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AI Modeling Bootcamp
New
Bootcamp

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Aug 25, 2025
You’ve got IT experience. Now it’s time to level up. In our AI Modeling Bootcamp, you’ll learn how to build and train real-world AI models – exactly the kind of skills today’s companies are hiring for.
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Course content

All content at a glance

Become a Machine Learning Specialist – in the neue fische AI-Powered Marketing Bootcamp

The AI Modeling Bootcamp is a 6-week full-time curriculum designed for job seekers and employees with IT/software development background looking to expand their skills in artificial intelligence, data modeling, and machine learning.

Career change to AI Modeling : These are the requirements

Ideally, you already have some IT experience – but most importantly, you're curious about artificial intelligence, data, and modern technologies. Whether you come from software development, data science, or a related field: if you think analytically, enjoy learning new things, and want to level up your tech skills, this bootcamp is a great fit for you. And if you're missing the right equipment: we're happy to help.


Keyfacts

  • Full-Time: 6 Weeks (Mo – Fr, 08.30 – 18.30h)
  • Participants: approx. 12
  • Location: Remote
  • Language: German
  • Future Job: Data Scientist, AI Engineer, Machine Learning Specialist

Tech Stack

Tensorflow
Jupyter Notebooks
Scikit-Learn
Pandas
Github
Python
Tensorflow
Scikit
Download free info material

The course content, application process, pricing & funding all in one pdf.

Starting dates

The next dates: AI Modeling Bootcamp

Our AI Modeling Bootcamp runs full-time Monday through Friday for 6 weeks.

Aug
25th Aug6th Oct ‘26

Full-Time

Remote

German

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Curriculum

This is what you learn in our AI-Modeling Bootcamp

People working on laptops in a classroom
Pandas
Phyton
Github
NumPy
Matplotlib

In your first week, you'll build a solid foundation for your AI journey. You'll learn to navigate the Bash command line, work with Git & GitHub, and refresh your Python skills using NumPy, Pandas, and Matplotlib. You'll explore and visualize data, formulate initial hypotheses, and conduct exploratory data analysis – culminating in a team-based mini project.

People working on laptops in an office.
Scikit-Learn
Feature Engineering

You’ll dive into machine learning with a focus on classification problems. Alongside an introduction to AI, ML, and DL concepts, you’ll explore supervised learning techniques. Using scikit-learn, you’ll build your first classification models, optimize them through feature engineering and hyperparameter tuning, and evaluate them with industry-standard metrics. Your project: predicting Titanic passenger survival.

Person using laptop with video conference in office
Phyton
Gradient Descent
Overfitting
Time Series

This phase focuses on regression techniques in supervised learning. You'll work with time series data, apply linear regression and regularization, and explore techniques to avoid overfitting. You'll also dive into gradient descent as a core machine learning principle and refine your Python function skills. All of this is applied in a project forecasting bikeshare demand.

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XGBoost
K-Means
PCA

In week 4, you’ll deepen your knowledge with decision trees, random forests, and ensemble methods like bagging and boosting (including XGBoost). You'll explore model comparison strategies and handle imbalanced datasets. On the unsupervised side, you'll implement clustering techniques like K-means and hierarchical clustering, and apply PCA for dimensionality reduction – all tied into real-world business cases.

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Tensorflow
Keras

This week is all about deep learning. You’ll explore the structure of artificial neural networks and implement them using TensorFlow and Keras. Key topics include backpropagation, training strategies, and convolutional neural networks. With transfer learning, you'll build your own image classification model based on pre-trained architectures.

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TF-IDF
BERT
GPTs
Langchain

In your final week, the focus shifts to language and modern large language models. You’ll explore classic NLP techniques like tokenization, TF-IDF, and sentiment analysis, and dive into LLMs like BERT and GPT. You'll experiment with RAG, fine-tuning, and libraries like LangChain to build your own AI agents – such as an intelligent FAQ bot or analysis tool.

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Re- & Upskilling

To the education voucher
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These steps are important to take the course

Whether you have dropped out of university, are on short-time work, are threatened with unemployment or have lost your job, your time will be well spent if you become more digital. Please note that the process of getting an education voucher from the employment agency can take a relatively long time. We therefore advise you to follow the procedure below.
Step 1

Register as a jobseeker early

In order to receive your education voucher for your retraining from the employment agency, the Jobcenter or the Labour Office, you should register as a jobseeker at an early stage. It is therefore very important that you first make an appointment with the relevant office. It's best to do it now!

Step 2

Get your educational offer from us

The next step on the way to your IT training voucher is quick and easy: Contact us! We will create an official training offer for you that you can then submit to the employment agency, the Jobcenter or the employment office.

Step 3

Apply for the training voucher

Now it's down to the nitty-gritty: With the training offer we have created, you now go back to your responsible office and apply for your training voucher. As soon as it is approved, you can start your new career with us. We look forward to seeing you!

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Final projects of our alumni

Final projects at neue fische & SPICED

4,500 alumni have already completed a final project with us. You too will complete one that you can present to your future employers. Discover which projects already exist.

The bootcamp is designed for job seekers or professionals with a background in IT, software development, or data science who want to deepen their knowledge in artificial intelligence and machine learning.

Ideally, you have a degree in a STEM field or relevant practical experience in software development. Basic knowledge of Python and statistics is a plus, but not required

You’ll gain hands-on experience in building and training AI models – from classical machine learning to deep learning and advanced LLM applications like GPT or RAG. Tools include scikit-learn, Keras, TensorFlow, and LangChain.

After completing the program, you’ll be prepared for roles in AI Engineering, Data Science, or MLOps – such as Machine Learning Engineer, AI Developer, or Data Analyst with a focus on AI.


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What are you waiting for?

Our Student Admissions team is happy to talk with you, answer your questions, and advise you. Get in touch with us!

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