Key Differences between Data Science & Artificial Intelligence

Data Science and Artificial Intelligence are the two most in-demand fields currently. The terms Data Science and Artificial Intelligence are often used interchangeably. While these fields depend on each other, they have minute differences. 

Artificial Intelligence is the science of making machines capable of thinking like humans and generating human-like solutions. Data Science is simply the process of collecting data and information from various sources to uncover insights.

Before diving into the conclusion that which one is the right career path for you, let’s understand the difference between Data Science and Artificial Intelligence in terms of tools and technologies used, career paths, and job opportunities.

What is Data Science?

Data Science, to begin with, is a method to collect, organize, and analyze sets of data to generate meaningful insights used for decision-making, planning, and other purposes. Data Science techniques are used widely in every sector. Be it in agriculture, medicine, or marketing, Data Science is used to extract useful information such as medical image analysis, tracking the market trends, insights about customers, the company’s progress, and its possible future outcome. 

Data scientists use different Data Science techniques like regression, classification and coding languages such as R and SQL which makes the algorithm accelerate the process of data collection, analysis, and predict the outcomes.

What is Artificial Intelligence?

Having discussed Data Science, let’s understand the true meaning of AI. Artificial Intelligence is an imitation of human intelligence. AI is a machine that functions the way the human mind thinks and takes decisions.

The applications of Artificial Intelligence are numerous; right from the healthcare industry to games and finance, their use is aiding humans in solving complex tasks. 

Data Science vs Artificial Intelligence

Data Science vs Artificial Intelligence: Job Profiles

Job profiles in the Data Science and AI field vary greatly. The work of a data scientist is to generate valuable information from big data and analyze it for various purposes. 

However, Data Science job profiles are not limited; they include Data Engineer, Data Architect, Data Scientist, and others. 

AI domain provides various promising job roles to make a better future career. Anyone aspiring to enter the field of Artificial Intelligence (AI) can opt for job profiles like Bioinformatics Scientists, Robotics Engineer (computer vision), Bioinformatics Analyst, etc. 

But data scientists and AI engineers work collaboratively in certain areas like the building of Machine Learning models.

Responsibilities of a Data Scientist vs AI Engineer

The responsibilities of a data scientist and AI engineer depend on the job roles and responsibilities. Their basic work is to perform extensive research by analyzing the data and predicting the possible outcomes of the data. 

The responsibilities of a data scientist include:

• Extracting data from valuable sources
• Cleaning and analyzing the sets of data
• Processing the data through data analysis
• To analyze large data and find a similar pattern from it
• Predicting the outcomes through Machine Learning algorithms

The responsibilities of an AI engineer include:

• Speech recognition
• To obtain information from videos and images from the given inputs
• Stock trading through automation
• Providing services to customers through chatbots or messaging bots

Data Science vs Artificial Intelligence: Core Skills Required

Data Science and Artificial Intelligence demand high skills in the relevant domain. Apart from theoretical knowledge, the company hiring data scientists and AI engineers looks for skills in every candidate. 

Any individual aspiring to get into the Data Science field must be knowledgeable in R, Python, database management, analytics and modelling, and other important tools and techniques. 

When it comes to the Artificial Intelligence field, one should be familiar with Spark, big data technologies, Python, R, Java, C++, etc. 

Conclusion

Knowing the difference between Data Science and Artificial Intelligence (AI), it can be said that both fields vary greatly in every aspect. But their similarities cannot be ignored. Data Science is a broad category that includes AI as well. Data Science uses ML algorithms that need AI to work efficiently. 

Both Data Science and AI are making a significant impact in the 21st century along with providing a better future career. Both fields offer many job opportunities with interesting roles to play. Machine Learning Engineer, AI Engineer, NLP Scientist, etc., are some of the positions an enthusiastic tech person can apply for. A person who wishes to make a career in either Data Science or Artificial Intelligence must know the basic distinction between the two.