12 Best Laptops For Data Science in 2020 [Top Picks by Data Scientists]

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Choosing a laptop for a data scientist can get tricky as you need to take several aspects into account. However, before proceeding further, you must understand that a majority of data-specific activities are initiated on a remote server and the computer mainly acts as an intermediary.

That said, things tend to get murkier in the absence of internet connectivity where you might need a responsive OS, faster processor (of course not the Intel Core i9), and enviable amounts of storage for more balanced performance. Also, if you’re a student, you would be performing most of the tasks on your computing machine itself (not all universities provide a remote server access.)

Besides that, Data Scientists use several applications and tools to analyze datasets, databases, and more. The likes of Tableau for data visualization or Terminal or connecting the device with the Data server, requires exceedingly high processing power. Many professionals often require access to SQL management resources like Workbench and prototyping tools like Anaconda for simplifying their work.

To start with, the operating system is an essential factor when it comes to selecting the perfect device for data science. Although the macOS works the best if you’re connected to remote server, However, you can always opt for a Windows 10 powered machine but with Linux on-board.

Although you won’t need a very powerful machine if you end to use remote server for your work. However, to make the best use of the mentioned tools, the concerned device must feature a powerful, multi-core processor, decent and fast SSD based storage, and a sizable RAM. In addition to these, the device must also feature a decent display followed by an ergonomic keyboard and a cohesive collection of usable ports.

Only if you are working alongside neural networks, machine learning, and indulging in parallel computing, it is necessary to opt for a device with a powerful GPU. However, as the graphics card isn’t upgradeable, you must always opt for the one that can handle your work (Don’t mind increasing the budget, because what’s the point in buying a laptop that isn’t capable of doing the task you bought it for?)

Minimum & Recommended System Requirements

 Minimum System RequirementsRecommended System Requirements
CPUIntel Core i5 (8th Gen)Intel Core i7 (9th Gen)
RAM8GB16GB
Storage256GB SSD and/or 1TB HDD512GB SSD or better
Display13.3-inch FHD (1920 x 1080)15.6-inch FHD (1920 x 1080)
GPUIntel Integrated UHD 620Nvidia GTX series GPU with at least 2GB VRAM
BatteryUp to 6 HoursUp to 10 hours

Best Laptops For Data Science in 2020

ImageNameFeaturesCheck Price
TensorBook

  • CPU: 2.3GHz Intel Core i7-10875H

  • RAM: 64GB

  • Storage: 2TB SSD

  • GPU: 8GB NVIDIA RTX 2080 Super Max-Q

  • Display: 15.6-inch OLED (1920 x 1080)

Asus ROG Strix Scar III

  • CPU: 2.6GHz Intel Core i7-9750H

  • RAM: 16GB

  • Storage: 1TB PCIe SSD

  • GPU: 8GB NVIDIA RTX 2070

  • Display: 15.6-inch FHD (1920 x 1080)

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Razer Blade Pro 17

  • CPU: 2.6GHz Intel Core i7-9750H

  • RAM: 16GB

  • Storage: 512GB SSD

  • GPU: 6GB NVIDIA RTX 2060

  • Display: 17.3-inch FHD (1920 x 1080)

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Apple MacBook Pro

  • CPU: 2.6GHz Intel Core i7 (9th Gen)

  • RAM: 16GB

  • Storage: 512GB SSD

  • GPU: 4GB AMD Radeon Pro 5300M

  • Display: 16-inch Retina (3072 x 1920)

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Dell XPS 15 7590

  • CPU: 2.6GHz Intel Core i7-9750

  • RAM: 16GB

  • Storage: 256GB SSD

  • GPU: 4GB NVIDIA GTX 1650

  • Display: 15.6-inch 4K OLED (3840 x 2160)

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Asus ZenBook 14

  • CPU: 1.8GHz Intel Core i7-10510U

  • RAM: 16GB

  • Storage: 512GB SSD

  • GPU: 2GB NVIDIA MX250

  • Display: 14-inch FHD (1920 x 1080)

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Lenovo ThinkPad P53s

  • CPU: 1.8GHz Intel Core i7-8565U

  • RAM: 16GB

  • Storage: 512GB SSD

  • GPU: 2GB NVIDIA Quadro P520

  • Display: 15.6-inch FHD (1920 x 1080)

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HP Envy 17T

  • CPU: 1.8GHz Intel Core i7-1065G7

  • RAM: 16GB

  • Storage: 256GB SSD + 1TB HDD

  • GPU: 4GB NVIDIA MX250

  • Display: 17.3-inch FHD IPS Touch (1920 x 1080)

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Acer Swift 3

  • CPU: 1.8GHz Intel Core i7-8565U

  • RAM: 8GB

  • Storage: 256GB SSD

  • GPU: 2GB NVIDIA MX150

  • Display: 14-inch FHD IPS (1920 x 1080)

