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Content creation using AI - What artificial intelligence is already capable of today

12/28/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Artificial intelligence (AI) today is capable of performing a wide range of tasks, such as automated authoring and editing of text, creation of images and graphics, recognition of patterns, and segmentation of data.

A particularly insightful example of the application of AI in content creation is what is known as automatic text generation. Artificial intelligence can be used here to autonomously generate text on a given topic. This text can then be reviewed and edited by a human editor to suit the client's requirements.

AI can also be used to create images and graphics. Artificial intelligence can be used to generate images and graphics using algorithms on a computer. These images can then be edited by a designer to fit the client's needs.

AI technology can also be used to recognize patterns. Artificial intelligence can be used to analyze data and look for patterns. This technology can then be used to uncover what content is best suited for a particular audience.

Finally, AI techniques can be used to segment data to ensure it is relevant to specific audiences. These techniques can also be used to customize content for different audiences.

In a nutshell, it can be said that AI is already playing a strong role in content creation. AI technology can be used to create text, images and graphics, recognize patterns and segment data. This allows content creators to work more efficiently and customize content for different audiences.

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The study of computer science and programming: A look at the course content

11/17/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Computer science and programming are crucial in today's digital era and offer a wide range of course content. This article takes a closer look at studying computer science and programming and provides insights into the exciting topics that students explore.

Basics of computer science

The study of computer science often begins with a comprehensive introduction to the fundamentals of the discipline. Students learn about the history of computer science, basic concepts and principles, algorithms and data structures.

Programming

Programming is a central component of the degree programme. Students learn how to master various programming languages such as Java, C++, Python and JavaScript. They develop skills in software development, coding, debugging and creating applications.

Databases

Databases are crucial for storing and managing information. Students learn how databases are designed and managed. They learn SQL (Structured Query Language) and other techniques for querying and managing data.

Operating systems and networks

Students deepen their understanding of operating systems such as Windows, Linux or macOS. They also learn the basics of computer networks, network protocols and security concepts.

Software development

Software development is a central component of the degree programme. Students learn how to plan, develop and test software projects. Agile development methods and project management are also covered.

Artificial intelligence and machine learning

The fields of artificial intelligence (AI) and machine learning (ML) are becoming increasingly important. Students deal with these topics and learn about ML algorithms and techniques as well as their application in various fields of application.

Security and data protection

In view of the growing threats in the field of cyber security, security and data protection are of great importance. Students study techniques for securing computer systems and data protection regulations.

Web development and front-end and back-end programming

In the age of the internet, web development is an important focus. Students learn how to create modern web applications, both in the frontend (user interface) and in the backend (server and databases).

Practical projects and internships

During their studies, students often work on real projects to apply their knowledge in practice. Internships in software development companies or IT departments offer the opportunity to gain practical experience.

Professional preparation and certifications

Many computer science programmes integrate vocational preparation courses and offer the opportunity to acquire certifications in relevant areas. This facilitates the transition into the professional world and shows employers the qualifications of graduates.

Conclusion

The Computer Science and Programming degree programme offers a wide range of course content that enables students to explore and shape the world of technology. Graduates are well placed to succeed in areas such as software development, IT management, data analysis, cyber security and many other IT and technology-related careers. As digitalisation progresses, computer science knowledge and programming skills are invaluable and offer a wide range of career opportunities.

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Studying Data Science: A look at the course content

11/17/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

In an era where data has become one of the most valuable commodities, the study of data science has become one of the most sought-after disciplines. This article takes a closer look at the study of data science and provides insights into the exciting topics that students explore.

Mathematical basics

The Data Science degree programme often begins with a comprehensive introduction to mathematical fundamentals. This includes statistics, linear algebra, calculus and probability theory. This knowledge forms the foundation for later data analysis and modelling

Programming and data analysis

One of the key skills of a data scientist is programming. Students learn to master programming languages such as Python or R in order to collect, process and analyse data. They are familiarised with data wrangling techniques to transform raw data into a suitable form for analyses.

Data visualisation

Data visualisation is an important aspect of data science. Students learn how to present data in charts, graphs and interactive visualisations. This helps to recognise and communicate complex patterns and findings from the data more easily

Machine learning and artificial intelligence

A central focus of the Data Science degree programme is machine learning. Students deal with various ML algorithms and techniques to create predictions and models. This includes supervised learning, unsupervised learning, deep learning and more.

Big data and databases

The processing of large amounts of data, also known as big data, is an essential part of data science. Students learn how to store and retrieve data in distributed systems and how to use tools such as Hadoop and Spark.

