Programming.

Programming is the basis for the development of software and applications that influence our daily lives. It has become an essential skill as it enables companies to automate processes, analyze data and develop innovative solutions.
The Python programming language is particularly popular with beginners because it is easy to learn and versatile. It offers a clear and understandable syntax that enables even beginners to quickly become productive. Once you have mastered it, it is easier to learn other languages.
Python is often used for data analysis and machine learning as there are many powerful libraries such as Pandas, NumPy and Scikit-Learn.
Programming with Python is a central component of our Data Analyst and Data Scientist training program. For example, you will learn how to write simple scripts, handle variables, functions and loops and apply advanced techniques such as machine learning and deep learning. This will prepare you for the future and teach you how to program with a specific area of application.
Data Analytics
- Basics of programming in Python: variables, functions, methods, conditions and loops
- Use of popular Python libraries such as Pandas and Matplotlib to read, process and visualize data
- Dealing with internal (csv, SQL) and external data sources (APIs) in Python
- Use of the Python library statsmodels to make predictions
Data Science
- Use of the Python library NumPy for efficient numerical calculations
- Introduction to Scikit-Learn (sklearn) for the use of machine learning algorithms
- Using TensorFlow to create and train neural networks and working with Keras as a high-level API for the development and training of deep learning models
- Development and management of data pipelines for the automation and optimization of data processing processes
Object-Oriented Programming
- Process functions and lists in Python
- Working with selected Python libraries
- Interactive interim project on best practice handling of work processes
- Object-oriented programming (OOP) with focus on classes and attributes
- Use inheritances for code reusability
- Advanced functions for simplifying classes
Portfolio Project
- Application of libraries such as Pandas, NumPy and Matplotlib
- Development and evaluation of machine learning models using Scikit-Learn, TensorFlow or Keras
- Consolidate debugging skills to effectively fix errors in the code
- Use of Git and GitHub for version control and team collaboration
- Best practices for documenting code and projects to foster collaboration and meet industry standards
Are you interested?
With the Data Scientist training program, you will learn practical data skills and AI basics for a career start in a job with a future.
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FAQ
What sets StackFuel apart from other training providers?
Our training courses are developed and produced by our own team of data scientists and subject matter experts, who provide you as a participant with personal mentoring during the course. We not only focus on realistic and practical content, but also ensure that all your questions are answered in a personal exchange and thus guarantee your learning success.
Thanks to our "learning-by-doing" principle, you will learn in our interactive learning environment with realistic data sets and real business cases from the industry, preparing you perfectly for a successful career start in a data job.
Why is StackFuel the right choice for me?
With StackFuel, you can rely on a market leader with Germany's most innovative learning platform to develop your data skills in a practical way. In certified training programs, you learn online, flexibly and with 80 % of practical content.
This will enable you to make a lateral entry as a data analyst or data scientist and learn how to use data and the basics of artificial intelligence professionally. Your new data career starts with your online training at StackFuel.
How can data skills help me to start a new career?
Data has become an integral part of our (professional) lives. In almost all areas, data helps you to better understand facts and make more precise decisions. Data skills are the key to being able to use and interpret data correctly. Even though you may not realize it, you work with, interact with and generate data every day.
This data is becoming increasingly important for companies and is the basis for decisions and business models, which makes data professionals incredibly important for companies.