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Lenovo Yoga 730

  • CPU: 1.6GHz Intel Core i5-8265U

  • RAM: 12GB

  • Storage: 256GB SSD

  • GPU: Intel Integrated UHD 620

  • Display: 15.6-inch FHD Touch (1920 x 1080)

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Apple MacBook Pro

  • CPU: 1.4GHz Intel Core i5 (8th Gen)

  • RAM: 8GB

  • Storage: 512GB SSD

  • GPU: Intel Iris Plus 645

  • Display: 13.3-inch (2560 x 1600)

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Lenovo Ideapad L340

  • CPU: 2.4GHz Intel Core i5-9300H

  • RAM: 8GB

  • Storage: 512GB SSD

  • GPU: 4GB NVIDIA GTX 1650

  • Display: 15.6-inch FHD IPS (1920 x 1080)

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Data science is a resource-intensive domain. Therefore, it is necessary to select the best laptops if you are an experienced or even an aspiring data scientist. In the subsequent sections, we shall segregate 12 of the best computing devices, perfectly suited towards data analysis and other relevant activities:

1. Best Overall: TensorBook

  • CPU: 2.3GHz Intel Core i7-10875H
  • RAM: 64GB
  • Storage: 2TB SSD
  • Display: 15.6-inch FHD OLED (1920 x 1080)
  • Refresh Rate: 144Hz
  • GPU: 8GB NVIDIA GeForce RTX 2080 Super Max-Q
  • Battery: Up to 2 hours

Enterprising data scientists that are looking for a powerful notebook to handle diverse aspects of Big Data repositories while accounting for concurrences with predictive intelligence, Machine Learning, and Data Visualization can rely on the Lambda Labs TensorBook for staying one step ahead of the competition.

Powering this innovative gadget is the Intel Core i7-10875H CPU that comes equipped with eight cores and 16 threads, courtesy of the Hyper-threading technology. The single-core turbo clock speed of up to 5.1GHz ensures that basic data processing tasks are handled with ease. However, the octa-core structure comes in handy if you are looking to pair single-threaded tools like Python and R with R data table and libraries. 

If you are a top-level data scientist who needs to work with ML frameworks and deep learning algorithms for training self-learning data sets, the NVIDIA GeForce RTX 2080 Super Max-Q comes in as a handy resource.

The existing CUDA cores and Tensor cores ensure that frameworks and libraries like Tensorflow and PyTorch are handled with ease. It also offers dedicated ML libraries out of the box as one-step software support as a part of its Lambda stack.

The existing GPU also comes equipped with 8GB VRAM which makes it a pretty functional gaming ally. When it comes to graphic speeds and the memory bus on offer, the RTX 2080 Super Max-Q is comparable, with almost every model barring the RTX Titan and 2080 Ti. In terms of CUDA cores, the featured processing unit is at par with RTX 2080 Super and way better than RTX 2070.

TensorBook comes equipped with 64GB RAM which ensures that you never run out of system memory while processing intricate datasets. You also get 2 Samsung EVO SSDs that are exceedingly fast when ‘reading and writing’ speeds associated with dataset rendering is concerned. When the operating system is concerned, Lambda Labs offers Windows 10 Pro, Linux Ubuntu, and a dual-boot option to choose from.

The 15.6-inch 1080p display is exceedingly vibrant. Then again, it is the 72 percent NTSC color gamut that ensures that other professional tasks like video and graphics editing can be initiated with perfection. The OLED panel is a great asset for creatives, making way for sharpest viewing angles and enviable color accuracy. Gamers, however, can rejoice as the 144Hz refresh rate keeps screen tearing to a minimum.

TensorBook comes equipped with some of the other bare essentials, including a backlit keyboard, basic touchpad, standardized speakers, and a serviceable webcam-microphone combo. Then again, it is the port arrangement that deserves a mention, as you get access to Thunderbolt 3, USB Type-A, and other display ports for legacy peripherals.

Connectivity-centric requirements are handled by Bluetooth, LAN, and Wi-Fi 6 compatibility. Then again, the 4.39 pound device doesn’t score any brownie points in the battery department with the 73Wh module, capable of lasting up to 2 hours, on heavy usage.

Pros
  • Powerful processor
  • High-end GPU with decent 90W TDP
  • OLED panel
  • Optional Dual Boot support
  • 64GB of System memory
Cons
  • Shorter battery life

2. Best Desktop Replacement: Asus ROG Strix Scar III

If you are an experienced data scientist, looking for a powerful desktop replacement laptop that would fulfill each one of your diverse professional requirements, the ASUS ROG Strix Scar III is the one to purchase. It is a gaming device but there is no application or tool this laptop cannot handle.

