A few years ago, had we imagined a driverless car, a digital talking device (Alexa or Siri), or a spacecraft without human presence, and many more things we are witnessing nowadays seem possible. It is all possible because of artificial intelligence. We are using artificial intelligence in our daily lives through several mobile and computer applications such as Google Maps, banking apps, social media platforms, and several assistance apps. Artificial intelligence is playing a vital role and gaining more and more popularity due to the recent advanced innovations in the field of machine learning and artificial intelligence.
Artificial Intelligence has played a very important role in the field of computer science. Artificial intelligence tools and techniques and subsequent components make this world a better place to work and live. Artificial intelligence technologies are a great asset to humans and are programmed to decrease human work/effort as much as possible. These tools and technologies tend to possess the capability to work in an automated era. They also speed up your processes and tasks along with a guaranteed level of accuracy and precision.
So in today’s scenario, there is a huge demand for artificial intelligence engineers, especially those who have taken AI certification course, who can make an organization’s technical work easier and faster. So this article is going to discuss some of the important basic steps to become a successful artificial intelligence engineer.
What is an Artificial Intelligence Engineer?
The Artificial Intelligence Engineer is an IT expert who can develop smart algorithms capable of learning, predicting, and analyzing future events. They are the pro-level experts who can make machines capable of thinking and reasoning like the human brain. They are also known as researchers who analyze the functioning of the human brain to create computer programs with the same cognitive abilities as humans. Their aim is to develop algorithms that receive input data on the history of purchase, sales, and products to predict potential customer behavior.
Companies highly value the Artificial Intelligence Engineer’s post as it can make companies achieve their goals smoothly. They work with traditional ML techniques like natural language processing and neural networks to create models that power AI-based applications. They establish and achieve objectives using techniques associated with AI reasoning and uncertainty. They analyze systems to control and monitor development projects using AI methodologies. These engineers use their best AI practices in several processes like data recognition, data mining, data processing, and robotic control. They apply logic, machine-learning concepts, and probability analysis in problem-solving initiatives for smooth and easy business operations.
Artificial Intelligence engineers can create applications such as Language translation, Visual identification or perception, and Contextual advertising based on sentiment analysis. They focus on developing tools, processes, and systems to enable artificial intelligence applications in real-world contexts.
Steps To Become a Successful Artificial Intelligence Engineer
To become an AI engineer, it is highly recommended to complete a certification course in Machine Learning, Data Science, or Artificial Intelligence. It can add value to your resume and make your portfolio attractive and strong. Achieving certification can also help you acquire in-depth knowledge of AI topics with chances of increased salary.
To get success in these job roles, professionals must have an analytical thought process and the ability to solve problems with cost-effective and efficient solutions. But there are some of the important basic steps to be taken to become an AI engineer mentioned below.
- Fundamental Education- The journey of an AI engineer begins with earning a bachelor’s degree first in streams like Mathematics, Computer Science, Information Technology, Statistics, Finance, or Economics. Sometimes a Master’s degree is also required in Mathematics, computer science, Cognitive science, Data Science, etc., and certification in Machine learning and Data Science.
- Master Your Technical Skills- After gaining certification it is also necessary to gear up your practices, software development techniques, and programming skills. To get success in the AI field, you must master Programming Languages, Mathematics and Algorithms, Statistical Knowledge, Natural language Processing, Neural networks & Deep Learning, etc. In-depth knowledge and understanding of these technical skills are required.
Besides those skills, AI engineers are also required to brush up on their theoretical and practical knowledge about topics like Software development life cycle, Design Patterns, OOPS, Modularity classes, Statistics and Mathematics, Machine Learning, Robotics, Electronics, and Instrumentation, etc.
- Develop Your Business Skills- Besides your technical knowledge, it is also essential to develop your necessary business skills in order to secure your artificial intelligence job. Business skills such as effective communication, rapid prototyping, creative thinking, industry knowledge, analytical problem-solving skills, etc., are required to be a successful AI engineer.
Skills Required For AI Job Roles
Professionals who want to become AI engineers must know about the skills required in this dynamic field. Some of them are:
- Programming Skills- It is the first skill required to become a successful AI engineer. It is essential to learn the required programming skills like R, Python, Java, and C++ to create and implement models.
- Statistics, Probability, and Linear Algebra Skills- AI Engineers implement different AI models such as Naive Bayes, Hidden Markov models, Gaussian mixture models, and linear discriminant analysis. So it is necessary to have a deep understanding and knowledge of Probability, linear algebra, and statistics to work with such models.
- Big Data and Spark Technologies- AI engineers have to work with a huge amount of data that could be in terabytes or petabytes. So these engineers must learn about spark and other big data technologies to make sense of it. Hadoop, MongoDB, Cassandra are a few more big data technologies that can be learned to become a perfect AI engineer.
- Frameworks and Algorithms- To implement AI models in real-time operations, it is necessary to understand deep learning algorithms like a convolutional neural network, generative adversarial network, and recurrent network and implement them using a framework. These frameworks like Theano, Caffe, PyTorch, and TensorFlow are used in artificial intelligence.
Besides the above-mentioned skills, some soft skills like communication skills, problem-solving skills, and analytical skills are also required to become a successful Artificial intelligence engineer. So get prepared with AI certifications and skills and find your niche in this dynamic domain.