AI+ Architect™

Price
Net: 1.985,00 €
VAT.: 377,15 €

Duration
5 days

For companies and job seekers:
this course is 100% fundable!

Location

Course Language
English

Training Solutions
WalkIn^®

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New perspectives on AI-supported architectural processes provide fresh impetus for digital innovation. The text conveys an understanding of how technical concepts, automation, and creative problem-solving intertwine to design complex systems that are fit for the future.

Key topics

AI-based structuring of digital solutions.
Modeling data-driven workflows.
Use of modern AI tools for scalable architectures.
Quality by design in AI-supported environments.
Future trends in automation and GenAI.

Prerequisites:
Basic knowledge of IT concepts and an understanding of data-oriented working methods.

Target
audience: Professionals from the fields of technology, IT, consulting, and product development who want to deepen their strategic thinking about AI.

This creates a clear path to well-founded, future-oriented architectural approaches that combine modern AI skills with structured thinking and strengthen digital solutions
in the long term.

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Course content

Fundamentals of neural networks

Introduction to neural networks
Architecture of neural networks
Practical exercises: Implementation of a basic neural network

Neural network optimization

Tuning hyperparameters
Optimization algorithms
Regularization techniques
Hands-on: Hyperparameter tuning and optimization

Neural network architectures for NLP

Important NLP concepts
NLP-specific architectures
Practical exercises: Implementation of an NLP model

Neural network architectures for computer vision

Important concepts in computer vision
Computer vision-specific architectures
Hands-on: Building a computer vision model

Model evaluation and performance metrics

Model evaluation techniques
Improving model performance
Practical application: Evaluation and optimization of AI models

AI infrastructure and development

Infrastructure for AI development
Deployment strategies
Hands-on: Using an AI model

AI ethics and responsible AI design

Ethical considerations in AI
Best practices for responsible AI design
Hands-on: Analyzing ethical considerations in AI

Generative AI models

Overview of generative AI models
Generative AI applications in various fields
Hands-on: Exploring generative AI models

Research-based AI design

AI research techniques
Cutting-edge AI design
Hands-on: Analysis of AI research papers

Final project and course review

Presentation of the capstone project
Course review and future direction
Practical exercises: Development of the capstone project

Optional module: AI agents for architects

Understanding AI agents
Case studies
Practical exercises with AI agents

Your training will be 100% funded

Our funding schemes are available exclusively to participants who live or work in Germany. Funding is not available outside Germany.

For career starters, job seekers, career changers, startups, experienced professionals, those looking to advance their careers, specialists, etc.

The QCG program for everyone in the company

Further information

The education voucher for all job seekers

Further information

Frequently asked questions

Why is further training in AI architecture worthwhile?

Artificial intelligence is transforming professional fields. Those who design systems that work with AI ensure structure, efficiency, and sustainable digital solutions.

What prerequisites are needed for the AI+ Architect™ course?

Knowledge of IT, databases, programming, and cloud technologies is advantageous. Technical understanding is essential.

What are the typical contents of the AI+ Architect™ course?

Topics such as machine learning pipelines, data engineering, cloud platforms, model deployment, and AI strategies will be covered.

Which tools and platforms are used?

Modern cloud systems, AI frameworks, APIs, databases, and MLOps tools are used—all in a practical context.

Who is AI+ Architect™ suitable for?

Ideal for professionals with a technical background who want to plan, implement, or be responsible for AI solutions—in IT, data science, or engineering.

What career opportunities does the field of AI architecture offer?

AI architects are in demand in IT, industry, research, start-ups, and corporations. The role is future-proof and strategically important.

What is the difference between an AI engineer and an AI architect?

The architect plans and designs the overall system, while the engineer builds and integrates the models. Both roles complement each other.

How can you stay up to date in the field of AI architecture?

Through specialist portals, courses, certifications, online platforms, and regular practice with new tools and methods.

What tools are used in the course?

The following tools are used in a practical manner in the course: AutoGluon for automated machine learning, ChatGPT for text and analysis support, SonarCube for code quality testing, and Vertex AI for developing scalable AI models in the cloud.

Do you have any further questions? Please contact us.

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