  • CPU: 2.6GHz Intel Core i7-9750H
  • RAM: 16GB
  • GPU: 8GB NVidia GeForce RTX 2070
  • Storage: 1TB PCIe SSD
  • Display: 15.6-inch FHD (1920 x 1080)
  • Battery: Up to 6 Hours

The Asus ROG Strix Scar III features a powerful Intel Core i7-9750H chipset with a turbo clocking speed of up to 4.5GHz. The unique processor allows you to install Linux Distros onto the device, besides the existing operating platform. In addition to that, Asus packs in a potent NVidia GeForce RTX 2070 GPU which is lighting fast and also brings forth 8 gigs of VRAM.

In terms of RAM support, you get access to 16GB of memory, which complements the processor further. Moreover, the 1TB PCIe SSD storage unit contributes towards the ultra-fast processing and data rendering speeds. The ROG Boost overclocking tech makes sure that high-end tools like SAP Lumira and PostgreSQL work like charm. Asus offers Windows 10 Home edition out-of-the-box.

The display on the ROG Strix Scar III is exceptional with the 15.6-inch screen flaunting a resolution of 1920×1080 pixels and sharpest possible viewing angles. Clubbed with the GPU, the device achieves a display refresh rate of 240Hz. The visual experience looks unique courtesy of the 80 percent screen-to-chassis ratio and the IPS technology.

The manufacturer has added an efficient keyboard with curved keycaps, backlit interface, fast actuating tabs, and the N-key rollover technology. The device also flaunts a highly functional touchpad with the ROG Keystone support. The multi-dimensional key offers access to the Shadow Drive and helps unlock gaming and work-based settings via a single touch.

This laptop is perfect for data scientists who are worried about overheating. ROG features enhanced fans with 17 percent increased airflow. Moreover, the device features several operating modes, depending on the criticality of the tasks. Besides that, you need not worry about cleaning the gadget frequently as Asus brings forth the innovative self-cleaning technology.

The gadget is extremely durable and resilient even against the harshest possible working conditions. The ROG Strix Scar III weighs a mere 5.97 pounds which is still manageable despite the device packing in a host of durable design elements. Most importantly, even with an extensive feature set, the overall thickness is less than a 1-inch. In terms of port management, you get USB Type-C and 6 other productive ports.

The battery is slightly underwhelming as, despite the intelligent cooling tech, you only get 6 hours of backup. Overall, this is an extremely powerful device for a data scientist as it runs applications like Tableau and Terminal without any issues.

Pros
  • Impactful processor 
  • Fastest possible storage unit with decent capacity
  • Excellent display courtesy of resolution and potent GPU
  • Durable chassis with triple radiators for heat dissipation
Cons
  • Less than adequate battery unit

3. Best 17-inch Laptop: Razer Blade Pro 17

  • CPU: 2.6GHz Intel Core i7-9750H
  • RAM: 16GB
  • GPU: 6GB NVidia GeForce RTX 2060
  • Storage: 512GB SSD
  • Display: 17.3-inch FHD (1920 x 1080)
  • Battery: Up to 8 hours

Nothing beats the excitement of purchasing an extremely powerful laptop that also looks great and flaunts a metallic chassis. Moreover, if you are into data science, the new Razer Blade Pro 17 is an excellent device to own courtesy of a sizeable display and a host of other functional specifications.

For data scientists, processing power is of paramount importance and the Razer Blade Pro 17 readily packs in a top-notch Intel Core i7-9750H chipset. This SoC facilitates faster data modeling and even supports data script prototyping applications like Anaconda.

Most importantly, if you are into deep learning and sentiment analysis, the existing NVidia GeForce RTX 2060 GPU is a sizeable addition, clubbed with 6 gigs of functional VRAM.

This device is a virtual powerhouse with zero-compromises in the memory department. You get 16 gigs of RAM which speeds up the processor further. Moreover, the 512GB of SSD storage unit is fast and comes with dual-channel upgradeability.

This means that it is easier to pair additional storage units, based on requirements, via the vacant M.2 slot. Windows 10 is the featured operating platform but you can easily install the Linux Ubuntu OS for running Terminal applications with ease.

In terms of display, the 17.3-inch panel is a great addition for data analysts. In most cases, data scientists require additional screen space to work on diverse spreadsheets or use multiple applications at once. This is where the 17.3-inch 1080p panel comes to the rescue. Other screen-specific specs include thinnest possible bezels and a refresh rate of 144Hz.

The new Razer Blade Pro 17 flaunts future-proof aesthetics with a focus on a responsive trackpad and a backlit and ergonomic keyboard. The featured keyboard also brings forth RGB lighting with more than 12 present profiles. Other features include biometric security courtesy of face unlock, IR sensor, and Windows Hello compatibility.

This powerful laptop weighs slightly more than 6 pounds but is enviable thin at 0.78-inch. The CNC, aluminum-clad unibody chassis adds to the durability of the same. Most importantly, even the experienced data scientists can indulge in demanding neural network designing without having to worry about overheating. The company brings forth vapor-chamber cooling technology, targeting demanding activities. 

