which is best between BSC ARTIFICIALLY I AND BTECH ARTIFICIALLY INTELLIGENCE??? BSC DATA SCIENCE AND BTECH DATA SCIENCE??? BSC MATHEMATICS, STATISTICS VS BTECH DATA SCIENCE WHICH IS BEST FOR DATA SCIENCE??

Comparing an engineering degree in Civil Engineering and Data science would be equivalent to comparing apple to oranges. Instead of comparing the two domains, the recommended way is to understand the pros and cons within both domains and then make a choice on the one which suits us better. This can again be a very personal question that varies from opinion to opinion. There is a famous saying, which goes like: “Do what you like, and you will never have to work a single day in your life.”

We would throw some light on both domains and rest the choice of picking a domain based on the reader's opinions and ideas.

As we begin to analyze the domain, one must keep in mind that there this list is suggestive and not exhaustive. The opinions and ideas are subjective and vary from scenario to location.

Let us begin by analyzing the top market trends and skill requirements in both domains.

Domain advantages:

• In a growing economy such as hours, civil engineering continues to see constant demand for skilled individuals. The demand exponentially increases for specialized skills and experienced professionals.
• The domain can offer asymmetric returns for highly skilled and experienced professionals.
• Comparatively, this domain is shielded from multiple disruptive technologies and changing landscapes.
• Your growth and development exponentially rises with your personal brand the organizational brand development.
• The domain forms the backbone of an economy. Hence, one can always expect government support and initiatives from the ones who are willing to add actual value and better services.

Domain disadvantages:

• The people who are starting to build their careers from scratch in this domain might not be compensated as per their peers in other domains. The compensation rises as you grow inexperience.
• The domain highly is dependent on government policies and market trends.
• There might be a demand-supply mismatch in terms of labor skills within entry level jobs. However, this balances out as people transition their careers to complimentary verticals.

Let us now focus on the Data Science domain keeping it under a comparative lens to the civil engineering domain.

Domain advantages:

• High growth domain with huge opportunities for skilled individuals to build a robust career path.
• As the amount of data that we manage today grows exponentially, so would the need for people who can manage and make sense of this information.
• The domain leverages multiple open-source solutions. Hence, the barrier to entry is minimal to learn and grow.

Domain disadvantages:

• As the gap between skill demand and supply closes, the industry might witness a slowdown in lucrative compensation that is being seen now.
• The process could soon be automated as technologies such as auto ML become better at making decisions.
• The domain requires highly skilled professionals who are willing to constantly adapt to new tools and solutions.

Having analyzed the pros and cons of both domains we can now make an informed decision on the type of domain that suits best to our needs and career goals. One must also keep in mind that the underlying landscape in both domains is fairly dynamic in nature and hence, one needs to do sufficient amount of research during the point of actual decision making. However, the broader points remain consistent and must be leveraged while actually comparing and analyzing career options.