It goes without saying that the realm of data science has one of the most computing hardware-intensive requirements. And it’s not fair to generalize different types of data science-related computing requirements as equal. The computing requirement that is specific to you has mostly got to do with the specialization that you’re learning or working in. If you are someone who works on data sets and codes, a high CPU performance will be your first and foremost priority. On the other hand, if you are learning or working in deep learning/machine learning, a top-of-the-line graphics processing performance will help you compile the models, simulate them, as well as run them.
If you have already made it till here reading the intro, it’s likely that you have plans to buy the right laptop for learning or working on data science. While it’s impossible to suggest the ultimate laptop, we sure have done extensive research and compiled this list of 10 best laptops for data science.
By exploring our selection, we are positive that you will find the right laptop that will best meet the requirement that is unique to you. Although the laptops that we have included in this list aren’t specifically designed for several data science parameters such as datasets, machine learning models, coding languages, tools, and frameworks, the hardware configuration they pack sure does suffice for delivering a well-student performance.
Minimum requirement for the best laptop for data science
Before you move on to check out the laptops in the list, we recommend going through the minimum requirement list so as to better prepare yourself in making an informed decision.
- CPU – A core i7 CPU will be a good value for money as it can work for most types of data science-related requirements. A core i7 or i9 CPU with multi-threaded performance is good for compiling, simulation, dataset analysis, model training, and other such tasks.
- GPU – A good graphic processing performance is equally important for intensive data science-related tasks such as deep learning model training, model simulation, etc. Look for a dedicated GPU that has at least 2 GB of RAM.
- RAM – Multitasking such as using different tools, working on one or more coding languages, and using a browser for web research requires high bandwidth RAM. 16 GB RAM is the minimum recommendation.
- Storage – Storing large-sized, multiple datasets require plenty of storage space. Look for a minimum of 512 GB of SSD storage. 1 TB HDD storage will help you store all your important files, documents, programs, and tools in a consolidated way.
- Connectivity – A good combination of connectivity options, including Thunderbolt 3 port, USB Type A port, mini display port, and an HDMI port, will help you customize your laptop the way you want.
Review of Best Laptops for Data Science/Data scientist
Lambda TensorBook – Best overall

Lambda TensorBooks have gained good traction in the digital technology realm as its hardware configuration and features cater to varied requirements for machine learning, deep learning, and data science. This laptop is especially beneficial for data scientists and engineers who work for deep learning labs as it comes pre-included with CUDA, cuDNN, Keras, PyTorch, and TensorFlow.
Whether you are arranging data sets, using data analysis and mining tools, or working on coding platforms, the 10th generation Intel i7 8 core processor of Lambda TensorBook powers you for all your data science-related requirements. The base performance of the CPU clocks at 2.3 GHz and Max performance at 5.1 GHz.
packed with a beefy computing power
Apart from powerful CPU performance, this model also deserves a good spot among some of the best laptops for data science with its powerful NVIDIA RTX 2080 Super Max Q GPU that helps you seamlessly train models without any graphics processing performance issues. A best-in-class combo of 2 TB SSD storage and 64 GB DDR4 RAM completes the core configuration of this laptop.
Viewing all your work in progress in the Lambda TensorBook becomes a breeze with its 15.6 inch full HD display that has a 144 Hz refresh rate. Whether you want to connect an external GPU or other peripherals, the availability of one Thunderbolt 3 port, three USB 3 Type A ports, one HDMI port, one ethernet port, and one microSD card reader makes it all possible. This model also includes one separate headphone jack and one mic jack.
Pros:
- Powerful CPU and GPU
- Pre-included Lambda Stack includes several deep learning tools and libraries
- One of the highest RAM and SSD capacities
Cons:
- Bulky design
- Weight is a bit heavy
Lenovo ThinkPad X1 Carbon 7th generation – best value
If there are laptop series that stays true to their do-it-all spirit, the ThinkPad lineup from Lenovo is one. What’s great about this lineup is Lenovo is wholeheartedly dedicated to making consistent improvements in new models every year, and the X1 Carbon 7th generation is a perfect example of this.
It’s astonishing to see how the brand has been able to pack such a beastly performance in a fairly sleek chassis that has an overall weight of 4.6 pounds. If you are a student or a professional looking for one of the best laptops for data science that features the best of performance and portability, you cannot go wrong with this laptop.
a perfect balance of price and performance
The Intel i7 4 core CPU, with its 1.8 GHz of base processing power, makes it easy for you to work on complex datasets, arrange them, run codes and compile them, and machine learning/deep learning models. When you need to push through these tasks in a more intensive way, the 4.6 GHz of overclocking power of this CPU will not let you down. Working in sync with the CPU is the laptop’s Intel Integrated 620 graphics which doesn’t fail to efficiently handle graphics-intensive tasks.
