Data Science Vs Machine Learning [Updated] - October 3rd, 2024

There are a lot of points that help to establish Data Science vs Machine Learning.

The major one is Data Science deals with all kinds of data, assimilation, segregation, and analysis to offer detailed solutions. At the same time, Machine Learning spins around Artificial Intelligence only. There are other reasons as well that make both of them different from each other. In this article, you will learn more about Data Science and Machine Learning and the major skills that make them poles apart.

Table of Contents

Data Science Vs Machine Learning: Major Differences

There is a huge difference between Data Science and Machine learning; here are some salient points covering the same:

Data Science is a field that includes the segregation and arrangement of Data and then extracting knowledge from the data. Whereas Machine Learning is entirely focused on developing algorithms and models to predict results.
The main objective of Data Science is to extract patterns and trends from data and then offer an actional solution to the problem. Machine Learning learns from the previous data and then offers improved suggestions.
Data Science uses major skills like Math, Statistics, and Probability to offer concrete solutions. Whereas Python, JAVA, SQL, Prototyping, and Data Modelling are some significant skills required for Machine Learning.
All those industries and fields that require and transform data in direct application utilize Data Science. Whereas, Machine Learning is heavily invested in the field of Artificial Intelligence.

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What is Data Science?

Data Science is a multidisciplinary field that works on the basic to advanced principle of data assimilation. The field combines a lot of techniques from Mathematics, Statistics to Computer Science for extracting insight from available data. The science includes various processes like Data Cleaning, Data Collection, Data Analysis, and Data Visualisation. The primary goal of Data Science is to learn about patterns and trends and use the same to make informed decisions and solve complex problems.

Skills Needed

Here are the major skills that are needed for Dat Science:

Programming
Data Manipulation and Analysis
Statistics and Mathematics
Machine Learning
Domain Knowledge
Effective Communication
Data Visualisation
Understanding of Probability

Career Prospects

Those who complete the Data Science course effectively get to work in the following career fields:

Data Scientist
Data Analyst
Machine Learning Engineer
Data Engineer
Business Intelligence Analyst
Research Scientist

What is Machine Learning?

Machine Learning is a subfield of artificial intelligence (AI) which is focused on the development of algorithms and models. The data also plays a huge role here by offering crisp predictions. Machine Learning includes designing statistical techniques and computational models that help a machine to improve its performance.

The technique also uses past data to identify patterns and relationships in data to make predictions. Machine Learning also uses steps like feature extraction, data processing, model evaluation, and model deployment.

Skills Needed

Programming
Mathematics and Statistics
Machine Learning Algorithms
Data Processing
Feature Engineering
Evaluation and Model Selection
Data Visualization

Career Prospects

Here are some major career prospects one can go for post completing the Machine Learning course:

Machine Learning Engineer
Data Scientist
Research Scientist
Data Analyst
Artificial Intelligence/Machine Learning Consultant
Artificial Intelligence/Machine Learning Product Manager

Who Earns More Data Science Vs Machine Learning?

Both Data Science and Machine Learning are high-paying jobs in the industry. Generally, Machine Learning Engineers are paid high as compared to Data Science. The reason being the world is moving towards Artificial Intelligence. The average salary of a Data Science Engineer is Rs 10.5 lakhs per annum. Whereas the same is Rs 12.4 lakhs per annum for a Machine Learning Engineer.

The salary package is generally based on the course pursued, its popularity and its application in the industry. The salary gap tends to increase with the rise in the experience level of both posts.

Which is Better, Data Science Vs Machine Learning Engineering?

Data Science and Machine Learning are both illustrative career paths for those looking for a great technological career. Here are the salient points that can be checked to understand the same:

Data Science has a broader scope, including collection, segregation, assimilation, and visualization of data. Whereas Machine Learning is limited to Artificial Intelliegence only
Data Science emphasizes data manipulation and analysis, whereas Machine Learning focuses on model development and software engineering skills.
Data Science works by utilizing the available data to devise a concrete solution. Whereas Machine Learning focuses on implementing and scalable solution

Data Science Vs Machine Learning FAQs

What is Data Science?

Ans. Data Science is a multidisciplinary field that works on the basic to the advanced principles of data assimilation and segregation.

What skills are required to learn Data Science?

Ans. Programming, Data Manipulation and Analysis, Statistics and Mathematics, Machine Learning and Domain Knowledge are some basic skills required to learn Data Science.

Which is better, Data Science Vs Machine Learning?

Ans. It is completely dependent on the industry and the type of p

What skills are required to learn Machine Learning?

Ans. Programming, Mathematics and Statistics, Machine Learning Algorithms, Data Processing, and Feature Engineering are some basic skills required to learn Machine Learning.

What career prospects are open for one after completing a Data Science course?

Ans. Data Scientist, Data Analyst, Machine Learning Engineer, and Data Engineer are some major career prospects open for one after completing the Data Science course.