No doubt that Machine Learning (ML) and Artificial Intelligence (AI) are rocking the digital marketplace. These two technologies have transformational power that has changed businesses upside down. It has also changed the interaction between computers and humans at times of complex tasks.
Even Chinese Computer Science Expert Fei-Fei-Li confirmed the increased dominance of game-changing technology. Majority of corporate has been implementing AI in their organization to multiply their investment. AI bandwagon has become a great opportunity for all corporate to grab exciting full-time or remote jobs.
Companies knowing the importance of AI are stagnating and the common question, what are the skills to implement or know AI? Here are the nine essential skills explained to clear their doubts.
- Solid Mathematical and Algorithms Knowledge
- Well-Versed With Probability and Statistics
- Basic Expertise In Programming Languages (Python/C++/R/Java)
- Efficiency In Distributed Computing
- Good Command Over Unix Tools
- Expanding The Knowledge Of Advanced Signal Processing Techniques
- Innate Curiosity and Creativity
- Ability To Stay Updated and Grasp New Concepts Quickly
- Perseverance and Patience
Solid Mathematical and Algorithms Knowledge
An AI expert will have a broad set of algorithms and applied mathematics. Those candidates or employees will have a well-versed knowledge with huge problem solving and analytical skills. It helps them to perform difficult tasks in an efficient manner. According to many AI experts, strong mathematical and algorithmic knowledge will help the employees address a problem with the ways to optimize the outputs.
Well-Versed With Probability and Statistics
Every AI professional must have a detailed probability and statistics knowledge. In order to understand difficult AI models including Hidden Markov Models, learning complex algorithms really helps a lot.
Statistics comes first in the list of prerequisites for efficient AI programmers and professionals. Navigating in the basics and updated statistical methods helps them to have a model evaluation metric level.
Basic Expertise in Programming Language (Python/C++/R/Java)
Proficient experts have to learn programming languages like Python, C++, Java, etc at some point in their work life. Python makes it easier to create complex algorithms and C++ thereby speeds up the entire coding process.
Basic knowledge in R is essential to deal with stats and plots. Many aspiring AI professionals need Java to implement reducers and mappers too. There are many easy ways to explore or master languages. It helps in exploring open source libraries.
For instance, let us take Scikit-learn. It is one of the great resources for Python professionals that helps in the transition of AI and ML. On the contrary, Spark, and WEKA brings ideal information for Java experts to enter into the magical AI domain.
Efficiency in Distributed Computing
The majority of the AI jobs deal with large data sets that cannot be processed using a single machine. After minding it in the operation, it is necessary to equally distribute across an entire cluster. Efficiently distributed computing will sharpen the skills of the AI professional.
Good Command Over Unix Tools
Many AI process takes place in Linux-based machines. Hence, programmers need to master several Unix tools to tackle the errors. Programmers have to know about the Unix tools including awk, grep, cat, sort, etc. Having thorough knowledge about their functions and ways might help them to utilize the tools well.
Expanding the knowledge of advanced signal processing techniques
ML is its integral aspects where engineers have to be familiar with different problems along with advanced signal processing algorithms. Many bandlets, wavelets, curvelets, etc have been handled by AI professionals when they have the ultimate thought process with the advanced signal processing techniques.
Added to this, core understanding along with the time-frequency analysis will discover many ways to implement problems. Concepts including Convolution and Fourier Analysis will help AI professionals to expand our knowledge.
Innate Curiosity and Creativity
To excel in the AI domain, programmers have to be curious and innovative about their implementation. It also helps them to discover novel ways in order to approach specific problems. When the professional is creative in his way, then it grabs abstract information efficiently. It also reduces the possibility of error occurrence.
Ability To Stay Updated and Grasp New Concepts Quickly
Aspiring and energetic AI professionals must have a passion for updating their knowledge with frequent updates. With the latest developments in the tech industry, they will put forth efforts to update their skills. At the same time, advanced development tools, theories, algorithms, etc, will boost up the performance of the employee.
In addition, participating in various online forums, communities, and blogs help in catering to AI professionals. Many popular papers including Google Big Table, Google Map Reduce, etc will sharpen the AI skills of programmers. At the same time, it brings in a good job to grab attentive skills regarding the AI development domain.
Perseverance and Patience
Engineers must have a persistent attitude to cope up with the beneficial skills and countless iterations. This perseverance and patience will help to achieve accurate results. Discovering new tools and methods to make the community more efficient.
There are many ways to achieve the outputs. Every technology including AI and ML will update in a while. Hence, it is necessary to take the step over to the new career move. The confidence makes a smooth transition into the AI development domain.
As an employer, what is the next step?
In a nutshell, there are many skills to start the AI phase. Moreover, the above-mentioned skills help in making the AI implementation phase smoother. In order to train your employees under AI technology, have a glance at our AI corporate training where you can grab enough information to move on further.