How to Create a Strong AI Portfolio That Attracts Employers

Artificial Intelligence (AI) is among the greatest technological revolutions that have strike the world of technology. According to Market Search Engine estimation the AI will be worth USD 5.80 billion by the year 2025. This resulted in the high demand for AI professionals today.

With the growing demand for AI, many professionals are considering it as a career option. In this article, let’s understand the step-by-step process of developing a strong AI Portfolio that showcases the in-demand AI skills to employers

Steps to follow to Maximize the AI Portfolio and Become an Artificial Intelligence Professional

Step-1

One of the essential requirements for an artificial intelligence professional, who is looking for a growth-driven career in the field of AI must be good at numbers, i.e. they must hone their basic math skills. This will be helpful in writing better code.

Step-2

In this step, one should strengthen their roots, on those concepts that play a crucial role in this field. Here are the following concepts:

☛ Linear Algebra, Probability, and Statistics — As mentioned before mathematics are an integral part of AI. And if an individual wants to excel in the AI career, then they must have sound knowledge of these concepts of advanced math. They are vectors, matrices, statistics, and dimensionality, and also have clear understanding on probability basics such as Bayes Theorem.

☛ Programming Languages — The most vital factor is that an individual must be learning programming languages, as they play a prominent role in AI. One can choose an AI engineer certification to learn the programming languages. There are many programming languages, an individual can enroll at least one among the following to learn and excel:

• Python
• Java
• C
• R

☛ Data Structures — Enhance the way to solve problems that have data, create an analysis of data more accurately so that one can develop their own systems with fewer errors. Learn the various parts of programming languages, which will be useful in getting an understanding of data structures like stacks, linked lists, dictionaries, etc.

☛ Regression — Regression is very useful for making predictions in real-time implementations. It is useful to have knowledge of these concepts of regression.

☛ Machine Learning Models — Acquire knowledge on the different machine learning concepts, such as, Decision trees, Random Forests, KNN, SVM, etc. Learn the ways to apply these by understanding the algorithms as they are quite useful in solving the problems.

Step-3

In this step, an artificial intelligence professional should learn more in-depth concepts that are a complex part of AI. If one masters these concepts then they can excel in their career in the field of AI and it also acts as a most important asset in the portfolio.

☛ Neural networks — It is a computer system designed on the human brain and nervous system that works by incorporating data through an algorithm it is built on. The concepts of neural networks are the foundations for developing AI machines, it is better to have a deep knowledge of its functionalities.

There are various types of neural networks that are helpful in many different ways.

• Perceptron
• Multilayer perceptrons
• Recurrent neural network
• Sequence to sequence model
• Convolutional neural network
• Feed forward neural network
• Modular neural network
• Radial basis functional neural network
• Long Short-Term Memory (LSTM)

☛ Domains of AI — After obtaining knowledge about the concepts and various types of neural networks, learn about different applications of the neural networks, it will be useful to develop one’s own applications. Each application in the AI field demands a different approach. One must have right AI skills to begin with a certain domain, and then can proceed further, to master all the fields of AI.

☛ Big Data — Though it is not considered an essential part of getting expertise in AI, knowledge about the basic concepts of big data will be beneficial.

Step-4

This is the last step in the process of developing a portfolio that is needed to be a master in the AI career:

☛ Optimization Techniques — By learning optimization of algorithms will be useful to enhance or less the error function. These functions are related on the models internal learnable parameters that play a crucial role in the accuracy and efficiency of results. Learning this will be useful to apply optimization techniques and algorithms to model parameters that are useful to obtain optimum values and accuracy of such parameters.

☛ Publish Research Papers — One of the best approaches to establish one’s own credibility in the field of AI career is by going a step ahead by reading research papers in this field and publishes research papers. Start the own research and understand the cases that are in the process of building.

☛ Develop Algorithms — After completing the process of learning and research, begin working on building algorithms. One might get a new revolution with the knowledge to have.

Conclusion

Building a strong AI portfolio is very necessary for displaying the skills to potential employers in the field of AI. The AI portfolio is a reflection of the skills and expertise. It must demonstrate the ability to tackle the real-world problems with the help of AI techniques and showcase the commitment to the field.