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Although understanding artificial intelligence and data science is crucial; you cannot deny the fact that both are two sides to the same coin. Technology advances are taking the entire world economy by storm. This is where understanding the core amalgam of data science and artificial intelligence is the key.

The fight for being the best is still on between data science and artificial intelligence. But one without the other is incomplete. The truth is that although these terms are used interchangeably over time, they are not the same. It is imperative to understand the key differentiators that set them on separate pedestals. Let us understand each of them in detail.

Understanding Artificial Intelligence

Calling it Artificial is for a reason. Artificial Intelligence is the capability of machines or computing devices to process human intelligence in the same form. It simply is an incredible way of auto-simulation of computer systems for the greater good of the business world.

Global AI Applications:

Personalized shopping
AI Shopping Assistants
Fraud prevention
EdTech Digitization
Smart content creation
Administrative Task automation
Voice assistants
Personalized learning
Autonomous vehicles
Spam filters
Facial recognition
Recommendation systems
Human Resource
Social media
Data security
Travel and transport
Supply chain optimization
Humanized operations

Artificial Intelligence Jobs on Offer:

As per, 2.4 million jobs will be replaced by Artificial Intelligence by 2030. While AI remains a threat to many job profiles, the technology domain is highly vulnerable to being revamped via AI. LinkedIn also remarks that AI will trigger 65% of job skills by 2030. Choose from ML Engineer, Robotics scientist, AI ethics officer, AI Quality assurance manager, and much more to earn big!

Artificial Intelligence Salaries:

Looking through the massive advancements this incredible industry restores; as per Payscale, starting with an average takeout of USD 127380 annually from this year onward is the way ahead to earning a whopping remuneration with the best AI skills on offer and outstanding credentials in your portfolio. There is no stopping earning a massive salary with the right AI and Machine learning certifications and skill sets yielding a highly satisfying career.

Understanding Data Science

Data science is the study of combining mathematics and statistics, specialized programming, advanced analytics, artificial intelligence, and machine learning to make an impact on the future business growth trajectory.

Global Data Science Applications:

Manufacturing Process Optimization
Advanced Personalization
Medical image analysis
Internet Search
Speech Recognition
Advanced Advertising
Financial Fraud detection
Airline route planning
Defending against cyber threats
Customer behavioral Analytics
Hi-end Gaming
Efficient Recommender systems
Search engines
Augmented reality
Image recognition and logistics

Data Science Jobs on Offer:

Data scientist, data analyst, data engineer, data architect, and beyond are some of the exciting career opportunities in data science as you plan. Big moves need informed decisions. Indeed informs that there are 52492024 data science jobs available on the job portal. Isn’t that a massive pool to dive in and land a preferred role of your choice in data science?

Data Science Salaries:

Data science has become one of the hottest jobs in the world today. Stay ready to earn a median salary of USD 146,000 annually in 2024 as per Leap Scholar. Understanding the core data science course eligibility shall make all the difference to set you up for a higher income zone career.

Industry Outlook 2024:

Believing global records from Statista, revenue from the AI software market worldwide is expected to reach 126 billion by 2025. Servion Global Solutions predicts a 95% of customer interactions will be powered by AI by 2025. Aren’t these scores inviting enough to enter the AI world?

Throwing some light on the Data science industry, it is revealed that the demand for qualified data science professionals will surge by 36% through 2031 as per the US Bureau of Labor Statistics. The industry is sure to soar to greater heights, in view of greater data being generated every passing second. By the year 2032, the global data science platforms market size is stipulated to reach USD 501.03 billion ( # # shared by Precedence Research). This is what a promising future looks like.

What makes them different?



Data science is preprocessing analysis, prediction, and visualization
It involves statistical techniques, design, and development methods
Developed to find patterns and hidden data trends
Complex models can be built to extract facts and insights


It involves algorithm design, development, efficiency, conversions, and deployment
TensorFlow, Kaffee, and SciKit-learn are popular AI tools
It is used to handle data autonomously, removing humans from the task
It is meant to build models that emulate cognition and human-comprehension

Do they have any common grounds?

Both rely on large amounts of data to be more effective
Both use statistical techniques for data analysis and insight extraction
Both are interdisciplinary fields, a great amalgam of computer science, mathematics, and statistics


Understanding the core differentiators between the two pivotal streams of professions is a great way to comprehend and build an everlasting career in the field. Both have their own benefits and rewards accordingly. Targeting either of the two streams is surely a rewarding career decision. Stay informed and make big career moves now!