In terms of connectivity and port management, the brand includes the USB 3.2 and the Thunderbolt 3 ports followed by a host of other slots. You also get enviable Wireless and Bluetooth connectivity for better productivity. The battery backup is a mere 8 hours which leaves a lot to be desired.

Overall, the Razer Blade Pro 17 is a perfect fit for the data sifters with an emphasis on screen size, cooling, and processing power.

Pros
  • Powerful processing conglomerate
  • Fast and upgradeable storage unit
  • Sleek design and durable chassis
  • Exceptional display with additional screen real-estate
Cons
  • Weak battery
  • Slightly on the heavier side

4. Best For Everyone: Apple MacBook Pro

  • CPU: 2.6GHz 9th Gen Intel Core i7
  • RAM: 16GB
  • GPU: 4GB AMD Radeon Pro 5300M
  • Storage: 512GB SSD
  • Display: 16-inch Retina (3072 x 1920)
  • Battery: Up to 11 hours

There is no denying the love of a data scientist for MacBooks. In most cases, applications concerning data modeling and visualization are designed to work the best on the macOS which validates the popularity of the new 16-inch MacBook Pro.

In terms of processing power, the new and improved MacBook Pro features a class-leading Intel Core i7 unit with a base clocking speed of up to 2.6GHz. The performances are further accentuated by the thermal layout and availability of turbo clocking speeds. Data scientists prefer processors with multiple cores and the new MacBook Pro has 6. The AMD Radeon Pro 5300M GPU is a market-moving component which works closely with 4 gigs of built-in VRAM.

Moving on, Apple also integrates 16GB RAM which lends decent support to the existing chipset. There is a 512GB of solid-state storage unit which is ultra-fast and offers a decent capacity to the data scientists. This feature allows you to install Windows OS running the Boot Camp. In addition to that, you also get 12MB of L3 cache memory for minimizing the access time further.

Apple still leads the path in terms of the display with the 16-inch screen featuring 3072×1920 pixels. Besides a decent display resolution of 226 pixels, the new MacBook Pro is also known for the excellent Retina Display technology, supporting deepest blacks, liquid crystal enhancement, and precise visual alignment. This device runs Mac OS X Catalina, straight out of the box.

If you are into data analysis, a decent keyboard always comes in handy. Apple MacBook Pro, therefore, stacks in the Magic Keyboard with 1 mm key travel followed by other accessible specs like the integrated touch bar and the intuitive Touch ID for added security. A lot of journalists, writers & bloggers, programmers, etc prefer the latest MacBook devices because of the great keyboard experience.

This device flaunts a metallic chassis and weighs a mere 4.3 pounds. In terms of port management, you get Thunderbolt 2 with USB-C support. As most data scientists prefer cloud server interactions, Apple makes sure that Wireless and Bluetooth connectivity is never an issue. You also get an 11-hour battery backup upon moderate to high usage.

Overall, the new MacBook Pro is the best choice for this profession courtesy of the speed and computing power. Most importantly, the graphics units are exceptional with this device also featuring an integrated Intel UHD 630 GPU for added support while handling intricate analytics. However, if you work only with remote servers then you shall consider getting the MacBook Air over this one.

Pros
  • Excellent graphics support
  • Sizeable battery
  • Top-of-the-Line Processor
  • Retina display with decent color reproduction
Cons
  • Underwhelming storage for seasoned data scientists

5. Best For Professionals: Dell XPS 15 7590

  • CPU: 2.6GHz Intel Core i7-9750
  • RAM: 16GB
  • GPU: 4GB NVidia GeForce GTX 1650
  • Storage: 256GB SSD
  • Display: 15.6-inch 4K UHD OLED (3840 x 2160)
  • Battery: Up to 14 hours

If you are looking for a feature-packed notebook that can handle technical and academic requirements with ease, the new Dell XPS 15 7590 is the perfect gadget. Moreover, if you are into data science and looking to handle massive repositories, this device has the requisite levels of firepower to get the job done.

There is an impactful Intel Core i7-9750 processor at the helm that clock at speeds of up to 4.5GHz under demanding circumstances. Besides that, you also get the NVidia GeForce GTX 1650 GPU which is powerful and clubbed with 4 gigs of VRAM support. In terms of OS, you get Windows 10, straight out of the box.

Dell brings forth 16 gigs of RAM that can handle intricate statistical analysis with ease. For instance, most data scientists prefer working with the SPSS Software from IBM that has a minimum RAM requirement of 4GB. This device has four times the required power, thereby making way for faster and reliable analysis. The boot-up time and data rendering are handled by the 256GB SSD storage unit.

The 15.6-inch screen looks marvelous courtesy of the OLED panel. Dell excels in the visual department with the 4K panel and a cumulative resolution of 3840×2160 pixels. The InfinityEdge display further enhances the screen and visual quality of this powerful device.

Dell leaves no stone unturned when it comes to packing an ergonomic keyboard and a highly responsive touchpad. Besides that, the company also allows a data scientist to indulge in leisure with the MaxxAudio Pro speakers. Moreover, you also get the smallest possible HD webcam on a laptop, owing to the innovative design.

