All the AI job seekers must have these tech and non-tech skills

The era of nerds has come to an end. For the new aspiring AI job seekers, it is no longer about how good they are at coding, but alongside they must have very good social skills and the ability to explain the technology to the non-technical directors of the companies. Here are the top 5 tech and non-tech skills that these job seekers must adapt to.


Top 5 Tech Skills

1. Computer programming: One of the fundamental skills to have is the ability to program. Computer architecture, optimization algorithms, data structures, trees, and graphs are just some of the subjects that one would need to be well-versed with.

2. Statistics and probability: At the root of data science is statistics. This is a core part of AI and ML, and having a working knowledge of probability concepts including conditional probability, Markov models, Bayesian principles, etc. is very important.

3. Data modeling: A strong skill that can help in AI is data modeling. It is used extensively in AI to handle pattern recognition and datasets classification.

4. Strong understanding of Unix tools: AI professionals are required to have a strong understanding of Unix tools, their functions, and how to best utilize them since most AI processing will take place on Linux-based environments.

5. Efficiency in distributed computing: The majority of the AI jobs require programmers to deal with large volumes of data, which cannot be processed effectively using a single machine.


Top 5 Non-Tech Skills

1. Communication skills: Just like any other job, AI jobs require professionals to be good communicators. In addition to having technical know-how, AI aspirants need to communicate innovative ideas effectively to their teams.

2. Collaboration: For an AI professional, it is necessary to effectively collect data and convey the information in a comprehensible manner to the team.

3. Marketing skills: No matter how good your idea or project is, it will not sell itself. Being able to market your ideas is crucial to succeeding in the AI space.

4. Systematic and analytical thinking: Systematic and analytical thinking is very important when building a career in AI. One needs to have a curious mindset and a thirst for problem-solving.

5. Understanding ability AI aspirants need the ability to understand problems faced by users and then devise solutions accordingly. Furthermore, they need to crave knowledge that will keep them abreast with the latest technological developments in order to remain relevant.

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