Data Science vs Machine Learning | Which Has A Better Career

Data Science vs machine learning

In data science vs machine learning, data science works with data to make future predictions. While machine learning uses data to perform some functions.

Have you ever thought about how brands target your needs and seek your attention? In other words, how do you see the most relevant ads on different networks over the internet? If, yes then here is the cutting throat answer to this question with the help of data science and machine learning. 

Yes, in the 21st century, data science and machine learning are changing the world. Both of these have become the most searched terms over the internet. Data science and machine learning are almost everywhere, from our mobile phones to our favourite apps like Netflix, Amazon, Google, WhatsApp, Facebook, etc., that rely on data science and machine learning to show the most accurate results. These technologies also lead to Big Data, where these organizations work on massive amounts of data. 

There are lots of other sub-technologies running with the help of machine learning and data science. Now let’s look at which one is supposed to be the best as a student for you. Should you go with data science, or machine learning could be a better choice for you? Let’s get the comparison between data science vs machine learning. But before we compare them let’s answer a few questions:-

Which pays more for machine learning or data science?

If we talk about PayScale, then obviously, machine learning can offer you better pay than data science. Machine learning offers approximately $123,000 per annum, while data science offers approximately $97,000 per annum. The reason is that machine learning is the core concept for modern-day technologies such as artificial intelligence, robotics, business intelligence, software development and many more.

Machine learning Engineer Salary

Data Scientist Salary

Keep in mind that the pay scale of both of these technologies is growing at a rapid pace. We can say that machine learning has a slight edge over data science in this comparison between data science vs machine learning.

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Is Machine Learning a branch of data science?

No, machine learning is not a branch of data science. The branch of artificial intelligence allows the Machine to apply learning without human intervention. But it is one of the core parts of data science that is quite useful in data cleansing, preparation and analysis. 

What is Data Science

Data Science is used to study the complex and massive amount of data in an organization. It deals with the raw data and then converts it into valuable information. And at the end, get a solid conclusion from that data that helps with organizational growth. Data science deals with structured and unstructured data. It helps to find the pattern within the massive dataset to get an edge over the competitors.

To be successful in data science, you should have a good command of data mining, statistics, machine learning and data analytics. You should also have a good command of R or Python to understand the algorithms. Data science has the best in class future scope and is widely used by the leading tech giants such as Amazon, Google, Apple, Netflix, Facebook, Tesla and many more. 

The Limitations of Data Science

Likewise any other technology, data science also has some limitations. Data science relies on data. And we know that data is growing at a rapid pace. There is always a possibility to get cheap quality data even from the most reliable sources over the internet or offline. The reason is that there are lots of spammers who are spamming with the data.

That is why we have more chances of getting incorrect data nowadays. It will lead to wasting lots of time, effort, and resources to build a model that will provide misleading information. Although data scientists are working on the process to make it more accurate, we don’t have any best solution for this problem.

Careers in Data Science

Data science is full of opportunities. It is the core of big data technologies. Therefore, wherever you find big data, there is always an opportunity for data science. And we know that nowadays, almost every company is collecting data from their users. And to process that data, they are looking for a data scientist. That’s why data science offers one of the leading opportunities to students. Have a look at it:-

  • Data Scientist
  • Data Architect
  • Statisticians
  • Data Engineer
  • Data Analyst

Skills Needed for Data Scientists

  • Statistics
  • Data mining and data cleansing
  • Data visualization
  • Unstructured data management techniques
  • Programming languages such as Python or R
  • Strong knowledge of SQL databases
  • Good commands over big data tools like Hadoop, Hive and Pig.

If you want to start your Data Science journey, joining a Data Science Bootcamp is the best way. The Bootcamp provides an updated industry-vetted curriculum, mentorship with Tech leaders, and 360° job and placement assistance.

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Machine Learning

Machine learning is a way that gives computers the ability to learn without human intervention. Machine learning also works with the help of data. It has plenty of algorithms that process the data and train the Machine for delivering future predictions. It is a branch of artificial intelligence that is a set of instructions to perform specific functions.

Machine learning is quite powerful and plays a crucial role in modern-day technologies such as robotics, voice recognition, search engines, and more. Most of our daily used platforms such as Netflix, Amazon, Google, Facebook are using machine learning to suggest the best possible content. Machine learning is all about finding the best fit for the problem. It finds the solution without human intervention. It comes into action to make predictions about complex topics most efficiently and reliably. 

Limitations of Machine Learning

Machine learning also has some the limitations like any other technology. However, machine learning is better at creating useful results. To get full advantage of machine learning, you need to use algorithms to solve new problems. But still, machine learning has some limitations to solve some problems.

Let’s have an example that we can solve some traditional equations to solve problems most of the time. But if we solve the same problems with the machine learning algorithm, it can be quite a complex process to solve the same problem. 