Coming to the aesthetics, the new Dell XPS 15 features a metallic chassis that thrives on sleekness. The entire device weighs a mere 4 pounds and features USB 3.0, Thunderbolt, and other productive ports for improved functionality. Not just that, Dell also brings forth a responsive fingerprint scanner and excellent Wireless support for helping data scientists with improved security and connectivity standards.

The powerful battery offers a steady backup of up to 14 hours, regardless of the usage. To sum things up, this gadget from Dell fits in perfectly if the concerned data scientist has a penchant for faster performances and excellent display quality.

Pros
  • Excellent 4K UHD OLED display
  • Brilliant aesthetics
  • Powerful battery unit with a built-in battery indicator
  • Class-leading processor
Cons
  • Underwhelming storage capacity

6. Best Value For Money: Asus ZenBook 14

  • CPU: 1.8GHz Intel Core i7-10510U
  • RAM: 16GB
  • GPU: 2GB NVidia GeForce MX250
  • Storage: 512GB SSD
  • Display: 14-inch FHD NanoEdge Bezel (1920 x 1080)
  • Battery: Up to 12 hours

Despite being a hardcore data science professional, you might want to opt for style, creativity, and innovation while selecting a computing device. The New Asus ZenBook 14 offers all of the mentioned traits and more, courtesy of an improved design and better processing power.

The performance is top-notch with the 10th gen Intel Core i7-10510U processor on-board. The existing SoC can turbo clock at speeds of up to 4.9GHz. Despite this being a sleek device; no power-centric compromises are made with Asus packing in the improved NVidia GeForce MX 250 GPU with 2GB VRAM support.

In terms of memory allocation, the 16GB RAM minimizes data mining and document creation time. Besides that, the 512GB PCIe SSD storage unit is fast and renders data quicker as compared to the SATA3 module. Windows 10 Pro edition is the pre-existing OS but the device supports Linux Ubuntu installation.

Asus features the Nano-Edge display technology and the 14-inch screen flaunts a display resolution of 1920×1080 pixels. The Full HD panel also boasts of  the178-degree, wide-view technology, and sharpest possible viewing angles. This device also flaunts a 92 percent display-to-body ratio and thrives on the 2.9mm ultra-thin bezels for a better visual experience.

In terms of keyboard productivity, Asus brings forth a backlit interface, followed by a 1.4mm key travel and quicker access keys. You also get an intelligent touchpad that flaunts the ScreenPad 2.0 technology with a touch interface and one-tap access to a host of processes. This ScreenPad offers instant app switching access, especially for data scientists who are always on the clock.

The new Asus ZenBook 14 flaunts an ultralight chassis, weighing a mere 1.26kgs. Moreover, this is one sleek device that measures 16.9mm and almost 13 percent slimmer as compared to the preceding model. Other physical enhancements include an optimal typing position, an enhanced set of speakers, and an advanced cooling system. In terms of port management, you get USB Type-C, USB 3.1, and a host of other outputs.

Asus features Gigabit Wi-Fi 6 and advanced Bluetooth connectivity for enabling data scientists to work with remote servers. Besides that, data science professionals can go on for almost 12 hours on battery, without requiring a recharge. Overall, the new Asus ZenBook 14 is a powerful device that excels in the processing department.

Pros
  • Excellent 10th gen processor
  • Brilliant nano edge bezel display
  • Excellent design and aesthetic elements
  • Powerful and long-lasting battery
Cons
  • Storage could have been better
  • Not apt for Neural Networking

7. Best For Data Mining: Lenovo ThinkPad P53s

  • CPU: 1.8GHz Intel Core i7-8565U
  • RAM: 16GB
  • GPU: 2GB NVidia Quadro P520
  • Storage: 512GB SSD
  • Display: 15.6-inch FHD LCD (1920 x 1080)
  • Battery: Up to 8 hours

Here is a new and improved Ultrabook from Lenovo that is a perfect fit for the data visualization and data mining experts, courtesy of the portable design elements, class-leading processing power, and a decent enough display.

To start with, the Lenovo ThinkPad P53s boasts of excellent processing performances with the powerful Intel Core i7-8565U processor at the helm. The SoC is further complemented by the NVidia Quadro P520 GPU and 2GB of existing VRAM memory. Despite having similar architecture to the GeForce GPUs, the Quadro units have more memory and are better suited towards handling professional, data-centric requirements.

In terms of memory, this gadget features 16 gigs of RAM which works well with the existing processor and the workstation-centric GPU. The 512GB SSD storage unit renders data faster than an HDD and also plays a major role in speeding up the boot-up time. Although you get Windows 10 as the featured OS, Lenovo also allows you to install Linux, based on preferences.

