Is MacBook Air Good for Data Science? (2021 Review)

Choosing the right laptop for your schoolwork or at-home work is crucial. You could opt to purchase the most expensive and high-performance device, but you could end up spending extra money on unnecessary features and functions. The Macbook Air is a highly acclaimed laptop, but can it handle a data science student or professional’s needs?

The Macbook Air is a good laptop for data science tasks and applications. It contains an advanced Apple M1 chip for superb processing, a powerful GPU that can accelerate machine learning tasks, and a gorgeous Retina display. There are more powerful options, but the Macbook Air is a solid choice.

In this article, we’ll be examining the benefits and potential drawbacks of the Macbook Air. We’ll also be discussing data science and the features buyers should look for when choosing a laptop for data science work. Finally, we’ll find out if a Macbook Air is suitable for data science.

Apple MacBook Pro keyboard

Benefits of MacBook Air Laptops

The Macbook Air generally has positive reviews, and before we can determine how useful it might be for data science, we must first understand its most significant benefits. Some of the most notable advantages of the Macbook Air include the:

These features vary in their usefulness, depending on your needs and preferences. But quite a few of them stand out as outstanding features in the ideal data science laptop. However, that doesn’t mean that the Macbook Air is without its potential disadvantages.

Potential Drawbacks of MacBook Air Laptops

Before you head out to grab a Macbook Air, you might want to consider the potential drawbacks of this high-powered laptop. While this particular Apple product doesn’t seem to have many disadvantages, it’s vital to think about these negatives before making a final purchasing decision.

The Macbook Air has three primary drawbacks. Firstly, it doesn’t allow for standard upgrades. It only comes as an 8GB model as standard configuration, and while it’s configurable to a 16GB version, there’s not a lot of room for further improvement with an Apple laptop. 

Secondly, the Macbook Air is relatively pricey. You could purchase two budget-friendly laptops for the price of a single, lower-tier Macbook Air. Thirdly, the Macbook Air offers limited storage options. You can definitely upgrade to a higher storage capacity drive at the time of purchase, but that is going to hurt your wallet pretty hard.

What Is Data Science?

Data science is a broad term that incorporates many areas of study. As such, discussing what a data scientist does can quickly become complicated. In the briefest possible terms, data science is a way of rendering meaning from collected data. Data scientists employ many different methods and use many different tools to do this.

A data scientist is expected to have and access a massive internal toolbox that includes expertise in many fields and subjects, including:

They use the information they’ve learned on these subjects to gather data, prepare it, analyze it, and recommend a course of action to clients and internal stakeholders based on the information gleaned from the data. Data scientists are very similar to data analysts, but data scientists perform far more programming work than you would expect from analysts.

Individuals who’ve decided to become data scientists can expect to make an average annual salary of about $139,840. But they’ll need a high-performance computer to help them complete all of the necessary modeling, analysis, and programming work.

What Should You Look for in a Laptop for Data Science?

You may be somewhat familiar with computer terminology, but if you’re not completely clear on the standard component terms what they mean, now is the time to familiarize yourself. 

After all, it’s going to be tricky to find a laptop for data science if you’re not familiar with many of the most basic computer jargon. When you’re looking for a new computer to help you along with your data science learning or tasks, it’s crucial to consider your potential device’s:

While most online college courses won’t be too much of a drain, even on most advanced laptops and desktops, some programs can put a considerable load on the device’s processor. The machine learning aspect of data science could especially become problematic for those with older devices. 

The Macbook Air has an upgraded CPU that can execute 11 trillion operations each second. This jaw-dropping accomplishment is all thanks to the new Apple M1 chip, which is currently predicted to change the future of machine learning tasks.


Your smartphone, tablet, laptop, and desktop all contain a CPU. This acronym stands for central processing unit, which is physically a small square “chip” made of silicone and metal. 

It acts as the brain for your various electronic devices, sending and receiving electronic signals to make things function correctly. Gamers are already aware of how essential a device’s CPU is to satisfactory performance, but you might not be.

The older your CPU, the less likely it is to process information quickly. The rate at which our current technology is improving is almost outpacing our ability to manufacture, sell, and distribute it. A laptop from five years ago is nearly useless now and is likely to be entirely obsolete within the next five years. 

