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12 Best Laptops For Data Science And Data Analysis 2023

If you’re a data scientist looking for the ideal laptop for your work, knowing which laptops best suit your needs would be helpful. 

You have several options, but which data science laptop meets your needs and requirements? It could take hours to read through information and reviews. Data science laptop requirements include: 

  • A responsive operating system. 
  • A fast central processing unit. 
  • Sufficient storage for balanced performance with diverse data types and insights. 

You can complete your assignments on a laptop if you are a data science student. 

Data scientists need computers with excellent memory and processing power to perform their duties effectively. Finding a laptop suitable for data science is problematic because it requires hours of research, including reading reviews and examining the characteristics of each model. 

It’s time to replace your outdated laptop with one of the data science laptops listed in this article. 

Our Top Picks

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12 Best Laptops For Data Science And Data Analysis 2023

Data science is currently a challenging career option. Regardless of your experience with data science, you should seek out laptops designed specifically to facilitate your work. The following laptops have proven their dependability and will satisfy your inner data scientist: 

1. Best Overall Laptop for Data Science: Lenovo Legion 5 Pro

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The Lenovo Legion 5 Pro is an underappreciated powerful PC laptop. Its AMD Ryzen 7 CPU, and NVIDIA 3060 GPU make it uncommon in the $1,500 price bracket. Its 16-inch screen size makes it portable without sacrificing resolution (2,560 by 1,600 pixels) or refresh rate (165Hz). I recommend this Lenovo if you’re looking for a durable, upgradable laptop that can handle data science work at a reasonable price. In addition, Lenovo’s customer service is satisfactory, which cannot be said of many other brands. 

The Legion 5 Pro is a hard-copy version of the IdeaPad i3 with enhanced performance and image quality. It inherits a user-friendly port system, and support from Lenovo is typically excellent. It is a step up from the Acer Nitro 5 but comes with a price increase of approximately $230, making it a good option for data scientists who have graduated from the beginner phase. 

Specifications 
  • Screen Size: 16 inch 
  • Screen Refresh Speed: 165 Hz 
  • Screen Resolution: 2560×1600 
  • Operating System: Windows 11 
  • Hard Disk Drive/Storage/SSD: 1TB 
  • RAM: 16GB 
PROS
  • Excellent screen
  • Very good performance
  • User-upgradable RAM and storage
  • Excellent hardware controls
  • Decent value for money
CONS
  • Middling battery life for a Zen 3 CPU
  • Fairly heavy at 5.4 pounds
  • Poor mic and speakers
  • 720p webcam
  • Runs noticeably hot

2. Most Powerful Laptop for AI & ML: Razer Blade 17 Gaming Laptop

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The Razer Blade 17 is the best machine on our list if cost is no object. The specifications are 144Hz refresh and 25601440 resolution, 1TB storage, a 12th Gen i7 processor, and an NVIDIA 3070 Ti PLUS coprocessor. The only way to improve this machine is to add more storage and install an i9 processor, but you won’t need to. 

The most powerful computer on our list is the Razer Blade 17. It can easily handle even the most complex programming involving evolutionary programming, fuzzy logic, artificial intelligence, and machine learning. And with a resolution of 25601440 and a refresh rate of 144Hz, the hardware can fully leverage NVIDIA’s 3070 Ti GPU, delivering stunning image quality. 

Specifications 
  • Screen Size: 17.3 inch 
  • Screen Refresh Speed: 144Hz 
  • Screen Resolution: ‎2560×1440 
  • Operating System: Windows 11 
  • Hard Disk Drive/Storage/SSD: 1TB 
  • RAM: 16GB 
PROS
  • Slim, premium chassis
  • Solid overall and gaming performance
  • Accessible 2x M.2 2280 and 2x SODIMM
  • Plenty of ports
  • Improved keyboard layout and excellent trackpad
  • Extremely fast 300 Hz refresh rate
  • IPS display
  • Loud, well-placed speakers
CONS
  • High price
  • Tends to run hot
  • Loud fans when gaming
  • Low storage on all but top configuration
  • 70Wh battery and short battery-life
  • No Optimus or G-Sync

3. Best Data Science Laptop for Graphics: Dell XPS 17

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The touchscreen technology on the Dell XPS17 requires some adjustment, but scrolling is more accessible, and overall screen interaction has been enhanced. The XPS17 has by far the highest image quality on our list. This one is ideal for data scientists who work long hours but do not need to host their databases or servers (freelancers are not recommended).  