Whether you need to multitask for a long period of time or frequently access multiple files and programs, the 16 GB DDR3 RAM of this laptop, together with 512 GB of SSD storage, works wonders in maintaining consistently fast speeds to effortlessly cope with your varied requirements.
The 14 inch full HD display of Lenovo ThinkPad X1 Carbon 7th generation looks fairly modern as compared to its predecessors. The thin bezels design of the display at both sides opens up more viewing room in the 14 inch footprint.
Unlike many sleek laptops in the 14 inch territory, this model offers a desktop-class typing experience with its ergonomic keyboard that has good key travel. Together with the 3 buttons trackpad, the keyboard helps you work on codes and datasets without breaking a sweat. Just like other ThinkPad laptops, this model comes with a robust suite of external connectivity options, including two Thunderbolt 3 ports, two USB 3.1 Type A ports, HDMI port, one ethernet port, and one headphone/mic combo jack.
Pros:
- Reliable performance
- Sleek chassis with a high-quality build
Cons:
- No the best GPU
Dell XPS 15 – best compact and power performance
Dell XPS laptops have been charting new-generation computing performance paths for all of the brand’s laptops. Dell has been highly successful in seamlessly fusing tasteful aesthetics with some of the best-in-class hardware configurations in the XPS models over the years. Dell XPS 15 may not be the best laptop for data science, but it sure does come close to being one with its well-calibrated performance.
aesthetically-pleasing power
Powering the Dell XPS 15 is a 9th generation Intel i7 6 core processor. The 12 threaded architecture of the CPU, combined with 4.5 GHz of overclocking power, helps you get most of your data science-related work done in a hassle-free way. The CPU is paired with NVIDIA GeForce GTX 1650 4GB DDR5 GPU which helps ensure that the overall computing performance of the laptop doesn’t fall short when it comes to tackling graphic-intensive requirements.
Joining the core computing ensemble of this laptop is 16 GB DDR4 RAM which makes even the most intensive multitasking tasks a breeze. In the storage department, Dell XPS 15 packs 1TB of SSD storage space which you can use to store all your data science work essentials or learning materials.
The design language of Dell XPS 15’s display is similar to that of MSI Prestige 15. The thin bezels design, in combination with 4K resolution, work wonders in offering an immersive viewing experience in the 15.6 inch footprint. The responsive touch feature of the display further improves accessibility. This laptop offers extra connectivity options with two Thunderbolt 3 ports, one USB 3 Type A port, one HDMI port, an SD card reader, and one headphone jack
Pros:
- High-end performance
- Premium look and feel
Cons:
- No full-sized keyboard
Razer Blade 15 – gaming beast and data science
Similar to MSI Prestige 15 and Dell XPS 15, Razer Blade 15 packs the best-in-class hardware configuration in a compact and lightweight chassis. What’s different about this laptop is it has an extra oomph to its performance which is usually reserved for desktop rigs. So, if you want a desktop-class performance in a sleek and lightweight laptop for working on data science, you cannot go wrong with this model.
the all-in-one workhorse
Although Razer Blade 15 carries a gaming DNA, it fits the bill as one of the best laptops for statistical analysis, data analysis, and machine learning, given its ultra-powerful performance which its 10th generation Intel i7 8 core processor has been calibrated to deliver. With Max Turbo, the CPU can crank up to a whopping 5.1 GHz of overclocking power.
Graphics processing performance in this laptop is hands down one of the best, it’s NVIDIA GeForce RTX 2070 Super Max Q 8 GB DDR6 GPU does all the talking. Completing the core computing set up of this laptop is 16 GB DDR4 RAM and 512 GB SSD storage that speed up multitasking, booting, and file loading times.
Razer Blade 15’s 15.6 inch 4K touch display doesn’t fail to offer vivid visuals that help elevate your work experience. Colors come to life with the display’s HDR 400 True Black technology. This laptop also comes with plenty of external connectivity options, including three USB 3.2 ports, two Thunderbolt 3 ports, one HDMI port, one SD card reader, and one headphone/mic jack. Despite the sleek design of the choices, Razer Blade 15 includes extra RAM and SSD slot for upgradability.
