Difference Between Data Science, Artificial Intelligence and Machine Learning

Difference Between Data Science, Artificial Intelligence and Machine Learning | Artificial Intelligence and Machine Learning | Emeritus

Businesses are embracing process automation, with 88% of Indian companies looking to boost their AI investment in 2022, up from 82% in 2021, as per Deloitte India’s second edition of the State of Artificial Intelligence (AI) in India report. Three areas in which Indian companies are showing keen interest are Data Science (DS), Artificial Intelligence (AI), and Machine Learning (ML) because they are reaping tangible returns from these AI technologies. In this article, we look at the difference between data science and machine learning and artificial intelligence. 

In this blog, you’ll learn:



  • What is Data Science and How is It Related to Artificial Intelligence? 
  • What is Artificial Intelligence and Machine Learning, and How are They Connected?
  • What is the Difference Between data science, and machine learning, and artificial intelligence? 
  • How do Data Science, Artificial Intelligence, and Machine Learning Complement Each Other? 
  • Which Field is the Most Promising Career-wise?
  • Differences in Job Titles and Salaries in Data Science, Artificial Intelligence, and Machine Learning

Data science is a multidisciplinary field that combines techniques from statistics and computer science to extract valuable insights and knowledge from data. Additionally, it involves collecting, cleaning, and analyzing data to discover patterns, make predictions, and enhance decision-making. Data scientists use a variety of tools and techniques, such as data analysis, machine learning, data visualization, and data mining, to achieve these goals.

On the other hand, artificial intelligence applications require large amounts of data to function smoothly. Data scientists are the ones who make this data available. Moreover, they collect, clean, and analyze large amounts of data to learn patterns and correlations, which AI apps can use to create predictive models. 

ALSO READ: The Importance of Data Science Courses for Success as a Professional

What is Artificial Intelligence and Machine Learning, and How are They Connected?

Artificial intelligence is the subdiscipline of computer science focused on building machines capable of solving complex problems using data. Meanwhile, machine learning is a subfield of artificial intelligence that trains machines to act like humans and perform human-like tasks using historical data. Furthermore, ML provides AI the ability to analyze data, recognize patterns, and adapt to new information. This makes AI autonomous and capable of performing tasks that require human intelligence with ease. 

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What is the Difference Between Data Science, ML and AI?

 

Data Science  Artificial Intelligence Machine Learning 
Focus  Extracts deep insights from raw data to make informed decisions  Enables machines to perform complex tasks like humans, such as decision-making and problem-solving, with ease.    Creates a system for computers to learn from data and uses the insights to improve their operation over time. 
Application  It can be used by businesses to solve complex problems, capture trends, and make market forecasts.   It can be used in chatbots, for voice assistance, and in robots to perform manual tasks typically performed by humans.  It can be used to make automated recommendations, search algorithms, and health monitoring to learn from available data. 
Skills and Competencies Required  
  • Advanced mathematical skills 
  • Statistics 
  • Database management
  • Data visualization 
  • Basic understanding of ML methods
  • Advanced math
  • Knowledge of programming (especially Python, R, Java, and C++)
  • Probability and statistics knowledge
  • Knowledge of neural network architectures
  • Data modeling and evaluation
  • Basic understanding of natural language processing

Now that we have looked at the difference between data science, and machine learning, and artificial intelligence, let’s look at how they are connected. 

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How do Data Science, AI, and ML Complement Each Other?

Data science, Artificial Intelligence (AI), and Machine Learning (ML) are interconnected disciplines. Data science collects, analyzes, and interprets data to gain insights. Meanwhile, AI focuses on creating intelligent systems that mimic human decision-making, and ML, a subset of AI, enables machines to learn from data. 

Data science provides the data and analysis that fuel AI and ML. AI leverages data-driven decision-making from data science, and ML algorithms improve through data provided by data science. The three work in harmony: data science extracts meaningful information, machine learning enhances predictive models, and artificial intelligence employs those models to make intelligent decisions, collectively driving advancements in technology and automation.

Which Field is the Most Promising Careerwise?

All three fields—data science, ML, and AI—offer promising career prospects. According to the World Economic Forum, there will be 95 million jobs in these three fields by 2025. Certainly, the job landscape in data science, machine learning, and artificial intelligence is expanding rapidly. Given that, there will be increased demand for professionals with advanced data science, artificial intelligence, and machine learning knowledge like AI Specialists, Big Data Specialists, Process Automation Specialists, and Digital Transformational Specialist. 

ALSO WATCH: Mid-Career Transition to Data Science by Dr Chirnajiv Roy, Head of Data Science & Analytics

Differences in Job Titles and Salaries in Data Science, AI, and ML

By now you must have figured the difference between data science, and ML, and AI. Therefore, now let’s look at the job titles and salaries in data science, artificial intelligence, and machine learning. 

Data Science Job Title  Average Annual Salary
Data Architect  ₹20,00,000 to ₹24,00,000 
Data Scientist  ₹12,00,000 to ₹12,80,000
Data Engineer ₹9,00,000 to ₹9,80,000
Data Analyst ₹5,30,000 to ₹5,60,000
Python Developer  ₹5,00,000 to ₹5,60,000
Data Researcher  ₹4,70,000 to ₹5,00,000

 

Artificial Intelligence Job Title Average Annual Salary
AI Specialist ₹20,00,000 to ₹23,00,000
AI Consultant ₹11,00,000 to ₹11,30,000
AI Engineering Leader ₹8,50,000 to ₹8,70,000
AI Scientist ₹8,00,000 to ₹9,00,000
Chatbot Developer ₹5,00,000 to ₹5,40,000

 

Machine Learning Job Titles  Average Annual Salary
Lead Machine Learning Engineer ₹23,00,000 to ₹25,00,000
NLP Researcher  ₹13,00,000 to ₹14,00,000
Machine Learning Specialist  ₹10,00,000 to ₹12,00,000
Robotics Engineer ₹3,00,000 to ₹3,80,000

 

Note: All the salary figures are extracted from AmbitionBox.com

Learn Data Science With Emeritus 

If you are looking to build a career in data science, and machine learning, and artificial intelligence, you’re in the right place. Emeritus offers an array of data science, machine learning, and artificial intelligence courses that equip learners with the skills and knowledge they need to drive data-driven decision-making in their organizations. Furthermore, these courses are designed for freshers and experienced to enhance their understanding of data management, exploratory data analysis, machine learning, and deep learning.

Write to us at content@emeritus.org

About the Author

Content Writer, Emeritus Blog
Nikhil is a passionate and free-spirited writer with 4+ years of experience. He has a keen eye for the ever-evolving content landscape, which helps him craft captivating content across various genres. He writes about marketing, data science, and finance for the Emeritus Blog. Beyond work, Nikhil is a dedicated pet parent who loves leisurely walks with his beloved puppers.
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