7 Top Notch Tips for Growing Your Career in Artificial Intelligence

In the modern era, a career in artificial intelligence (AI) has been in massive demand. The core objective or goal of this technology is the transformation of human resources into the power of the machine. AI also develops automatic machines, wireless machines or robotic machines that are able to think, act or perceive as a human being. In the near future, it is expected that AI could well lead over the technology-driven world due to its capability. There is no surprise in the fact that there would certainly be many job openings for machine learning or artificial intelligence in the near future.

1. Improve your skillset

For the purpose of building a career in artificial intelligence, it is essential that you must be able to boost up different levels of skills. They may include deep learning, natural language processing (NLP), mathematical and statistical skills, knowledge representation and reasoning (KR), pattern recognition, semantic, neural network (NN), graphics, data pre-processing, robotics, cognitive science theory, algorithm design and physics.

2. Learn programming languages

As a professional, if you do want to develop your individual career in machine learning (ML) or artificial intelligence (AI), then you should also be a good programmer. It is also essential to know the syntax of a programming language very well. From a technical perspective, a programming language could be termed as a set of instructions. To develop a machine learning project or artificial intelligence, various programming languages can be used. For example, learning some of the prominent languages such as R, Python, JavaScript, Scala, Prolog, LISP and C++ could be highly beneficial.

3. Know about frameworks and tools

To make a career in artificial intelligence, one should be able to utilize frameworks and tools for the purpose of working in this field. As a result, you should be able to have an idea of the various kinds of tools that could be utilized for the purpose of developing a project for artificial intelligence. There are various tools and frameworks that are available such as Caffe, TensorFlow, PyTorch, Theano, NumPy, Microsoft Cognitive Toolkit (CNTK), SciPy, Keras, Spark MlLib, Apache MXNet and several others. As a professional, if you ever feel developing an interest in your career in artificial intelligence or if you are looking for a job in artificial intelligence, then you must know the specific tool or framework that could help to make your code easy to implement.

4. Know about deep learning

Apart from having a firm knowledge of algorithms, artificial intelligence and programming language, you should also have comprehensive knowledge about deep learning. Also known as structured learning, deep learning could be termed as one kind of machine learning based on artificial neural networks. This can be helpful in making a career in artificial intelligence.

5. Data processing techniques

For the purpose of developing any machine learning project, data pre-processing is usually the first step. As data is usually collected through the means of different sources, it is required to be cleaned. This is a technique of transforming raw and unprocessed data into a specific desired format. For the purpose of getting a job in machine learning, you should be able to know the data pre-processing technique effectively.

6. Read AI Blogs

One of the best ways of improving your knowledge about AI is through means of reading blogs. If you are keen on getting a job in machine learning or artificial intelligence, then you should go through several AI blogs. If you are able to read blog articles then you will be able to know about several other prominent techniques. Some of the most prominent blogs include Open AI, Machine Learning Mastery, MIT AI News, Chatbots Life, etc.

7. Expand your understanding of algorithms

It is a fact that an algorithm is an extremely essential part of machine learning as well as artificial intelligence. As a result, if you are interested in doing machine learning or artificial intelligence job then you must also be able to understand algorithms very well. There are various algorithms and every algorithm is essential to develop for a machine learning-based project. Every algorithm tends to be different from each other. Some are basic and easy algorithm while others could be complicated and advanced. Some of the most common algorithms include linear regression, Naïve Byes, Support Vector Machine (SVM), Decision Tree, K-means, K-nearest Neighbor (KNN), Gradient Descent, and many others.