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The activity of programming, regardless of the programming language used, will change fundamentally in the coming years due to the possibility of using AI as a tool.
This AI training course uses examples and various tools to show how AI systems can support this and what added value can be gained from them. This involves both the creation of code and its optimization as well as documentation.
-
Course Contents
-
- Fundamentals: AI, machine learning, and language processing
- Modern AI functions: Working with your own data and documents
- Effective prompts and AI control
- Getting started with programming using Python and VS Code
- GitHub Copilot: Using AI as a programming assistant
- Advanced settings and tools for professionals
- AI in everyday coding: Automatic code completion and testing
- Methods for code improvement and documentation
- Dealing with errors and frustration while learning
- Automating daily tasks on the computer
The detailed digital documentation package, consisting of an e-book and PDF, is included in the price of the course.
Premium Course Documents
In addition to the digital documentation package, the exclusive Premium Print Package is also available to you.
- High-quality color prints of the ExperTeach documentation
- Exclusive folder in an elegant design
- Document pouch in backpack shape
- Elegant LAMY ballpoint pen
- Practical notepad
The Premium Print Package can be added during the ordering process for € 150,- plus VAT (only for classroom participation).
-
Target Group
-
This AI training course is aimed at programmers and career changers in the field of software development who want to use generative AI to automate routine programming tasks.
-
Knowledge Prerequisites
-
Basic knowledge of any programming language is an advantage.
-
Course Objective
-
You will gain in-depth experience in the day-to-day use of AI in software development. You will learn first steps and best practices. You will learn how to master typical challenges and structure larger projects. After the course, you will also be able to clearly communicate the benefits and pitfalls of the technology.
-
Complementary and Continuative Courses
- AI Programming Advanced – Agentic AI and API Use Cases
| 1 | Einführung zu künstlicher Intelligenz |
| 1.1 | KI-Fluch oder Segen? |
| 1.1.1 | Was ist denn eigentlich KI? |
| 1.1.2 | Geschichte von KI |
| 1.2 | Machine Learning |
| 1.2.1 | Supervised Learning |
| 1.2.2 | Unsupervised Learning |
| 1.2.3 | Reinforcement Learning |
| 1.3 | Natürliche Sprachverarbeitung |
| 1.3.1 | Tokenisierung |
| 1.3.2 | Vektorisierung und Embeddings |
| 1.4 | Allgemeine Künstliche Intelligenz |
| 1.4.1 | Wann kommt die AGI? |
| 2 | Neuronale Netze und die Transformer Architektur |
| 2.1 | Einführung in neuronale Netze |
| 2.1.1 | Biologisches vs. künstliches Neuron |
| 2.1.2 | Mehrschichtige neuronale Netze |
| 2.1.3 | Training und Backpropagation |
| 2.2 | Entwicklungsschritte zu ChatGPT |
| 2.2.1 | Rekurrente neuronale Netze (RNN) |
| 2.2.2 | LSTM & GRU |
| 2.3 | Transformer: Attention-Mechanismus |
| 2.3.1 | Die Evolution der Sequenzmodelle |
| 3 | Das GPT-Modell |
| 3.1 | Was ist GPT? |
| 3.2 | Training von GPT |
| 3.2.1 | Stufe 1: Pre-Training |
| 3.2.2 | Stufe 2: Supervised Finetuning |
| 3.2.3 | Stufe 3 & 4 Reinforcement Learning |
| 3.3 | Alternativen zu GPT |
| 3.3.1 | Vergleich der Modelle |
| 3.3.2 | Antwortenvergleich der Modelle |
| 3.3.3 | Benchmarks für den Leistungsvergleich |
| 3.3.4 | GPT4ALL - Open Source Modelle lokal nutzen |
| 3.4 | Anwendungen von GPT |
| 3.4.1 | Microsoft Office365 Copilot |
| 3.4.2 | Github Copilot |
| 4 | Die Nutzung von ChatGPT |
| 4.1 | Die grafische Oberfläche zu ChatGPT |
| 4.1.1 | Textgenerierung & -Übersetzung |
| 4.1.2 | Formulierung von Texten |
| 4.1.3 | Brainstorming |
| 4.2 | Programmieren mit ChatGPT |
| 4.2.1 | Erste Schritte als Programmierer |
| 4.2.2 | Codeanalyse und Fehlerkorrektur |
| 4.2.3 | Wahl eines Moduls |
| 4.3 | Best Practices und Prompt Engineering |
