Introduction

A few years ago, we would never have imagined that technology could become so advanced, and it’s all possible thanks to data science and machine learning.

Just look around. A lot of the applications and technology you use every day rely on data science and machine learning to work.

For Example – If you scroll your social media like Instagram you can observe that your social media feed is filled with posts and ads recommended just for you, right?

This is all possible by algorithms working behind the scenes. And it’s not just social media platforms; there are recommendation systems on streaming platforms like Netflix, which suggest movies and shows based on what you have  watched before.

Another example is, IBM recently improved heavy rain forecasts using data science and machine learning. They gather weather data from satellites and weather stations and use this information to spot patterns that signal heavy rain. 

On the other hand, Machine learning models learn from past data to predict storms and update forecasts with new information in real time. This helps provide more accurate weather predictions and timely warnings, such as Red Alerts. So people can be aware & better prepare for heavy rain.

You may have a question in your mind: how do these technologies work, and why are they so important? To answer all these questions, we need to first understand what Data Science and Machine Learning is?

In this blog, we will explain about data science and machine learning, their future scope, salary, skills and explore the differences between data science and machine learning.

So let’s first understand what is data science?

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What is Data Science?

Data science is everything and everywhere especially in businesses. Without data science, there is no balancing between businesses because it plays a very important role in understanding customer requirements. It combines statistical knowledge and domain specific expertise to extract invaluable insights from both organized and unorganized data.

In 2024, choosing to learn data science is a smart move.The field is growing fast, and there’s a growing need for people who are passionate about learning data science. As per linkedIn statistics 93,000+ data science jobs are available in India.

What Skills Required to Become a Data Science?

To become a data scientist, you need:

• Programming: Knowledge of Python or R.
• Mathematics & Statistics: Skills in statistics and probability.
• Data Manipulation: Ability to clean and handle data (e.g., using pandas).
• Machine Learning: Understanding of algorithms and models.
• Data Visualization: Skills in tools like Matplotlib or Tableau.
• Data Management: Familiarity with SQL and databases.
• Critical Thinking: Strong problem-solving skills.
• Domain Knowledge: Understanding of the industry you’re working in.

What are Career Opportunities after learning data science?

• Data Scientist
• Data Analyst
• Machine Learning Engineer
• Data Engineer
• Business Intelligence (BI) Analyst
• Quantitative Analyst
• Statistician
• Data Consultant
• Big Data Engineer
• AI Researcher

Also Read – What Is Data Science – A Ultimate Guide To Beginners

What is Machine Learning?

Machine Learning helps computers learn from data to make their own decisions or predictions. Instead of telling a computer exactly what to do, you give it lots of examples, and it figures out how to use that information to solve problems. 

For example – If you show it many examples of spam emails, it can learn to recognize and filter out spam in new emails.

Machine learning is becoming more important in many fields today such as – 

• Healthcare
• Finance
• Retailers 
• Transportation
• Entertainment services

Machine learning is an exciting and fast-growing field today. It’s part of artificial intelligence, and many people see them as the same thing. In this tech era, machine learning is very popular. Big companies like Google, Facebook, and Amazon use this technology. You have probably heard of Alexa and Siri , they are the best examples of machine learning.

Also Read – How To Choose The Right Algorithms For Machine Learning?

What Skills Required to Become a Machine Learning Specialist?

To become a machine learning specialist, you need:

• Programming: Skills in Python or R.
• Math & Statistics: Understanding of statistics and algebra.
• Data Handling: Ability to clean and manage data.
• Machine Learning Algorithms: Knowledge of different algorithms.
• Data Visualization: Skills in tools like Matplotlib or Seaborn.
• Data Management: Familiarity with databases and SQL.
• Problem-Solving: Ability to solve complex problems.
• Model Evaluation: Understanding how to test models.
• Software Development: Basic knowledge of coding practices.
• Communication: Ability to explain results clearly.

Also Read – What Is a Data Science Course?

What are Career Opportunities after learning Machine Learning?

• Machine Learning Engineer
• Data Scientist
• Data Analyst
• AI Researcher
• Business Intelligence (BI) Analyst
• Software Developer
• Quantitative Analyst
• Robotics Engineer

Which is better, Machine Learning (ML) or Data Science?

The future of technology is all about data, and fields like Data Science and Machine Learning are changing. Choosing between Data Science or Machine Learning depends on your interest and most importantly your career goals. 

As we discussed earlier, Machine Learning is all about building and improving algorithms that help computers make predictions from data. If you like working on advanced technology and solving tough problems, Machine learning is a great career choice for you. 

As we know, Data Science is about analyzing large amounts of data to find useful insights and help with decision-making. If you are interested in exploring data and spotting patterns, Data Science could be a better fit. 

Both fields are important; you just need to find your expertise and choose a career in Data Science or Machine Learning accordingly.

Which Profession Offers A Higher Salary: Machine Learning Or Data Science?

Machine Learning (ML) and data science are in demand in India and earn well. On average, Machine Learning engineers earn somewhat more than data scientists.

As per recent Naukri.com statistics indicates that the average yearly salary for a Machine Learning engineer in India is ₹20 LPA, while that of a data scientist is ₹15 LPA.

Keep in mind that salaries depend on experience, Job location, Company and most importantly your skills. Both fields offer rewarding careers with high earning potential.

Here is a table comparing the average annual salaries for Machine Learning engineers and data scientists in India, based on experience level:

Conclusion

In this blog we conclude that – 

• Both data science and Machine Learning field has booming career today
• Machine Learning is the right field for you if you like complex problems, working with algorithms, and developing systems that learn from data.
• If you are interested in statistics, analyzing and extracting data then you should go for data science.
• Ultimately, choose a field based on what you’re interested in and what you like.

Want to learn Data Science With Machine learning and Data Visualization?

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FAQ’s

Should I learn data science or machine learning first?

You should start with Data Science first to build a strong foundation in data analysis and then move to Machine Learning for advanced modeling.

Should I learn AI or ML?

Learn Machine Learning first, as it is a subset of AI (Artificial Intelligence) and provides the basics needed to understand other AI concepts as well.

Is Alexa AI or machine learning?

Alexa uses both AI and Machine Learning to understand and respond to user commands.

What is the difference between AI and ML?

AI (Artificial Intelligence) is the broader concept of machines being able to carry out tasks in a smart way, while ML (Machine Learning) is a subset of AI that involves machines learning from data to make predictions or decisions.