If you want the best display quality and interactivity, the XPS17 from Dell is the right computer. Powered by an NVIDIA 3050 graphics processing unit, its large 17-inch 4k ultra-HD screen with 3840 x 2400 resolution produces unrivaled image quality. 

Additionally, it is touchscreen. Consider this machine if image quality is your priority and you are willing to sacrifice performance. Ensure that you purchase this one with 1TB SSD and Windows 10 (Windows 11 performs less well). 

Specifications 
  • Screen Size: 17 inches 
  • Screen Refresh Speed: 120Hz 
  • Screen Resolution: 3840×2400 
  • Operating System: Windows 10 (avoid Windows 11) 
  • Hard Disk Drive/Storage/SSD: 1TB 
  • RAM: 32GB 
PROS
  • Sleek aluminum chassis with diamond cut edges
  • 17-inch UHD+ display in 15-inch form factor
  • Core i9 8-core and GeForce RTX performance
  • Four Thunderbolt 3 ports and SD card reader
  • Keyboard and touchpad are excellent
  • Surprisingly small
  • Excellent audio quality
CONS
  • Undeniably pricey as configured
  • Some may miss USB-A ports
  • Occasional coil whine
  • Even when plugged in, slight power drain during intense gaming sessions
  • Bad webcam

4. Most Cost-Effective Laptop for Data Science: HP Pavilion Gaming Laptop

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I recommend the HP Pavilion to beginners in the discovery phase of data science. However, I don’t recommend it to professionals who want a home computer for practice. At roughly $860, the HP Pavilion is our budget-friendly pick on the list.  

This laptop may be the best option if you intend to work primarily in an office with limited local storage and host only partial local data. Just note that you may need an upgrade. Even essential laptops use the i7 processor because the i5 is too weak to handle big data. If you are a beginner and want to dip your toes into data science, I recommend the HP Pavilion if you spend less than a few hundred dollars on the Acer Nitro 5. 

Specifications 
  • Screen Size: 15.6 inch 
  • Screen Refresh Speed: 60 Hz 
  • Screen Resolution: 1920×1080 
  • Operating System: Windows 10 
  • Hard Disk Drive/Storage/SSD: 512GB 
  • RAM: 12GB 
PROS
  • Fast AMD CPUs and powerful
  • NVIDIA dedicated graphics.
  • Very little throttling over time.
  • Upgradeable RAM and 2.5 inch drive slot.
CONS
  • Gets hot and loud under load.

5. HP Envy 17T

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HP is a well-known laptop and electronic device manufacturer. The HP Envy 17T is quite robust and packed with features. This laptop is ideal for any mathematical or data-science study or project. Due to its 10th Generation Intel i7-1065G7 processor, it is a powerful performer. 

The HP Envy 17T is a laptop designed to meet your data science requirements. Windows 11 Home is installed, and the 17.3-inch Full HD IPS display is IPS. In addition, the laptop has 16 GB of RAM and 1 TB of SSD storage space. It possesses exceptional multitasking and high-performance processing capabilities. 

Specifications 
  • Display: 17-inch, 3840×2160 IPS non-touch display 
  • CPU: Intel Core i7-1065G7 CPU 
  • Memory: 16 GB DDR4-3200 RAM 
  • GPU: Nvidia GeForce MX330 GPU with 2 GB VRAM 
  • Storage: 512 GB PCIe NVMe solid state drive 
PROS
  • Plenty of ports
  • Decent graphics performance
  • Voluminous audio
  • Minimalist styling
  • Comfortable keyboard
  • Available 4K screen
  • Automatic webcam privacy door
CONS
  • Lacks Thunderbolt 3
  • Very heavy
  • Poorly constructed touchpad
  • Expensive as configured
  • USB-C charger not included

6. Apple MacBook Pro

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Apple’s MacBook Pro is ideal for data processing due to its powerful processor and ample storage space. In addition, it is portable and lightweight, making it a perfect option for data scientists who travel frequently. 

The Touch Bar, a Multi-Touch-enabled strip of glass integrated into the keyboard, provides quick access to the required applications. 

The 13.3-inch Apple MacBook Pro with Retina Display is an excellent option for data scientists. It features an efficient Apple M1 Chip, a CPU with eight cores, and an exclusive AMD GPU with eight cores. With this configuration, you can efficiently manage massive data sets and execute complex algorithms. 