Even the most advanced home computers can suffer from this trend. It’s not your device’s fault, and it may be functioning correctly. But as file sizes, streaming speeds, and applications continue to grow more massive, our CPUs must also improve to keep up with the data load. 

Many areas of data science require the use of a powerful CPU. If you’re choosing a computer specifically for data science purposes, you’ll want to select one with a competitive CPU.


RAM is an acronym for random-access memory. This stuff is the temporary type of memory that is often called the computer’s short-term memory. It’s only available while the CPU is executing tasks. 

While you may be able to access a saved file after rebooting your computer, you’ll never be able to access the RAM used during a previous session. For this reason, RAM provides a boost in processing speed. The more cores and the more sizeable the RAM, the faster your applications will function, making it easier to complete data science tasks. 


The internal storage within a computer, tablet, or smartphone isn’t a suitcase-shaped area where files are stored away. At least, we can’t see it happening or physically touch the stored data in our devices. Without a hard drive, your laptop likely wouldn’t boot up and operate. 

It also wouldn’t be able to download or install complex applications, including machine learning software. The larger the hard drive space you can afford, the more use you can get from your laptop before needing to replace it. 


It feels lovely to watch a beloved film or television show on a crystal-clear display. But data scientists need high-resolution screens to allow them to read and process data. Data science is an involved career path. 

Data scientists will likely spend hours poring over thousands or hundreds of thousands of tiny bits of information. They need an excellent screen (and a helpful pair of computer-safe glasses) to help them get their work done.


GPU stands for graphics processing unit. You’ve likely heard this component referred to as a video card. Like gamers, data scientists benefit from owning a computer with advanced graphics capabilities. 

But instead of reducing pixelation and lag, data scientists can harness their computer’s GPU to increase their CPU power. This function allows them to perform more complex processing tasks, particularly those involved with machine learning.

The best laptop for data science has a capable GPU that’s doubly handy for machine learning applications and a late-night round of video games. Of course, if your chosen laptop doesn’t have a decent battery life, you might find yourself going to bed early each night.

Battery Life

Finally, it’s a great idea to consider your potential device’s battery life. Though you may be determined only to use your laptop while it’s connected to a power source, that’s the job for a desktop, not a portable personal computer. Relying on an outlet can also hinder your workflow while on the go.

The majority of laptops can last for between one and ten hours when removed from external power sources. The precise time limit depends on laptop usage. The brighter your screen and the more demanding the applications you’re using, the shorter your lifespan is likely to be.

When you consider how demanding data science applications tend to be, battery life becomes far more crucial. The Macbook Air can stay active for between 15 and 18 hours while disconnected from the nearest outlet. That certainly seems to give it a competitive edge.

Apple MacBook Pro keyboard

The Verdict

A Macbook Air could be an excellent laptop for data science students or data scientists. It may not be the most affordable or upgradeable device, but it features a breakneck processing speed, a gloriously rich Retina display, a relatively long battery life, and a competitive GPU. 

That’s just the right combination of features to make the new Macbook Air a worthy data science device. The only way that the Macbook Air could be a little better is if it came with the 16GB RAM option as a standard and allowed for more upgrade and customization opportunities.

Frequently Asked Questions

Below you’ll find the answers to some of the most frequently asked questions regarding Macbook Air and the best computers for data science.

How Much RAM Do I Need for Data Science?

You might be able to get away with 8GB of RAM while performing basic data science tasks. However, it’s far better to invest in a full 16GB of RAM, if possible.

Which OS Is Best for Data Science?

The answer to this question is bound to differ depending on the person so ask. However, there are some general trends concerning the operating systems most commonly used by data scientists. Firstly, it’s challenging to find a data scientist that uses Windows.

Secondly, there’s a healthy debate about whether macOS is better or worse for data science than Linux, but it seems to come down to personal preference. As such, the best way to answer this question is to say, “It depends on the data science programs that you plan to run on your system.”


The Macbook Air is a competitive laptop due to its powerful processing, clear display, and superior battery life. Though prospective owners pursuing data science may want to add the 16GB configuration and invest in external hard drives, this option is otherwise ideal – even in its standard configuration.

Daisy Adhikari is the founder of Passionate for the field of Data Science, she shares her learnings and experiences in this domain, with the hope to help other Data Science enthusiasts in their path down this incredible discipline.

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