Often the terms Data Science and Artificial Intelligence are used interchangeably. But are these same or have significant differences? It is very important to learn about them when you are planning your career path in either of these. For example, if you plan to start your career in data science, and enroll in some data science course, then will you be taught about Artificial Intelligence? And if the course curriculum covers Artificial Intelligence, then does it mean you simultaneously qualify for an artificial intelligence career too?
Well, let us go through a detailed comparison between Data Science and Artificial Intelligence, and see what the core differences are.
Career Outlook: Data Science vs. Artificial Intelligence
What is Data Science?
Data Science is known to be the sexiest job of the 21st century. It refers to the field of study where skilled data science professionals work with raw data to draw meaningful insights for solving complex business problems by helping the management with data-driven decision-making.
If we look at the data science market, it is rapidly growing at a CAGR of 16.2% and according to Markets and Markets, the market value will reach a value of $501. 03 billion by 2032. Whereas if we look at the employment opportunities in this field, then the demand for data scientists is expected to grow by 35% from 2022 to 2032, as reported by the US Bureau of Labor Statistics. Also, WEF has reported the data science jobs are the 5th fastest growing job this year. Data Science, therefore, is a great career option for 2024.
What is Artificial Intelligence?
On the other hand, Artificial Intelligence is a field of computer science that deals with designing and developing intelligent computer systems that can perform tasks similar to that of human intelligence. The WEF has already ranked Artificial Intelligence jobs as the fastest-growing job of the year. And if we look at the artificial intelligence market, then it is growing at a CAGR of 21.6% to reach a market value of approximately $2 trillion by 2030. The US BLS has reported the demand for AI specialists will grow by 31% by 2032.
So considering the job outlook, both Artificial Intelligence as well as Data Science fields are great choices for a rewarding career.
Data Science vs. Artificial Intelligence – Comparison Table
|
Aspect |
Data Science |
Artificial Intelligence (AI) |
|
Definition |
Data science focuses on
extracting insights and knowledge from data using statistical and analytical
techniques. |
AI involves creating machines or
systems that can perform tasks that would typically require human intelligence,
such as problem-solving, decision-making, and learning. |
|
Core Objective |
Analyzing and interpreting data
to inform decision-making, predictions, and problem-solving. |
Replicating human-like cognitive
functions, such as understanding, reasoning, learning, and adapting. |
|
Data Usage |
Data science primarily uses data
to answer questions and make informed decisions. |
AI uses data as a means to train
algorithms and models, enabling systems to perform tasks autonomously. |
|
Techniques and Methods |
Statistics, data mining, machine
learning, and data visualization are commonly used in data science. |
Machine learning, deep learning,
natural language processing (NLP), computer vision, and robotics are central
to AI. |
|
Scope |
Data science is a subset of AI, focused
on the processing and analysis of data. |
AI encompasses a broader range
of technologies and applications, including robotics, expert systems, and
more. |
|
Application Areas |
Data science is applied in
various domains, including finance, healthcare, marketing, and social
sciences. |
AI has applications in
self-driving cars, chatbots, recommendation systems, medical diagnosis, and
many others. |
|
Human Involvement |
Data science often requires
human intervention for data preparation, model building, and interpretation
of results. |
AI aims to reduce human
involvement by enabling systems to make decisions and learn independently. |
|
Examples |
- Predictive analytics for sales
forecasting |
Different job roles in Data Science and Artificial Intelligence
Now, let us have a look at some of the popular job roles in the field of data science as well as artificial intelligence.
|
Data Science |
Artificial Intelligence |
|
Data Analyst |
Artificial Intelligence Engineer |
|
Data Engineer |
Research Scientist |
|
Data Scientist |
Robotics Engineer |
|
Business Analyst |
Machine Learning Engineer |
|
Business Intelligence Developer |
Artificial Intelligence Scientist |
|
Data Architect |
AI Ethicist |
How to get into a Data Science or Artificial Intelligence Career?
Follow these simple steps to start your career in either Data Science or Artificial Intelligence:
· Acquire the right education: Both data science and AI are technical domains and having relevant degrees in mathematics, computer science, or related fields is recommended.
· Gain the right skills: The core skills in data science and AI although are the same, but have slight differences. Enroll in the best data science or AI certification program and gain the relevant skills
· Build a portfolio of real-world projects
· Network with people from these fields
· Start finding and applying to preferred jobs.
So this was our comparison of the Data Science and Artificial Intelligence fields. Both are great options to pursue a career in 2024 and are closely related. So, start by making your foundation strong and then specialize in a specific area as your career progresses.