Pros:
- Top-of-the-line performance
- High-quality aluminum build
Cons:
- Not the best keyboard layout
Gigabyte AERO 15 – style and performance
Laptops from Gigabyte are synonymous with high performance and uncompromised reliability. The AERO 15 takes the credibility of the brand a notch higher with an ultra-modern look that is second to none. Apart from an eye-catching look, this laptop also comes with plenty of utilitarian features such as a full-sized backlit keyboard, a good number of port selections, and a durable profile that elevates your overall work experience.
style meets unmatched performance
Under the chassis of Gigabyte AERO 15 lies a 9th generation Intel i7 4 core processor that has a base operating power of 2.6 GHz which can be overclocked to 4.5 GHz. Working on graphics-intensive tasks is not a problem as the laptop’s NVIDIA GeForce GTX 1660Ti GPU with a dedicated 6GB DDR6 memory is there to back you up.
This particular mid-range model packs a 16 GB DDR4 RAM which is sufficient for you to enjoy uninterrupted multitasking sprees. The RAM of this laptop is upgradable up to 32 GB. Also, 512GB of SSD storage makes sure that you don’t run out of storage space.
Gigabyte AERO 15 gets the spotlight in the display department as well. The ultra-thin bezels design of this laptop’s ultra HD display is unlike any other. Accurate color calibration of the display helps elevate the viewing experience.
The laptop offers myriad connection options that include three USB 3.1 Gen 1 ports, one Thunderbolt 3 port, one mini display port, one ethernet port, one HDMI port, one SD card reader, and one headphone/mic jack. The combination of 2 cooling fans, 5 heat pipes, 11 vents maintain superior thermal management in this model.
Pros:
- Good overall performance
- High-quality build
Cons:
- Not the best speakers
MSI Prestige 15 A10SC-010 – Ultra Thin and 4K
To say that MSI Prestige 15 is an affordable alternative to the new MacBook Pro 16 inch is both right and wrong. Right in the sense that it features a premium build quality on a sleek and lightweight chassis which, otherwise, isn’t the case with high performing laptops. And wrong in the sense that its performance calibration attracts a different set of audiences, ones who prefer to stick to the Windows OS environment.
But looking at the bigger picture, it is totally justifiable to say that this laptop in on a league of its own in terms of build quality, performance, pricing, and overall bells and whistles.
lightweight chassis packed with heavyweight performance
One of the biggest highlights of MSI Prestige 15, as it is obvious from the first look, is its stunning-looking display that has ultra-thin bezels design on the top and sides. The 4K resolution of the display with a high level of color accuracy gives even some of the best laptops for big data and data science a run for the money.
The sleek chassis of this laptop houses a 10th generation Intel i7 6 core processor that helps you unleash your creativity with its unbounded performance. Working on data science-related graphics-intensive tasks such as simulating deep learning algorithms, performing statistical data analysis, and training machine learning models becomes possible, thanks to the laptop’s NVIDIA GeForce GTX 1650 GPU that has 4GB of DDR5 dedicated memory.
This range-topping model comes with 32 GB DDR4 RAM which backs you up for all your multitasking sprees. With a whopping 1 TB SSD storage space, this laptop comes as an unmistakable repository that can store all your data science essentials. A pair of thunderbolt three ports, 2USB 3.2 gen 1 ports, one HDMI port, one SD card reader, and one headphone jack provide connectivity options in MSI Prestige 15.
Pros:
- Consistent performance
- Sleek and lightweight chassis
Cons:
- Can run a bit hot at times
New MacBook Pro 16 inch – For mac users
When it comes to offering a high-level computer performance that’s well-suited for data science, MacBook Pros don’t play around. The new MacBook Pro 16 inch comes as a good laptop for data science with an improved CPU and GPU power can efficiently take on different types of software and distros Python, Anaconda, and Pandas.
The seamless multitasking experience that MacBook Pros are known for helps you run multiple tools even in the most intensive programs, distribution software, and libraries.
premium look, feel, and performance
The new Apple MacBook Pro 16 inch gets its core processing power from a 9th generation Intel i9 8 core CPU. With its 8 core architecture, the CPU can help you crush most data science-related multithreaded tasks such as compilation, simulation, and training.
Also, this new model sets a new benchmark for its predecessors in the graphics processing department with its AMD Radeon Pro 5500M GPU that has 4 GB of dedicated DDR6 memory. The 16 GB DDR4 high-bandwidth RAM of this laptop helps you steer clear of lag issues which, otherwise, can be the case when working on intensive multitasking tasks. This core i9 variant comes with 1 TB SSD storage with which you can’t go short on storage space.