Careers in Machine Learning

There are lots of careers in machine learning. Machine learning is serving many industries, such as healthcare, robotics, software development, digital marketing and many more. Let’s have a look at some of the best careers in machine learning:- 

  • Machine learning engineer
  • Business intelligence developer
  • Software engineer
  • Natural language processing scientist
  • Software Developer

Skills Needed for Machine Learning Engineers

  • Statistical modelling
  • Computer science fundamentals
  • Good understanding of algorithms functioning
  • Data evaluation and modelling
  • Natural language processing
  • Good command over Python programming
  • Text representation techniques

Data Science vs Machine Learning Trends

This chart shows that data science and machine learning are giving neck to neck competition to each other. The red graph indicates data science, while the blue indicates machine learning over the past 12 months. As you can see that in Dec 2021, machine learning has a slight edge over data science. 

Data Science vs Machine Learning (Tabular Form)

S.NoData ScienceMachine Learning
FieldData Science is the field where we need to process and system that extract data into structured and semi structured format. Machine learning is the field that gives the machine extraordinary capabilities to learn without human intervention. 
AnalyticsRelies on analytics, without analytics, data science can’t exist.Machine learning can use data analytics for better performance and accurate results. 
DataData science deals with raw data from multiple sources.Machine learning deals with the data from data science or other techniques.
Techniques.Data science can use machine learning algorithms to process data but once data is not coming from multiple sources then it is not necessary.Machine learning uses various techniques to process data using regression, supervised clustering and lots more techniques. 
FocusData science is a broad field that focus data processing using statistics, algorithms and many more techniques. Machine learning focuses on statistics algorithms. 
TypesAlthough data science doesn’t have any specific types, it includes plenty of operations such as data mining, data clearing, data manipulation etc. Machine learning is of three types such as unsupervised learning, reinforcement learning and supervised learning. There are three types: Unsupervised learning, Reinforcement learning, Supervised learning.

Data Science vs Machine Learning

Usage

Ata science is used to understand the hidden pattern from the data and offer useful insights from the data. The organization uses that insight and pattern to make smart business decisions. 

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On the other hand, machine learning is the subset of artificial intelligence. It deals with machines rather than humans. It helps in predicting and classifying outcomes for learning patterns by past data.

Skillset

A data scientist needs to be skilled. Here are some of the key skills required to be a data scientist: Hadoop, Python, R, Scala, Data visualization, data mining, data cleansing, database, leadership, problem-solving, etc.

On the other hand Machine learning engineers should be skilled professionals. The most in-demand skills for machine learning engineers are computer science fundamentals, Python, statistics, problem-solving, mathematics concepts, SQL etc.

Model

Data science use involves various steps; a data scientist needs to create a model to solve the given problem. Therefore they can deploy multiple models.

On the other hand, machine learning doesn’t use any specific model, but it is used in the data modelling step of data science. In this comparison between data science vs machine learning, we can say that data science involves lots of models

Data

There are multiple sources used to gather the data for data science operations. That is why it needs to work with raw, structured, and unstructured data.

On the other hand, machine learning grabs the data from the structured and semi-structured format. From this comparison between data science vs machine learning we can see that data science require more effort to convert the data into valuable format.

Focus

Data scientists need to focus on mining, handling, and cleansing the data. Apart from that, they understand the data pattern and then visualize the final output of the data. 

On the other hand, Machine learning engineers focus on managing the complexity of the data that can occur during the implementation of algorithms and mathematical concepts behind it. 

Data Science vs Machine Learning Prediction

Let’s wrap up what we have learned about data science vs machine learning. From the comparison above, we can’t conclude which one is the best and why. But we can say that both of these technologies offer students outstanding career opportunities. In contrast, if you are more interested in data and statistics, you should go with data science.

On the other hand, if you want to work in futuristic technologies, machine learning is the preferred choice for you. Keep in mind that learning any of these technologies is not everyone’s cup of tea. To be good at these technologies, you need to spend lots of time and be consistent with your studies and tasks. Hope you have liked our comparison between data science and machine learning.

If you still have some doubts regarding machine learning or data science then you can take the help of our data science assignment help experts anytime.

Frequently Asked Questions 

Is Machine learning better than data science?

Machine learning needs the data to work efficiently. On the other hand, data science works with data along with machine learning algorithms. In other words, data scientists need to have strong commands over some machine learning algorithms to work efficiently with data science. In contrast, machine learning is not better than data science because it is crucial for data science and artificial intelligence. 

Is data science a good career?

Data science is one of the leading professions these days. It has become a must-have area for organizations because it provides measurable business outcomes. With the help of data science, organizations have become more productive and making more profits than their competitors. Now you can have an idea of data science career potential.