Specifications 
  • Screen Size: 14.2 inch 
  • Screen Refresh Speed: 120 Hz 
  • Screen Resolution: 3024×1964 
  • Operating System: macOS 
  • Hard Disk Drive/Storage/SSD: 1TB 
  • RAM: 16GB (64GB unified memory) 
PROS
  • Much-improved keyboard
  • Apple doubled the base storage
  • Four Thunderbolt 3 ports
  • Excellent battery life
  • Good graphics and computing performance
CONS
  • You have to buy at least the $1799 model to get 10th-gen Intel processors
  • Low-quality camera
  • Limited port variety
  • No support for Wi-Fi 6

7. ASUS VivoBook 15

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The ASUS VivoBook 15 is the best laptop for data scientists because of its powerful CPU, GPU, RAM, storage options, and long battery life. 

The Radeon graphics card provides exceptional support when analyzing data sets or creating presentations. At the same time, the Ryzen processor will allow you to complete all your data science projects efficiently. For data science, an Asus laptop is the best option. 

Specifications 
  • PROCESSOR: AMD Ryzen™ 7 5700U Processor 
  • DISPLAY: 15.6” FHD (1920 x 1080) OLED 
  • MEMORY: 8GB DDR4 on board 
  • STORAGE: 512GB M.2 NVMe™ PCIe® 3.0 SSD 
  • GPU: AMD Radeon™ Graphics 
  • OS: Windows 10 Home 
PROS
  • Slim and Lightweight.
  • Decent display panel.
  • Good performance.
  • Pricing.
CONS
  • No backlite keyboard. No indicator for Caps Lock.
  • Audio output could have been better.

8. ASUS ROG Strix G17

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The ASUS ROG Strix G17 is a data science-oriented gaming laptop. It has ample storage space, a powerful processor to execute any machine learning algorithm, and a respectable battery life. 

If your laptop has an AMD Ryzen 7 4800H 8-Core processor, its performance will undoubtedly be superior to that of laptops with Intel Core i7 processors. 

Specifications 
  • AMD Ryzen™ 7 6800H Processor 
  • 16GB DDR5-4800 SO-DIMM (2×8) 
  • 512GB PCIe® 4.0 NVMe™ M.2 SSD 
  • NVIDIA® GeForce RTX™ 3060 GPU 6GB GDDR6 
  • 17.3″ FHD (1920 x 1080)16:9/ Anti-glare  100.00% sRGB 
  • 360Hz 3ms IPS/ MUX Switch + Optimus HDR 
  • Windows 11 Home 
PROS
  • smaller, lighter and cleaner looking than before
  • friendlier materials than on the Scar 17
  • competent 300 Hz IPS screen option
  • good inputs
  • powerful hardware and solid performance across the board
  • quiet on Turbo, at sub-45 dB at head-level
  • 90W battery and long battery life
  • good value for what it is
CONS
  • no card-reader, Thunderbolt, camera or biometrics
  • the F1-F12 writting on the keys is not backlit
  • panel-lit ROG logo on the lid, can't be swtiched off
  • still high CPU/GPU temperatures with games and demanding loads (can be addressed on Manual)
  • no MUX switch, with an impact on the gaming experience

9. Lenovo Thinkpad P53s

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The renowned Lenovo Thinkpad laptop with the P53S has an excellent layout and is ideal for typing for extended periods. It is also one of the best laptops for data science on a budget. It has a more refined appearance and a more robust design. The P53S has exceptional battery life. 13 hours for everyday Internet use and more than 10 hours for a workstation are excellent. 

Specifications 
  • CPU: 8th Gen Intel Core i7 8565U  
  • RAM: 16GB of RAM  
  • Storage: 512GB SSD  
  • GPU: Nvidia Quadro P520 2 GB VRAM  
  • Display: 15.6 Inch | FHD (1920 x 1080)  
PROS
  • Light and robust design
  • Wide I/O connectivity options
  • Great battery life
  • Flourishing with security features
  • It has optional Thunderbolt support and LTE connectivity
  • Sufficient cooling
  • Doesn’t use PWM to adjust brightness levels (AUO B156HAN02.1)
CONS
  • Its price is a little on the high side
  • Not exactly a powerhouse of a hardware
  • Covers only 52% of sRGB (AUO B156HAN02.1)

10. Dell G15

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This laptop is exceptional due to its attractive design and data science-capable hardware. This is the best option for someone who must simultaneously work on multiple datasets without experiencing latency or stuttering because it is durable, stylish, and portable. 