| 4.3.1 | Grundlegende Vorgehensweisen |
| 4.3.2 | Chain of Thought |
| 4.3.3 | Zero- und Few-Shot Prompts |
| 4.3.4 | Benutzerdefinierte Anweisungen |
| 4.3.5 | ChatGPT als Prompt Creator |
| 4.4 | ChatGPT Plus, Enterprise und API |
| 4.4.1 | Plugins |
| 4.4.2 | API und Playground |
| 4.4.3 | ChatGPT-API |
| 4.4.4 | Playground |
| 4.5 | Grenzen von ChatGPT |
| 5 | Ethik und gesellschaftliche Auswirkungen |
| 5.1 | Technologischer Fortschritt |
| 5.2 | Regulierungen in Europa |
| 5.3 | Regulierungen in Amerika |
| 5.4 | Datenschutz und Privatsphäre |
| 5.5 | Ethik und Soziale Gerechtigkeit |
| 5.6 | Änderungen der Arbeitswelt |
| 6 | Zukunftsperspektiven von KI |
| 6.1 | Artificial General Intelligence |
| 6.1.1 | Unklarheit des Begriffs |
| 6.1.2 | Einschätzung der Experten |
| 6.2 | Hardware als Treiber für KI-Innovation? |
| 6.2.1 | Quantencomputer und KI |
| 6.3 | Überblick über KI-Trends |
| 6.3.1 | Abschließende Worte |
-
Classroom training
- Do you prefer the classic training method? A course in one of our Training Centers, with a competent trainer and the direct exchange between all course participants? Then you should book one of our classroom training dates!
-
Online training
- You wish to attend a course in online mode? We offer you online course dates for this course topic. To attend these seminars, you need to have a PC with Internet access (minimum data rate 1Mbps), a headset when working via VoIP and optionally a camera. For further information and technical recommendations, please refer to.
-
Tailor-made courses
-
You need a special course for your team? In addition to our standard offer, we will also support you in creating your customized courses, which precisely meet your individual demands. We will be glad to consult you and create an individual offer for you.
You can find the complete description of this course with dates and prices ready for download at as PDF.-
The activity of programming, regardless of the programming language used, will change fundamentally in the coming years due to the possibility of using AI as a tool.
This AI training course uses examples and various tools to show how AI systems can support this and what added value can be gained from them. This involves both the creation of code and its optimization as well as documentation.
-
Course Contents
-
- Fundamentals: AI, machine learning, and language processing
- Modern AI functions: Working with your own data and documents
- Effective prompts and AI control
- Getting started with programming using Python and VS Code
- GitHub Copilot: Using AI as a programming assistant
- Advanced settings and tools for professionals
- AI in everyday coding: Automatic code completion and testing
- Methods for code improvement and documentation
- Dealing with errors and frustration while learning
- Automating daily tasks on the computer
The detailed digital documentation package, consisting of an e-book and PDF, is included in the price of the course.
Premium Course Documents
In addition to the digital documentation package, the exclusive Premium Print Package is also available to you.
- High-quality color prints of the ExperTeach documentation
- Exclusive folder in an elegant design
- Document pouch in backpack shape
- Elegant LAMY ballpoint pen
- Practical notepad
The Premium Print Package can be added during the ordering process for € 150,- plus VAT (only for classroom participation).
-
Target Group
-
This AI training course is aimed at programmers and career changers in the field of software development who want to use generative AI to automate routine programming tasks.
-
Knowledge Prerequisites
-
Basic knowledge of any programming language is an advantage.
-
Course Objective
-
You will gain in-depth experience in the day-to-day use of AI in software development. You will learn first steps and best practices. You will learn how to master typical challenges and structure larger projects. After the course, you will also be able to clearly communicate the benefits and pitfalls of the technology.
