What Skills need to bring an AI developer?

Get started in AI and Machine Learning, part 1 What Skills need to bring an AI developer?

Machine Learning and AI are becoming more and more important. The way the AI programming, however, is not without hurdles. Software developers should, therefore, acquire some skills in order to be prepared for the future.


What to bring to a developer, if he wants to bring AI and ML projects to a successful conclusion?What to bring to a developer, if he wants to bring AI and ML projects to a successful conclusion?

From the banal Machine Learning, short-ML Algorithms in web applications to complex Autonomous systems in the industry or in the automotive industry: high-Performance systems with some intelligence in the future, and the future applications are indispensable.

Everywhere, the market is screaming for Software solutions that have a certain degree of autonomy and the increasing complexity of data processing, automated do. Software developers are doing well, therefore, to familiarize yourself with the AI and Machine Learning technology.

The industry provides to the developer of this Software genus, therefore, certain requirements, to fulfil, to be able in the future to exciting projects. In the Following, we present the most important Skills that bring AI and ML Developer, or should acquire.

1. Proficient in specific programming languages

The AI development is, in principle, with the majority of modern programming languages, some are better than others. In addition to Standards such as C and its derivatives programmer who see their future in the development of intelligent systems should be proficient in, therefore Python. Python has a very active Community, has a variety of freely available libraries for many applications and is optimized for Machine-Learning application.

2. Unix Expertise

It is no secret that many AI-based systems on Unix and Linux. For the programming of intelligent systems, it is therefore important to master the Unix environment. This not only simplifies the task of programming itself, but also for the connection of databases for the statistical analysis, Web Interfaces or Sensors, motors, and control systems. Virtuosity in the Standard Unix applications on the command line, therefore, is a duty and a little experience in programming for Linux and co. is in the KI-developer practice is always helpful.

3. Experience with distributed computing

Complex AI applications require enormous computing power. These provide, servers, and smart systems to form a solid unit. Who controls the distribution of the computational performance of various sub-systems, and knowledge of the friction has the freedom of wireless networking of clusters in Distributed Computing, therefore, has the ideal conditions for working with Machine Learning and AI systems. Computing clusters are also relatively expensive, so the ability to use existing capacity efficiently, it is also very helpful.

4. Expertise in data collection and processing

The recognition that data are not the same, is in the development of intelligent or Autonomous systems, fundamentally. Developers, data collect not only misleading, filter and useful process, but also weights and, if necessary, reject, are therefore predestined for the outstaffing work of intelligent systems. Finally, it is also in working with data, most recently to the effective utilization of existing computing and storage capacities, and thus a significant cost factor.

5. Mathematical and statistical knowledge

Programming is not logic, and, of course, mathematics, yet every programmer is a good mathematician. However, in the development of intelligent systems is a fundamental solid understanding of mathematics and, in particular, of the portion of the statistics requirement.

The programming of the statistical analysis of previously targeted the collected data allows to draw conclusions on trends and Trends. This in turn allows the development of AI, Machine-Learning and Deep-Learning systems. The in-depth understanding of statistical relationships enables AI-programmers to solve targeted problems in Software development.

6. Knowledge of the (sensor)Hardware

Just in the electronics industry, robotics or automotive, it is, of course, when the AI development is also about to process the sensor data. Here, it is therefore useful, in addition to the Software interfaces with the sensor Hardware to know about. For the selection of the appropriate Hardware other departments are, of course, be responsible, however, knowledge of the project that are important sensors help not only to use existing Hardware to be more effective, but also a fruitful exchange with engineers lead.

7. Abstract Thinking and creativity

In the AI development, the abstract is one to consider as one of the core competences, such as a certain degree of creativity in the solution of problems. As everywhere in software development, there are also the AI-development “prescribed” approach, however, developers can use existing solutions regularly and, where appropriate, re-implemented in order to achieve progress.

8. Quick thinking and flexibility

When the AI development, especially in larger team projects requirements change, is known to be. This is exactly why AI developers should be able to leave an already trodden path of the development and, where appropriate, a new approach. This requires not only flexibility, but also the ability to new situations quickly

9. Patience and perseverance

Of course, AI and Machine Learning are projects nothing other than development tasks. And how often during programming, it is often the case that something will not work as it should. In such cases, patience, and persistence to get to the end, to the very end – a feature that should be in every Software developer.

10. Good General education and empathy

Last but not least, intelligent Algorithms operate at the end of the path, of course, people interact with and support you. Also, if a developer is not directly involved with the man-machine communication, it can be helpful to keep this always in the back of the head. A broad General education can help to make this interface for the User as attractive as possible, especially if the developer can understanding the user, in order to allow him an optimal user experience.

Certainly, especially front – end and Interface designers are asked here, however, is an intelligent Software can be perceived as a threat. Communicate eye-to-eye with the user and is empathetic, is this the work of your programming team and the chances are good that the Software will be positively received.

Skills that every developer

Overall, developers are in demand for AI-related skills, such as in the case of the regular software development. The difference is that more of them are needed at the same time, in order to make intelligent Software in the most efficient and user-friendly. Who unites as many of the above-mentioned properties, will in the future be, when the AI development.


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