The Dell G15’s incredible display and refresh rate of up to 165Hz enable you to run multiple applications concurrently without experiencing performance issues. Additionally, it has 16GB of DDR4 RAM. 

Specifications 
  • Processor: 12th Gen Intel® Core™ i5-12500H (18 MB cache, 12 cores, 16 threads, up to 4.50 GHz Turbo) 
  • Operating System: Windows 11 Home, English 
  • Graphics Card: NVIDIA® GeForce RTX™ 3050, 4 GB GDDR6 
  • Display: 15.6″, FHD 1920 x 1080, 120Hz, WVA, Non-Touch, Anti-Glare, 250 nit, Narrow Border, LED-Backlit 
  • Memory *: 8GB, 1x8GB, DDR5, 4800MHz 
  • Hard Drive: 256 GB, M.2, PCIe, SSD 
PROS
  • Stylish, premium design
  • Long battery life
  • Good graphics performance
  • Matte, contrast-rich IPS display
  • Full HD resolution
  • Thunderbolt 3
  • Big I/O selection
CONS
  • Thick and heavy chassis
  • Slow SSD
  • Only 12 months of warranty
  • Gets loud under stress
  • Covers only 52% of sRGB

11. Acer Swift 3

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The Acer Swift 3 is an excellent option for data science due to its large storage capacity and powerful graphics processing engine. With 1 TB of storage, you can save all your data sets and models effortlessly. 

With an NVIDIA GTX 1050 Ti GPU, you can easily and quickly run complex models and algorithms. The Acer Swift 3 is an excellent choice if you need a robust and versatile laptop for data science. 

Specifications 
  • Windows 10 Home 64-bit. 
  • Intel® Core™ i3-1115G4 processor Dual-core 3 GHz. 
  • Intel® UHD Graphics shared memory. 
  • 35.6 cm (14″) Full HD (1920 x 1080) 16:9 IPS. 
  • 8 GB, LPDDR4X. 
  • 256 GB SSD. 
PROS
  • Ultra-lightweight
  • 3:2 display is very useful
  • Ice Lake CPUs
  • Covers 98% sRGB (BOE08BC)
  • USB-C with support for DisplayPort
  • Enormous Precision touchpad
  • Backlit keyboard
  • Fast NVMe SSD
  • Wi-Fi 6
  • Good system performance
CONS
  • No SD card reader
  • RAM not upgradeable
  • Display with low PWM frequency
  • Aspect ratio scaling on some apps
  • Intel "Ice Lake" CPUs outpaced by Ryzen 4000
  • Glossy display despite no touch

12. HP EliteBook

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The HP EliteBook features 8th Generation Intel Core processors for the best SAS or ggplot2 performance and is incredibly thin and light. The display’s high brightness and anti-glare properties allow a seamless transition from a dim boardroom to the bright sun. 

With up to 32GB of DDR4 RAM, you can efficiently process massive amounts of data. In addition, you won’t need to consider using external storage because you have access to two 2TB SSDs that provide lightning-fast work speeds. 

Specifications 
  • Display. Size. 14.00-inch. 
  • Processor. Processor. Intel Core i5. 
  • Memory. RAM. 8GB. 
  • Storage. Hard disk. 256GB. SSD. No. 
  • Connectivity. Wi-Fi standards supported. 802.11 a/b/g. 
PROS
  • Well-crafted, business-rugged construction, Nice keyboard
  • Second-gen Core i-series processor; excellent battery life; HP QuickWeb and ProtectTools
  • Good control over security and power, Matte LCD screen is pleasing
  • The sturdy HP EliteBook can be configured with a battery life of up to 32 hours
CONS
  • No HDMI or WiDi, A bit bulky and heavy for a 14-inch laptop
  • Heavy; bulky design
  • Industrial design is a little clunky, Speaker quality is terrible
  • This model does not include the 10button numeric keypad

Laptop Requirements for Data Science

A data scientist must be able to collect, analyze, and comprehend vast quantities of data. We offer the best Data Science certification online. To manage such a vast amount of data, you need a laptop that can operate efficiently and handle all your computing needs. With the proper equipment, you can complete your projects quickly and efficiently, focusing solely on your work rather than battling PC performance issues. To have seamless computing experience in data science, you must remember a few basic laptop configurations. You must carefully examine the specifications to choose the most suitable laptop for data science. 

