In recent years, the field of AI has practically flooded everywhere. Suddenly it was a huge topic, discussions broke out about whether AI would cost jobs and replace people. Virtually overnight, providers entered the market alongside ChatGPT and the tech giants engaged in unprecedented competition.
Although this new development was initially viewed very critically, it is now clear that there are many professions in the field of AI and machine learning that simply did not exist in the past. This gives you the opportunity to make a career in this field.
What qualifications do you need for a career in AI and machine learning?
You need special qualifications in the field of AI and machine learning. Understanding and practical skills are important. Programming languages and software skills are key here.
There are now over 20 different Bachelor's and Master's degree programmes in the field of AI at state universities in Germany. The contents are often very similar. However, you can also enter this area through courses and specialisation modules.
In both areas, data is analysed, statistical evaluations are created and algorithms are developed. Of course, you need programming languages for this. Python is very widely used in the field of AI. In the field of data visualisation and statistical analysis, R is very popular. But other programming languages are also in demand when it comes to developing software frameworks for AI.
Knowledge of SQL is also essential. Hadoop and Spark as big data technologies and AWL, Azure and Google Cloud for Cloud services should be familiar to you. Many ML projects rely on these due to the large volumes of data that are processed and stored in the cloud.
Tableau and Power BI are important when it comes to software tools used for data analysis and visualisation. They can be used to interpret data and communicate their insights.
What professions are there in the field of AI and machine learning?
There are various opportunities to enter careers in the field of AI and machine learning. The Prompt Engineer is the one that is gaining in importance in many industries. As a Prompt Engineer, you develop the prompts and ensure that they are optimised. In doing so, you get the best out of image generation tools or various AI models.
The Machine Learning Engineer is responsible for the development and optimisation of machine learning models for practical applications.
The AI researchers is also a very important area. Here you develop innovative algorithms and deliver new approaches in AI.
It can be an advantage here to also NLP Specialist to develop. The focus here is on the understanding of human language by computers and its processing.
The Data Scientist is important in this area when dealing with large data sets. It is also important for the derivation of findings through Machine learning techniques responsible.
If you would like to go one step further, apply for the AI Product Manager. Here you are the interface between the market and technical development. You help to design new AI products and then support them.
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