Although the display isn’t a deal-breaker when data analysis and mining requirements are concerned, the Lenovo ThinkPad P53s still perform satisfactorily courtesy of the 15.6-inch Full HD panel. The existing display resolution of 1920×1080 pixels results in exceptional color reproduction.

Data scientists prefer the ergonomic, backlit keyboard, and the responsive ClickPad on display. There is a fingerprint sensor integrated with the same, precisely to protect the existing data sets and prototypes. This gadget weighs around 4 pounds and is still pretty sleek for a full-fledged mobile workstation. In terms of port diversification, the gadget packs in Type-C and a couple of USB 3.1 slots.

Other handy specs for added productivity include stereo speakers, HD webcam, and exceptional Wireless connectivity. The existing battery offers a decent backup of up to 8 hours, depending on the usage. To be exact, the Lenovo ThinkPad P53s isn’t a fancy gadget but achieves perfection, owing to the powerful processor and the functional Quadro graphics unit.

Pros
  • Powerful GPU for professional usage
  • Decent display
  • Responsive touchpad and keyboard
  • Sizeable storage unit
Cons
  • Inadequate battery for professionals who are always on the move
  • Predictable design

8. Best with Touch Screen: HP Envy 17T

  • CPU: 1.8GHz Intel Core i7-1065G7
  • RAM: 16GB
  • GPU: 4GB NVidia GeForce MX250
  • Storage: 256GB SSD + 1TB HDD
  • Display: 17.3-inch FHD IPS Touch (1920 x 1080)
  • Battery: Up to 10 hours

Although a data scientist wouldn’t worry about touch support on a powerful laptop, the new HP Envy 17T is worth investing in, courtesy of its sleek aesthetics and a powerful processing conglomerate.

This gadget packs in the 10th gen, Intel Core i7-1065G7 processor that boasts of excellent performances and works in cohesion with the NVidia GeForce MX250 GPU. The existing GPU outperforms a GTX contemporary by almost 7 percent and makes it possible for you to indulge in neural networking and other deep learning activities. The 4 gigs of VRAM support further accentuate the graphics performance.

HP also brings forth 16 gigs of RAM that is capable of handling statistical operations with ease. What stands out is the dual-storage unit with a 256GB of SSD storage support and a 1TB hard disk. While the SSD unit is best suited towards speeding up boot-ups and data rendering, the hard disk works as the main data repository. Windows 10 is the existing operating platform, featured right out of the box.

The 17.3-inch screen is an exceptional addition, followed by the existing display resolution of 1920 x 1080 pixels. The IPS panel is extremely vibrant and boasts of multi-touch support.

The gadget also brings forth a backlit, island-style keyboard followed by a highly intuitive touchpad. Besides that, you also get FHD webcam with dual-array support for microphones. The new and improved Envy 17t also flaunts an aluminum chassis which is sleek and feathery at the same time. In terms of port management, HP packs in USB Type-C and all the other necessary and productive slots.

This touch-supported notebook packs in a powerful battery module, offering up to 10 hours of extended backup. Overall, this notebook is packed with decent processing power but doesn’t let down in terms of aesthetics and design elements.

Pros
  • Excellent display
  • Powerful processing components
  • Sleek and stunning design
  • Performance-oriented GPU
Cons
  • HP could have packed a bigger battery
  • Underperforming speakers

9. Best For Students: Acer Swift 3

  • CPU: 1.8GHz Intel Core i7-8565U
  • RAM: 8GB
  • GPU: 2GB NVidia GeForce MX150
  • Storage: 256GB SSD
  • Display: 14-inch FHD IPS (1920 x 1080)
  • Battery: Up to 12 Hours

If you are a budding data scientist who is looking to explore the caveats of data visualization, mining, and prototyping, the Acer Swift 3 is the perfect laptop to invest in.

This device cuts additional clutter and concentrates purely on the performance. The 8th gen Intel Core i7-8565U chipset is a force to reckon with, courtesy of a turbo clocking speed that can go up to 4.6GHz. Most importantly, despite flaunting an affordable price tag, it still packs in an NVIDIA GeForce MX 150 unit that can support up to 2 gigs of VRAM.

The dual-channel RAM support of 8GB makes way for decent performances, allowing you to handle basic statistical tasks, CRM alignment, and data visualization with ease. The 256GB SSD storage unit is extremely efficient and supports the quickest possible boot-ups. Acer features Windows 10 Home edition, straight out of the closet.

Acer features a 14-inch Full HD screen, offering exceptional levels of clarity and sharpest possible viewing angles. Overall display resolution for the same is 1920 x 1080 pixels which also makes way excellent visual quality.

You also get a standard backlit keyboard clubbed with an exceptional and responsive touchpad. Besides that, you also get access to excellent connectivity features in Gigabit Wi-Fi and Bluetooth 5.0, making way for seamless remote server applications. Other specs include built-in stereo speakers, HD webcam, resourceful microphone array, and a fingerprint scanner.