Apart from unmatched performance, MacBook Pros are also popular for offering a high level of accessibility. This is true with the new MacBook Pro 16 inch as well. A well-married ensemble of a highly-responsive Touch Bar, ergonomic keyboard, wide trackpad, and 16 inch Retina display helps you maintain your productivity at its best. Although this model has a limited action or connectivity option, the availability of four Thunderbolt 3 ports and one headphone jack compensate with versatility.
Pros:
- Fast and reliable performance
- Premium look and feel
Cons:
- Can run a bit hot at times
Lenovo ThinkPad P53s – heavy packed RAM’s
If you want the versatility and reliability of a ThinkPad laptop while prioritizing a more beefed up performance, there is no reason why you shouldn’t choose the Lenovo ThinkPad P53s. In fact, it is safe to say that the P53s is one of the few well-calibrated models that embody the essence of what ThinkPads are truly capable of.
From sheer performance power to myriad utilitarian features and lightweight chassis, this model stands out as an all-in-one package among other best laptops for data science. Sure, its price point does fall in the premium range, but you do get more than what you have paid for.
the uncompromised powerhouse
Fascination in this laptop, specs-wise, starts with its Intel i74 core processor that operates at a base power of 1.80 GHz and can crank up to 4.60 GHz of peak power. NVIDIA Quadro P520 GPU with 2GB DDR5 RAM works in conjunction with the CPU to help you take on CPU as well as graphically-intensive tasks such as coding, performing statistical analysis, working on deep learning/machine learning models, and arranging and compiling datasets.
This particular model packs an unmistakable combo of 24 GB DDR4 RAM and a whopping 1 TB SSD storage capacity. The high bandwidth calibration of the RAM, coupled with the fast read and write capabilities of the SSD storage helps you multitask as well as load various datasets, program, and tools in a jiffy.
The viewing experience of Lenovo ThinkPad P53s’ 15.6 inch thin bezels full HD display is on par with that of other premium, work-focused laptops. The full-sized classic ThinkPad keyboard with ergonomic layout eases typing experience and improves your coding experience. This model comes with a dedicated program that you can use to optimize performance to best suit your specific requirements.
For external connectivity, Lenovo ThinkPad P53s offers one Thunderbolt 3 port, one USB Type C port, two USB 3.1 ports, one ethernet port, one HDMI port, one SD card reader, and one headphone/mic jack. Also, this particular model comes with a USB 3.0 external USB data hub which opens up more external connectivity options.
Pros:
- High-end performance
- Premium look and feel
Cons:
- Can run a bit hot at times
2020 HP EliteBook X360 1030 G3 – Budget laptop
Getting your hands on a powerful hardware configuration doesn’t necessarily meany that you have to shell out a high budget. Proving true to this notion is 2020 HP EliteBook x360 1030 G3 which packs a considerably impressive hardware configuration in a non-premium price tag.
This model also excels in the design department with its sleek and contemporary look that usually reserved for laptops that are categorized in the premium range.
premium performance at non-premium price
2020 HP EliteBook x360 uses an 8th generation Intel i7 4 core CPU to deliver a base operating power of 1.90 GHz that comes on par with that of some of the best laptops for statisticians and data analysts.
For lag-free and power-efficient multitasking performance, this model has a standard 16 GB DDR3 RAM which backs you up through and through. Also, the option of upgrading RAM makes it possible for you to better address your changing multitasking requirement. In the storage department, this laptop offers 512 GB of SSD storage space that helps you keep all your data science essentials within quick reach.
The display of this laptop, despite its compact 13.3 inch footprint, offers a good viewing experience, thanks to its thin bezels design. Also, the ergonomic layout of the keyboard and trackpad further improves the usability factor of this laptop. For external connectivity, HP EliteBook x360 includes two Thunderbolt 3 ports, one USB Type A port, one HDMI port, one SD card reader, and one headphone/mic jack.
Pros:
- Good overall performance
- Good-quality build
Cons:
- Not the best thermal management
Eluktronics Pro-X P650HS-G – strong built
If you want to access desktop-grade performance in a laptop, the gaming territory is the right avenue to explore. This is because some of the best-in-class gaming laptops like the Eluktronics Pro-X P650HS-G offers a core performance that isn’t compromised in any parameter.
