GB should theoretically be possible.
- Powerful CPU
- 16GB of RAM out of the box
- High refresh rate display
- Decent GPU for both work and gaming
- The battery is mediocre at best
Best Mac For Data Science
If you want the best laptop for data science and you’re into Apple’s ecosystem, then the MacBook Pro 15 is definitely one of the most suitable picks.
- CPU: Intel Core i9 (9th gen)
- GPU: AMD Radeon Pro 560x 4GB
- RAM: 16GB up to 32
- Storage: 512GB SSD
- Display: 15-inch LCD IPS display at 2880×1800
- Battery: Up to 10 hours
- Weight: 4 pounds
A MacBook is, well, a Macbook! It uses macOS instead of Windows – which, as we all know, is much more optimized for the hardware, and it also works very well with other Apple products.
The touchbar is also another good addition if you’re interested in it. Now, in terms of raw power, the Core i9 may be the best CPU that you can get on a laptop, but do keep in mind that the Radeon Pro 560x isn’t the best GPU for gaming – especially for the money.
It’s still great for work-related tasks and chances are that those of you who want a Mac aren’t hardcore gamers anyway. But, we were obligated to give that fact a mention.
Do keep in mind that lots of people have reported issues with Microsoft apps such as Excel on Macs. But things seem to be getting better with time. Still, if you’re dead set on using the Microsoft suite then consider installing Windows or buying a Windows laptop instead.
- Good balance between portability and power
- Power-efficient – partially thanks to its optimized OS
- Works very well with other Apple products
- Offers the most powerful laptop CPU
- There have been various reports about Macs not playing well with certain Data Science-related software. So, make your own research on that depending on what you rely on
Best Laptop for Data Science: Wrapping Up
Now that everything has been said and done, you hopefully understand that each laptop has its own pros and cons. So, just pick whatever fits you best. And if that’s too much info to take in at once, here’s all you need to know in a nutshell:
- HP Pavilion 17: Best budget option with a big display but sacrifices a bit of portability
- Asus ROG Zephyrus S (GX531GS-AH76): One of the most powerful picks in this list and one that offers superb all-round performance
- Microsoft Surface Pro 7: By far the most portable laptop in this list but it doesn’t have dedicated graphics and the screen is rather small
- Acer Predator Helios 300: All around a balanced choice. Powerful processor, medium display, weight, battery, etc
- MacBook Pro 15: Your best bet if you need specifically a Mac. Very fast and very power-efficient while it works well with other Apple products. Its only downside is that it’s not really made for gaming and that certain programs don’t work as intended