Must-Have Laptop Specifications for Data Science 

You must choose a machine with sufficient processing power because the more data you manage, the more robust hardware you require. Here are the features that the best laptops for data science should possess: 

A Suitable CPU

Learning in an online Data Science Bootcamp and working as an expert will necessitate the use of various tools, and a suitable processor will provide the computational power necessary to manage massive data sets. It would help if you chose the proper CPU because not all processors are designed to handle the demands of data science. Depending on the number of data sets you manage, you need a processor with at least 4,2 GHz, 8 cores, and 16 threads. The recommended CPUs are the Intel Core i9-11950H and Intel Xeon W-11955M. You can select a CPU with 18 cores for increased performance or a 2x Intel Xeon processor with up to 56 cores. 

GPU

A good graphics processing unit (GPU) is essential for data scientists because it improves their ability to view data. A laptop with a powerful GPU can quickly and efficiently process large data sets, allowing you to gain insights more quickly. We recommend purchasing a laptop with a GeForce GTX 1070 or Radeon RX 580 graphics card for data science. 

RAM capacity

A larger RAM capacity makes multitasking possible. Therefore, when selecting RAM, opt for 8GB or more. The operating system consumes more than 60 to 70 percent of the recommended 4GB, leaving insufficient space for data science tasks. Choose 12 GB or 16 GB of RAM if you can afford it. 

Display

Most of a data scientist’s time is spent in front of a screen examining vast amounts of data. Therefore, you need a computer or laptop with an aesthetically pleasing display. Modern devices have screens with a high resolution, no flickering, and a blue light filter. By looking for this feature, you can select a screen that supports HD (720p), full HD (1080p), or even a higher resolution, such as 4k. 

Reliability

The frequency with which your laptop malfunctions while in use determines its dependability. The most common issues are unexpected shutdowns, blue screen errors, and other hardware malfunctions. 

Durability

Durability refers to how long you can use your laptop. By examining the length of the laptop’s warranty, you can deduce its durability. If you can use your laptop for at least four years, your money will not be wasted. 

Long-term Battery Life

Your device’s battery should be capable of lasting longer than eight hours, as you will be working longer hours. No one enjoys having to charge their electronic device multiple times per day. The ideal is a laptop with a battery life of at least 8 hours. 

Operating System (OS)

Windows 10 is recommended for data science students due to its intuitive interface and minimal configuration requirements. However, an alternative operating system, such as Linux, is also available. You can install it independently or use a virtual machine to run it. 

FAQs

Data science involves large datasets. Therefore, you’ll need a powerful laptop to run your projects smoothly. You’ll need a virtual OS with at least 8GB of RAM. You also need a powerful processor and GPU.

Yes, a laptop is ideal for data science. However, the laptop should have a powerful GPU and CPU. The Radeon RX 580 or GeForce GTX 1070 processor is ideal for data science.

The NVIDIA GEFORCE RTX 3090 Ti is the most powerful GPU for a data science laptop (not a desktop computer). However, the majority of data professionals will not require its capabilities. Our top-recommended GPU for notebooks is the NVIDIA GeForce RTX 3080, exclusive to the ASUS ROG Zephyrus on our list.

Windows 10 is the best operating system for a laptop used in data science. Early issues with Windows 11’s handling of high-performance operations will likely be resolved as updates are rolled out.
If you are part of the Apple ecosystem, macOS is your best option. This is the case for me, as all of my data is stored in the Apple cloud, and I simultaneously store all files on my computer and phone.

Newer Apple laptops (beginning in 2021) have increased processing and graphics power with their M1 units, making them excellent candidates for data science laptops, especially if you’re already a part of the Apple ecosystem and store data in the Apple cloud.

We recommend the 2021 MacBook Pro 14-inch. It will help if you steer clear of older models because they lack the processing power of Apple’s M1 CPU and M1 GPU. The MacBook Air’s small size may make it appealing, but it cannot perform advanced AI & ML, SQL, and visualization software such as Tableau and PowerBI functions.

Conclusion

Are they purchasing a laptop to satisfy Python requirements for Machine Learning? In that case, this is the proper location. In today’s world, data science is indispensable. Laptops and desktop computers are helpful in this situation. 

As a result of the development of data and analytics, analysts now require a laptop with adequate CPU power, speed, battery life, and other specifications. As a result, the best laptops for data science possess exceptional quality and performance. We hope to have assisted you in locating the ideal laptop for data science. 

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The above article was written by the BestTopReviewsOnline team, which consists of some of the most knowledgeable technical experts in the United States. Our team consists of highly regarded writers with vast experience in smartphones, computer components, technology apps, security, and photography, among other fields.

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