The new Acer Swift 3 boasts of exceptional levels of craftsmanship and flaunts a pretty sleek, unibody chassis. The gadget weighs a mere 2.97 pounds and features a host of productive ports, including Type-C and USB 3.0 slot. This gadget allows you to go on for almost 12 hours without requiring a recharge.

Overall, this is an excellent device featuring a powerful battery and a decent set of processing components. Most importantly, the company also boasts of competitive pricing.

Pros
  • Powerful processor
  • Enthralling display
  • Long-lasting battery
  • Light-weighted device
Cons
  • Underwhelming graphics support

10. Best 2-in-1: Lenovo Yoga 730

  • CPU: 1.6GHz Intel Core i5-8265U
  • RAM: 12GB
  • GPU: Intel Integrated UHD 620
  • Storage: 256GB SSD
  • Display: 15.6-inch FHD Touch (1920 x 1080)
  • Battery: Up to 8 Hours

The new Lenovo Yoga 730 is probably the best 2-in-1 laptop in the market for aspiring data science students and professionals. Besides featuring an extensive specs-sheet, this laptop is best known for the multimode functionality and competitive pricing.

In terms of processing power, Lenovo brings forth a decent yet powerful Intel Core i5-8265U chipset. Although the processor is capable of handling basic data processing and analytical requirements with ease, the Intel UHD 620 integrated graphics card further enhances the performance.

The Yoga 730 also features 12 gigs of RAM and a sizeable 256GB SSD storage unit. While the data storage capacity might seem a bit underwhelming for hardcore professionals, the PCIe unit is extremely fast and renders data in the quickest possible manner. You also get Windows 10 as the preexisting operating system.

The 15.6-inch touch screen offers a display resolution of 1920 x 1080 pixels. Besides that, Lenovo also boasts of sharper viewing angles and unmatched visual clarity.

If you are a student, the ergonomic and backlit keyboard is expected to serve you well. Besides that, the responsive trackpad is smooth and extremely efficient. Other specs include an HD webcam, built-in microphone, and exceptional Wireless connectivity.

What stands out is the unmatched portability courtesy of the 360-degree, convertible chassis! Lenovo Yoga 730 weighs 4.20 pounds and is also known for multi-mode usage as you can align the device based on the preferred form factor. Moreover, this gadget is easy to carry around courtesy of the enviable slimness at 0.7-inch. This device also features a thunderbolt port and other productive slots for pairing external gadgets and data repositories for better analysis.

Lenovo features a decent battery unit that supports up to 8 hours of continuous usage. To sum things up, Yoga 730 is a pretty efficient device that is sleek, portable, and capable of being used as a portable workstation by the aspiring data scientists.

Pros
  • Exceptional design and form factors
  • Enthralling display
  • Decent processing power for the given price point
  • Extremely portable device
Cons
  • Inadequate battery backup
  • Low storage space for seasoned data scientists

11. Best Value For Remote Server Access: Apple MacBook Pro 13

  • CPU: 1.4GHz 8th Gen Intel Core i5
  • RAM: 8GB
  • GPU: Intel Iris Plus 645
  • Storage: 512GB SSD
  • Display: 13.3-inch (2560 x 1600)
  • Battery: Up to 10 hours

If you are looking for a dependable yet mid-range device for data processing, the 13-inch MacBook Pro is the perfect device to work with. However, this laptop is best suited for aspiring data scientists as professionals might find this a bit underwhelming.

The Intel Core i5 processor is a decent addition, capable of clocking at almost 3.9GHz. The 64-Bit SoC processes data twice as fast as compared to any other 32-bit system. The Integrated Iris Plus 645 GPU also performs well but doesn’t render exceptional graphics-intensive data modeling capabilities to the system.

This gadget offers 8 gigs of RAM which is quite handy as intricate data processing takes place in the memory. Therefore, this MacBook is a good choice for basic professional ventures where the processed data doesn’t exceed the feature RAM. You also get a 512GB SSD unit which renders data at least 40 times faster in comparison to the conventional HDD. This device runs Mac OS X but supports Windows installation via the boot camp functionality.

In terms of display, you get the vibrant 13.3-inch screen with retina display technology and a cumulative display resolution of 2560 x 1600 pixels.

Apple simplifies professional and academic indulgence with the integrated Magic Keyboard, featuring backlit support, inverted arrow keys, one-touch Escape key, and a 1mm key travel. Besides that, the Force trackpad is a decent addition followed by the innovative touch bar and the secured Touch ID.

The 13-inch MacBook Pro is made of aluminum and comes across as an extremely sleek device at a mere 15.6mm. The device weighs a mere 3.1lbs and features a host of productive ports in two USB Type-C slots and more. In the case of electric outages, Apple allows you to continue the work with a 10-hour battery backup. It is an exceptional device that is almost perfect for a data science student and even an aspiring professional.

