5 Best Desktops for Data Science 2023

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Best Desktops for Data Science

Mastering data science along with other factors what device you use is also vital. Here is a list of the best desktop computers you can use for data science.

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Minimum & Recommended System Requirements for Data Science

Best Desktops for Data Science

To perform tasks related to data science such as data analysis, statistics, and algorithms, you need a very efficient PC that can process data faster and can bring the desired results within a couple of seconds.

For this purpose, you need to choose a PC that has minimum 16 GB RAM, an Intel core i5 processor, and an SSD. But the professionals need to go with high-end processors to get more satisfactory performance.

Minimum System Requirements: Intel core i5 8250U | 16 GB | Intel UHD Graphics 620 | 500 GB SSD.

Recommended System Requirements: Intel Core i7-12700 or better processor | 32 GB RAM or more | NVIDIA GeForce RTX 3060 or a better GPU | 512 GB SSD and 1TB HDD or more.

5 Best Desktops for Data Science:

1. Acer Aspire TC-1760-UR12 Desktop – Overall Best

Acer Aspire TC-1760-UR12 Desktop

Bottom Line: To perform advanced-level data science projects, you can consider this Acer desktop. Top-notch processing and huge storage make it the overall best option for this purpose.

Key Features:

  • Storage: 512 GB SSD and 1 TB HDD
  • RAM: 16 GB
  • Processor: Intel Core i7-12700
  • GPU: Intel UHD Graphics 730
  • OS: Windows 11 Pro
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Being equipped with an advanced and powerful 12th Gen, 12 cores Intel i7 processor, this device can deliver very smooth and speedy processing.

To work on tasks related to data science, you need to access and process a lot of data.

Acer Aspire TC-1760-UR12 has the power to deliver smooth processing under any circumstances. 16 GB RAM, and 512 GB SSD, ensure that you can get a very satisfying processing speed.

Those who want more processing speed can upgrade the RAM capacity of the device. There is an inbuilt optical drive.

Dual-band Wi-Fi connectivity and Bluetooth 5.2 are present in it. There are a lot of useful ports, including an USB Type-C port.

Pros

  • Configurations are easily upgradable.
  • Updated port options.
  • Can attach multiple displays by using 2 HDMI ports.

Cons

  • No thunderbolt port.
  • Simple and backdated outfit.
  • The GPU section is not so strong.

2. Dell Inspiron 3910 Desktop – Runner up

Dell Inspiron 3910 Desktop

Bottom Line: This is a moderate-level Dell desktop and is packed with decent specifications. You can easily use it to do projects related to data science, and it is the perfect fit for our runner-up position.

Key Features:

  • Storage: 1 TB SSD
  • RAM: 32 GB
  • Processor: Intel Core i5-12400
  • GPU: Intel UHD Graphics
  • OS: Windows 11 Pro

You can consider this device to do any mid-range task related to data science. The Dell Inspiron 3910 is not a very expensive device.

At the same time, it has very decent specifications that help it to process any mid-range task smoothly and deliver the result very fast.

Intel Core i5-12400 is present on this desktop. It has a huge 32 GB RAM and an SSD of 1 TB.

These two help this device to process any task with lightning-fast speed. Inbuilt Wi-Fi and Bluetooth are present in it.

Besides that, Type-C port, USB 3.2 port, and a lot of ports and connectivity features are available in it.

Pros

Cons

  • No thunderbolt port.
  • Boring, simple, backdated chassis.
  • A Strong cooling section is missing from it.

3. Skytech Blaze II Gaming PC – Smooth Processing

Skytech Blaze II

Bottom Line: This gaming desktop has the power to deliver very smooth processing. The students of data science will be very satisfied with its smooth performance.

Key Features:

Although this is a gaming desktop, it can be used for most moderate-level tasks. Compared to other gaming desktops, it is less expensive.

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There is an AMD Ryzen 5 5600G processor, accompanied by 16 GB RAM and an SSD of 500 GB.

So it can deliver very smooth and powerful processing. Besides its powerful internal component, its outfit is also very classy.

There is a transparent side panel and RGB fan lights. Advanced inbuilt wireless connectivity feature, options to attach multiple display units, and useful updated USB ports are present in Skytech Blaze II.

Pros

  • Very impressive design.
  • RGB ring fans with lights.
  • Good GPU section.

Cons

  • No thunderbolt port.
  • No USB port on the front side of the chassis.
  • High maintenance cost.

4. Kingdel Mini Desktop – Value for Money

Kingdel Mini Desktop

Bottom Line: This compact mini PC comes with a very pocket-friendly price tag. It has a good processor and it can be used by those who are new in the data science field.

