Computer engineering has come a long way from merely being a curriculum major to a key credential for your AI portfolio. Artificial engineering is a role that commands huge skill and expertise in the realm of technology. Unsurprisingly, the demand for their services outstrips the supply. The industry is oozing with valuable companies with diversified roles involving AI systems management.
AI engineers use a variety of hard and soft skills to succeed in their roles. Developing desirable AI engineer skills can greatly help advance your AI career manifold. From robots serving food in restaurants to self-driving cars, these applications of artificial intelligence can be seen in our daily lives. AI develops intelligent software and systems based on how human minds think, learn, decide, and solve a problem. It enables machines to perform human-like functions by learning through experience. In today’s world, AI capabilities are expanding at an astounding rate across industries- gaming, robotics, face recognition software, weaponry, speech recognition, expert systems, and search engines.
Who is an AI engineer?
Pursuing AI as a career is a lasting job opportunity that offers a wide range of roles and responsibilities to honor. An experienced and certified AI engineer is the one responsible for building AI models using machine learning algorithms and deep learning neural networks to draw business insights. These are further used to make business decisions that have a long-term impact on organizational growth. They create weak or strong AIs, depending on the organization’s intended goal.
AI engineer skills to succeed
AI engineer skills are the core abilities that assist AI engineers to succeed in bringing greater success to their recruiters. Many AI skills are hard to crack, but with due practice and repeated applications, these allow AI engineers to make the most of the situation at hand and delve deeper into the resolution trajectory.
Key credentials required
- Educational degree– A degree in computer science or STEM subjects leads your way ahead for a lasting AI engineer career.
- Programming language proficiency– Expertise in at least one of the popular programming languages such as Python, R, Java, etc is the stepping stone for a meaty AI engineer role.
- AI model proficiency– Building and training AI models is a critical skill demanded by an AI engineer role. It cultivates experience while you proceed with linear regression, classification algorithms, decision trees, and deep neural networks.
- Linear algebra and statistics– Basic knowledge about applied mathematics such as linear algebra and statistics help an experienced and certified AI engineer to tackle gradient descent algorithm; and other probability theories.
- Data literacy– It s the basic grounding for an AI engineer to be able to read, understand, analyze, and apply data to various use cases. The ability to comprehend data well for useful business insights is a credential that is never ignored by recruiters.
- Critical thinking– Apart from technical skills, it is imperative for an AI engineer to possess soft skills as well. Delivering timely and accurate results with a critical bend of mind leads the way to a balanced business decision.
- Business acumen– Working in the business environment calls for an efficient AI engineer to master AI skills that are business-centric and a great understanding of business workings would take you a long way.
- Communication skills– Breaking the second largest barrier to effective business decisions is communication. That is the reason the role demands impactful and open communicative skills, that enables you as an AI professional to connect with your team and reciprocate decisions to the stakeholders conveniently.
- Collaboration– If you are keen on working in a team and open to accepting or sharing information for making impactful business decisions, the AI engineer role is made for you.
- Time management– Building, testing, and deploying AI models demands timely action. Making the right move at the right time is key to a successful business environment.
- Experience with related technologies– Mastering related data and deploying technologies and AI models involves IoT devices, robotics, and cloud computing. Finesse in working in an integrated environment would take you a long way ahead in your AI engineering career.
Ways to enhance AI engineering skills
- Gain requisite AI Engineer certification
This is vouched as one of the easiest ways to scale your AI engineer career. Earning the best AI engineer certification from the most credible and sought-after AI world leaders such as MIT, USAII™, Stanford, Columbia University, etc would lead you closer to your preferred AI role.
- Earn a postgrad degree in AI
Build on the skills gained during your undergrad degree and level up your degree with a post-grad qualification. - Get a mentor– An experienced AI engineer from the industry would help you understand the inside-out of the industry quite easily; preparing you for a meatier role.
AI salary and benefits:
A Certified Artificial Intelligence Engineer is a highly skilled workforce, that attracts an inviting salary package commanding a wide job market with diversified roles. As per Glassdoor, the national average salary for an AI engineer is USD 121,046 annually. They are in high demand across the globe, with higher job openings in several states. Thereby, it’s time to build a future-proof AI engineer career that offers attractive job benefits. If you’re thinking to switch or build a flourishing AI engineer career, make an informed decision with the best AI engineer certification and the right credentials with popular AI skills to strengthen your portfolio.