However, if you prefer the aesthetic layout of the MacBook Air, you can always opt for the new model that also features 8 gigs of RAM and a 13.3-inch display. This gadget brings forth a 10th gen processor and offers 12 hours of battery backup. The MacBook Air is obviously lighter and also offers 4MB of cache memory which is an asset for the data scientists.

Pros
  • Exceptional display
  • A decent set of processing elements
  • Powerful battery
  • Exceptional keyboard and touchpad with integrated Touch ID
Cons
  • Underpowered graphics card
  • Lesser RAM

12. Best with Intel Core i5 and 8GB RAM: Lenovo IdeaPad L340

  • CPU: 2.4GHz Intel Core i5-9300H
  • RAM: 8GB
  • GPU: 4GB NVidia GeForce GTX 1650
  • Storage: 512GB SSD
  • Display: 15.6-inch FHD IPS (1920 x 1080)
  • Battery: Up to 9 hours

The new Lenovo IdeaPad L340 is a pretty efficient device if you are looking to run basic Data visualization applications like Tableau sans any lags. Besides that, this gadget also supports basic levels of neural networking, thereby helping you address the deep learning requirements with ease.

The existing 9th Gen Intel Core i5-9300H processor is a commendable addition and capable of reaching decent levels of turbo clocking speeds. You also get to experience the power of the dedicated NVidia GeForce GTX 1650 GPU that works in cohesion with 4 gigs of VRAM.

The memory-centric requirement is handled by 8GB of built-in RAM that amplifies the potency of the supplied SoC. Lenovo also offers a 512GB solid-state storage drive which renders data faster than usual and even minimizes the boot-up time. You also get the Windows 10 OS albeit with support for Linux installation via dual boot mechanism.

The 15.6-inch Full HD display is pretty standard for the existing price tag. The company offers a 1080p panel that also supports the Vantage ‘Eye Care’ mode for helping students and professionals continue data churning without straining the eye.

Besides featuring a backlit keyboard and a responsive touchpad, this device also packs in a host of innovative features. These include an HD webcam with dedicated shutter, speakers with Dolby Audio support, and diverse gaming and working modes. This is also a durable clamshell model that weighs less than 5 pounds and comes with a 180-degree movable hinge.

In terms of port management, Lenovo persists with the USB Type-C and other functional outputs. Up to 9 hours of battery backup is also a decent addition for the aspiring data scientists. Overall, this device from Lenovo is strictly a mid-range model that is perfect for beginners looking for decent graphics support and commendable battery support.

Pros
  • Excellent processing setup with exceptional graphics
  • Commendable storage capacity 
  • Exceptional display
  • Inclusion of utilitarian features like speakers, webcam, and more
  • Powerful battery
Cons
  • Underwhelming RAM support
  • Basic and monotonous design

Frequently Asked Questions

Why should you consider the MacBook as a Data Scientist?

OS X or the macOS is inherently built on the UNIX platform which makes it better equipped towards handling demanding software sets and applications. Therefore, some of the more intricate tools for data prototyping, testing, and visualization work the best on MacBooks. Some of these include the Power Query and the Power Pivot that rely on dataset sharing.

Why a Multi-Core Processor is required for better data processing?

Most data processing tools like Python and R use all the available cores for processing data in the best possible manner, despite being single-threaded. Moreover, the likes of R.Data Table are multi-threaded in nature and require high-end processors to work in the desired manner.

Are Gaming laptops sufficient for Data Scientists?

The processing power of the device for a data scientist actually depends on the tasks he or she is looking to indulge in. For instance, if you are interested in building simple data models using the likes of statistical libraries like Keras and Tensorflow, a decent chunk of RAM is the only requirement, provided the device already shelters a powerful processor.

What is the role of GPU for a Data Scientist?

A powerful GPU is necessary only if the data scientist is looking to work with deep learning tools. Besides that, high-end GPUs are necessary if GPU-Modeling and neural networking are concerned.

What are the most important aspects to look for in a laptop for a professional data scientist?

To start with, a professional would first require loads of RAM, as datasets are directly processed into the memory and once the size exceeds the RAM, processing slows down. The next requirement is a sizeable SSD storage, precisely to lower the access time. Processor speed, including the base and turbo clocking frequencies, is necessary to consider, especially when working on the Azure Platform is concerned.

Verdict

Data scientists are highly innovative professionals with high-end data processing requirements. Unless the data scientist always users a remote server to get the job done, a powerful laptop will continue to be a requirement.

If you are a seasoned professional who is only looking for storage, RAM, and processing speeds can go for the ROG Strix Scar III or the Blade Pro 17 from Razer. These gadgets also come in handy if you are looking to use the concept of GPU acceleration for neural networking.

If you are strictly looking for a MacBook, nothing beats the efficacy of the new MacBook Pro 16. However, if you are a student or an aspiring professional with not-so intricate requirements, the Lenovo Yoga 730 is a decent enough device.

In the end, it all comes down to the criticality of your job and the nature of tools that you would be using for data visualization, data scripting, database management, and establishing connections with the data server.

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