Key Features:

  • Hard Disk: 500 GB
  • RAM: 16 GB
  • Processor: Intel core i5 8250U
  • GPU: Intel UHD Graphics 620
  • OS: Windows 11 Pro

The next in the list for the best Desktop Computers for Data Science is the Kindel Mini Desktop Computer.

This desktop computer has been smartly designed that ensures that it is very compact and thus portable but at the same time ensures a high level of performance as well.

This Mini Desktop Computer is powered by the very powerful Intel i5- 8th Generation Processor that ensures that it generates high speeds that are usually required for processing the bulk data used in Data Science.

It also has a full metal case that makes this Mini Computer very sturdy indeed.

The Mini Computer has also been provided with the 16 GB DDR 4 RAM that is higher than the standard configuration and thus best suited for multiple computing jobs.

For storage, it has the 500 GB SSD that is the standard configuration. It has the Intel UHD Graphics 620 Graphics for providing realistic user experience.

The minicomputer can be connected over Wi-Fi. It has plenty of USB Ports and also ports for input devices.

So all in all, this Kingdel Mini Computer, given the highly advanced features offers great overall performance.

Pros

  • Lovely design
  • 8 generation processor
  • Good hardware

Cons

  • Little bit expensive
  • Ports issues
  • Support issues

5. Lenovo ThinkCentre M920s – Good Mainstream PC

Lenovo ThinkCentre M920s

Bottom Line: This is a good mainstream PC, that is easily upgradeable and one of the best options for students of data science. And they can experience smooth processing from it.

Key Features:

  • Hard Disk: 256 GB
  • RAM: 16 GB
  • Processor: AMD Ryzen 5 Pro 5650G
  • GPU: AMD Radeon
  • OS: Windows 10 Pro
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The last but definitely not the least in this category of desktop computers is the Lenovo ThinkCentre M920S.

Lenovo, as you would already know that, is a very reliable brand and so is this particular Lenovo Desktop Computer.

It has loaded with a host of the latest and the most advanced features for data science.

It is provided with the most powerful Intel Core i7 8700 Processor for fast speed.

It has the most advanced graphics in the form of the UHD Graphics 630 for the most realistic user experience as well.

This Lenovo Desktop computer has the 16 GB DDR4 RAM as well.

This is higher than the standard configuration of 4 GB and thus ideal for dealing with multiple computing jobs that are necessary for desktop computers handling data science.

This Desktop Computer from Lenovo has the SSD 512 GB for storage. This is a slight disappointment compared, especially if you are considering the other features.

You could thus consider an enhancement if you buy it. It has the Windows 10 operating system that boosts the overall performance of this desktop computer.

Considering all the features of this desktop computer you can definitely consider buying this computer if you are to use the same for your data science application.

Pros

  • Small design
  • Light weight
  • Good ports

Cons

  • Not available in the land stores
  • Hardware issue
  • Support issues

Questions & Answers:

What is the best desktop configuration for data science?

Hard Disk 2TB NVMe SSD + 1TB HDD, RAM 16 GB, Intel Core i7-8700 & Windows 10 Home is definitely good for the data science.

Why SSD storage recommended for data science computers?

SSD is good as it gives you proper security in storage.

How much RAM do you need for data science?

16 GB is good for data science project.

What is meant by data science?

This is a method which is involved with the scientific algorithm and other technical analysis of data base.

Conclusion

Get the best data science desktop for your lab so that you can do a perfect research. It is easy and effective from every direction.

You can get the best output from every angle of data functionality. In fact with all these information you can get the best desktop PC for data science.

About Dominic Chooper

AvatarDominic Chooper, an alumnus of Texas Tech University (TTU), possesses a profound expertise in the realm of computer hardware. Since his early childhood, Dominic has been singularly passionate about delving deep into the intricate details and inner workings of various computer systems. His journey in this field is marked by over 12 years of dedicated experience, which includes specialized skills in writing comprehensive reviews, conducting thorough testing of computer components, and engaging in extensive research related to computer technology. Despite his professional engagement with technology, Dominic maintains a distinctive disinterest in social media platforms, preferring to focus his energies on his primary passion of understanding and exploring the complexities of computer hardware.

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Dominic Chooper
Dominic Chooper, an alumnus of Texas Tech University (TTU), possesses a profound expertise in the realm of computer hardware. Since his early childhood, Dominic has been singularly passionate about delving deep into the intricate details and inner workings of various computer systems. His journey in this field is marked by over 12 years of dedicated experience, which includes specialized skills in writing comprehensive reviews, conducting thorough testing of computer components, and engaging in extensive research related to computer technology. Despite his professional engagement with technology, Dominic maintains a distinctive disinterest in social media platforms, preferring to focus his energies on his primary passion of understanding and exploring the complexities of computer hardware.
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