Tech

How to re-skill for a career in AI


For end users and IT professionals looking to transition into an AI career, here are the skills you need to develop and the steps to take.

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This year, LinkedIn named data science specialists and artificial intelligence specialists among the top jobs businesses look for. The salary for an artificial intelligence practitioner is $124,000 to $150,000. For a data science professional, the salary ranges from $100,000 to $130,000. Compare this to the average programmer salary in the US, which is under $100,000.

If you’re working for a company, you want to make as much money as possible – but you also want to enjoy what you’re doing and you want the confidence and reassurance that you’re providing value in your work. yourself and that you yourself are appreciated.

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At times, an IT professional can feel stuck at work, with no way out for a promotion or higher salary. Software maintenance programmers often fit into this category. So non-technical business analysts or IT support people who have spent so much time managing databases, storage and help desks that they are recognized as critical experts. If you try in these areas, unfortunately can be a career end in the IT field.

Time to try AI?

The skills required for a data science professional are knowledge of data visualization, statistical modeling, and open source tools and libraries for machine learning and artificial intelligence. For those practicing artificial intelligence, the skill set is machine learning, C++, Python, and cloud services like Amazon Web Services.

Want to try AI? Consider the following first.

Learn AI Job Search Strategies

If you are an IT person looking to transition to AI, what skills will you need and what strategies should you adopt?

Check with yourself

At first glance, it sounds very tempting to increase your salary by 30-40% by switching to AI, but is AI right for you?

Most IT professionals like to feel that they are in control. They like the idea of ​​working towards predetermined goals and deadlines for delivered products. AI doesn’t provide that.

Machine learning is the part of AI that can steer an AI project and its results in completely different directions than the project initiators thought. Some AI projects fail after months of efforts. Data scientists from academic backgrounds are used to this uncertainty, but IT professionals accustomed to tough deadlines and outcomes are not.

If you can’t live with uncertainty, then AI is probably not right for you.

Evaluate the skills you will need

If you are a database expert, SQL and NoSQL database skills are important. You should also plan on acquiring a working knowledge of graph databases, which are commonly used in AI systems.

If you are an application programmer, knowledge of Python, C++, Java, Julia, and R is very important.

If you are a business analyst, it is important to keep your business knowledge up to date so that you can assist users in building use cases and questions for AI, but you should also fluent in statistical analysis and algorithm development so you can speak to data scientists.

Create your own AI opportunities

In some cases, companies will assist employees in changing careers towards AI by offering them AI project work. In other cases, companies prefer to hire outside talent.

If you’re in a company that doesn’t have AI opportunities for current employees, you can still get AI training by taking college or university classes outside of business hours.

The next step is to find opportunities to work on real-world AI projects so you can include these real-world projects (and the new skills you’re using) on ​​your resume. Networking through your school is a good place to start when looking for actual AI project work.



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