Data ethics and data protection

Given the sensitivity and volume of data collected, ethics in data processing is of great importance. Students deal with issues of data ethics, data protection and the legal aspects of data processing

Practical projects

During their studies, students often work on real-life projects. These can be case studies, competitions or research projects in which they apply their knowledge and skills in practice.

Professional preparation and internships

Many data science programmes integrate career preparation courses and offer the possibility of internships in companies to give students practical experience in the industry. This facilitates the transition into the professional world.

Conclusion

The Data Science degree programme offers a wide range of course content that enables students to explore and shape the world of data. With a strong foundation in maths, programming and data analysis, graduates are well placed to succeed in areas such as business intelligence, data analytics, machine learning and many other career opportunities. Data science is not only one of the most sought-after disciplines, but also a key to shaping the future.

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Start-ups “Made in Germany”: Examples of success from the German start-up scene

11/09/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

Germany is not only known for its solid industry and strong economy, but has also developed into a hotspot for innovative start-ups in recent years. The German start-up scene has produced an impressive number of success stories. In this article, we take a look at some of the remarkable "Made in Germany" start-ups that have gained global recognition.

1. Zalando: fashion retail in the digital age

Zalando, founded in 2008, has developed into Europe's leading online fashion platform. The company started out as a small online shoe retailer and has since expanded its range considerably. Today, Zalando offers a wide range of fashion items and brands and serves customers across Europe. The platform has revolutionised e-commerce and is an outstanding example of the success of the German start-up scene.

2. Delivery Hero: international delivery services

Delivery Hero was founded in 2011 and has developed into one of the world's leading providers of online food delivery services. The company operates platforms in more than 40 countries and offers a wide range of food delivery options, from pizza to sushi. Delivery Hero has changed the way people order and get food delivered and has become a global player.

3. N26: Digital banking for the world

N26 was founded in Berlin in 2013 and is one of the fastest growing digital banks in the world. With a user-friendly mobile app, N26 offers a wide range of financial services, from current accounts to investment opportunities. The company has managed to challenge traditional banks and attract millions of customers across Europe.

4. FlixBus: revolutionising long-distance travel

FlixBus, founded in 2013, has redefined long-distance travel in Europe. The company offers comfortable and environmentally friendly coach travel in over 30 countries and has changed the way people travel across Europe. FlixBus has also established itself in the USA and is an impressive example of a German start-up expanding internationally.

5. Celonis: process optimisation through AI

Celonis, founded in 2011, specialises in process optimisation for companies. The company uses artificial intelligence to analyse and optimise business processes. Celonis has won leading global companies as customers and is one of the fastest growing German technology companies.

Conclusion

German start-ups have developed into real success stories in recent years and have played a significant role in various sectors such as e-commerce, delivery services, finance and technology. These examples show that Germany

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The golden years are over: Why you should definitely not become a programmer

11/03/2023 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS

In recent decades, programmers have often been considered the heroes of the digital age. They were considered the creative minds who revolutionized the world and created technologies that improved our daily lives. However, despite the glorious fame of times past, there are some key reasons today why you should definitely not become a programmer.

Saturation of the job market:

The exponential increase in the number of people who have flocked to the programming industry in recent years has led to a significant saturation of the job market. As a result, salaries are not as high as they once were, and competition for coveted positions is enormous.

Outsourcing abroad:

Many companies have realized that programming work can be outsourced at a low cost. As a result, jobs are being moved to countries where labor costs are lower. This trend is putting further pressure on salaries and working conditions for programmers in many countries.

Rapid technological change:

The world of technology is changing at breakneck speed, and programmers need to stay current to stay relevant. This means they must continually improve their skills through ongoing training and lifelong learning.

Lack of recognition:

Although programmers are the driving force behind many successful projects, they are often not properly recognized. Their work often remains in the background, and their successes are attributed to the company rather than the individual.

Monotony of tasks:

In many programming jobs, the work revolves around solving similar problems, which can lead to a certain monotony. This can lead to the work becoming less fulfilling after a while.

Work-life balance:

The constant accessibility and need to always be available in today's fast-paced digital world can make it difficult to maintain a healthy work-life balance.

Automation and Artificial Intelligence:

With increased automation and the advent of Artificial Intelligence, there is a possibility that some programming jobs may become obsolete in the future.

While programming is undoubtedly an important skill and there are still fascinating aspects to the technology industry, it's important to recognize the realities of today's job market. If you are not passionate about diving into the world of programming and are prepared to withstand the challenges of this industry, it may be wise to explore other career paths that better fit your interests and goals.

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