Although primarily designed for gamers, this model sure does fit the bill as one of the best laptops for data scientists with a go-getter spirit.
built to performance and last
Eluktronics Pro-X P650HS-G leads the pack with 2.8 GHz of base computing power that its Intel i7 4 core CPU consistently delivers. If needed, the CPU, with the TurboBoost function, can crank up to 3.8 GHz of overclocking power.
Equally stunning is the laptop’s NVIDIA GeForce GTX 1070 GPU which has 8GB of dedicated DDR5 memory. The high graphics processing performance of the GPU helps this laptop blaze through even some of the most graphics-intensive tasks such as training and simulating deep learning/machine learning models. With a whopping 32 GB DDR4 RAM, this model gives a tough competition to other laptops positioned in the premium range.
Eluktronics Pro-X P650HS-G comes with 512GB of SSD storage space which helps you ensure that all your data science essentials are within quick reach. In a way, this model is designed to be future-proof as it offers two extra ram slots and HDD/SDD storage slots for upgradability.
The 15.6 inch full HD display on this laptop makes it easy for you to view all your ongoing work with utmost convenience. The external connectivity option in this laptop is superior, thanks to a slew of ports available in the chassis. The ports include three USB 3.0 ports, two USB 3.1 Gen 2 ports, two mini display port, one ethernet port, one HDMI port, one SD card reader, one headphone jack, one microphone jack, and one line out jack.
Pros:
- Top of the line computing performance
- Good upgradability option
Cons:
- A bulky and heavy design
Acer Predator Helios 300 – another gaming and data science
Another high performing laptop in the gaming territory that deserves a good spot among some of the best laptops for data analysis and data science is Acer Predator Helios 300. This laptop checks the boxes in all the performance-related parameters associated with data science and analytics.
What’s cool about this laptop is that it doesn’t fail to perform double duty as an entertainment device with its easily-adjustable performance parameters.
gaming performance well-suited for data science
Acer Predator Helios 300 uses a 7th generation Intel i7 4 core processor to deliver a base computing power of 2.8 GHz which can be overclocked up to 3.8 GHz with TurboBoost technology.
The graphics processing department, an NVIDIA GeForce GTX 1060 GPU with 6GB of dedicated DDR5 memory helps you alter, simulate, and train machine learning algorithms without breaking a sweat. The 16 GB DDR4 RAM doesn’t fail to keep all your active programs, files, and miscellaneous tools in memory so that you don’t face any lag in quickly accessing them. The laptop’s 256 GB SSD storage speeds up loading and booting time. An extra empty HDD slot offers the option of expanding the storage space.
Apart from computing performance, battery backup is another area where is Acer Predator Helios 300 gives a tough competition to other premium-range gaming laptops. The lack of benefits from 7 hours of battery back up which means that you can get more work done when you are on the move. The 15.6 inch full HD display offers a mid-level viewing experience. For external connectivity, this laptop offers one USB 3 Type C port, one USB 3 Type A port, two USB 2.0 ports, one HDMI port, one ethernet port, one SD card reader, and one headphone/mic jack.
Pros:
- Good performance
- Good thermal management
Cons:
- The display doesn’t have a thin bezels design
FAQs
1) How much RAM do I need for data science?
16 GBDDR4 RAM is the minimum recommendation for both data science students and professionals. 32 GB RAM will work the best for you if you have intensive data science-related multitasking requirements such as accessing multiple datasets, using two or more distro, and simultaneously running multiple tools.
2) What kind of computer is the best for data science?
The type of computer that’s best for your data science requirement totally depends on your preference. Both desktop and laptop are good and each of them have their own pros and cons. While desktops are comparatively affordable and powerful, they have a stationery design. On the other hand, laptops are a bit expensive and offer the best portability.
3) Which processor is best for data science?
A core i7 processor helps you get most of your data science-related tasks done, such as compiling and running codes, arranging data sets, and working on deep learning/machine learning algorithms. For simulating machine learning algorithms, a CPU with a multithreaded architecture will be the best fit.
Conclusion
For many data science-related requirements such as simulating and training deep learning/machine learning algorithms, the sole hardware configuration of the laptop you choose may require additional support such as external GPU or cloud-based GPU, RAM, and more processing power. Many professionals in the data science realm who use laptops as their main computer take the additional resource-based support of Amazon Web Services. Tapping on these types of add-ons will help you augment the overall performance of your laptop which, in turn, will help you better address your requirement and achieve proper results.