-
Complementary and Continuative Courses
- AI Programming Advanced – Agentic AI and API Use Cases
| 1 | Einführung zu künstlicher Intelligenz |
| 1.1 | KI-Fluch oder Segen? |
| 1.1.1 | Was ist denn eigentlich KI? |
| 1.1.2 | Geschichte von KI |
| 1.2 | Machine Learning |
| 1.2.1 | Supervised Learning |
| 1.2.2 | Unsupervised Learning |
| 1.2.3 | Reinforcement Learning |
| 1.3 | Natürliche Sprachverarbeitung |
| 1.3.1 | Tokenisierung |
| 1.3.2 | Vektorisierung und Embeddings |
| 1.4 | Allgemeine Künstliche Intelligenz |
| 1.4.1 | Wann kommt die AGI? |
| 2 | Neuronale Netze und die Transformer Architektur |
| 2.1 | Einführung in neuronale Netze |
| 2.1.1 | Biologisches vs. künstliches Neuron |
| 2.1.2 | Mehrschichtige neuronale Netze |
| 2.1.3 | Training und Backpropagation |
| 2.2 | Entwicklungsschritte zu ChatGPT |
| 2.2.1 | Rekurrente neuronale Netze (RNN) |
| 2.2.2 | LSTM & GRU |
| 2.3 | Transformer: Attention-Mechanismus |
| 2.3.1 | Die Evolution der Sequenzmodelle |
| 3 | Das GPT-Modell |
| 3.1 | Was ist GPT? |
| 3.2 | Training von GPT |
| 3.2.1 | Stufe 1: Pre-Training |
| 3.2.2 | Stufe 2: Supervised Finetuning |
| 3.2.3 | Stufe 3 & 4 Reinforcement Learning |
| 3.3 | Alternativen zu GPT |
| 3.3.1 | Vergleich der Modelle |
| 3.3.2 | Antwortenvergleich der Modelle |
| 3.3.3 | Benchmarks für den Leistungsvergleich |
| 3.3.4 | GPT4ALL - Open Source Modelle lokal nutzen |
| 3.4 | Anwendungen von GPT |
| 3.4.1 | Microsoft Office365 Copilot |
| 3.4.2 | Github Copilot |
| 4 | Die Nutzung von ChatGPT |
| 4.1 | Die grafische Oberfläche zu ChatGPT |
| 4.1.1 | Textgenerierung & -Übersetzung |
| 4.1.2 | Formulierung von Texten |
| 4.1.3 | Brainstorming |
| 4.2 | Programmieren mit ChatGPT |
| 4.2.1 | Erste Schritte als Programmierer |
| 4.2.2 | Codeanalyse und Fehlerkorrektur |
| 4.2.3 | Wahl eines Moduls |
| 4.3 | Best Practices und Prompt Engineering |
| 4.3.1 | Grundlegende Vorgehensweisen |
| 4.3.2 | Chain of Thought |
| 4.3.3 | Zero- und Few-Shot Prompts |
| 4.3.4 | Benutzerdefinierte Anweisungen |
| 4.3.5 | ChatGPT als Prompt Creator |
| 4.4 | ChatGPT Plus, Enterprise und API |
| 4.4.1 | Plugins |
| 4.4.2 | API und Playground |
| 4.4.3 | ChatGPT-API |
| 4.4.4 | Playground |
| 4.5 | Grenzen von ChatGPT |
| 5 | Ethik und gesellschaftliche Auswirkungen |
| 5.1 | Technologischer Fortschritt |
| 5.2 | Regulierungen in Europa |
| 5.3 | Regulierungen in Amerika |
| 5.4 | Datenschutz und Privatsphäre |
| 5.5 | Ethik und Soziale Gerechtigkeit |
| 5.6 | Änderungen der Arbeitswelt |
| 6 | Zukunftsperspektiven von KI |
| 6.1 | Artificial General Intelligence |
| 6.1.1 | Unklarheit des Begriffs |
| 6.1.2 | Einschätzung der Experten |
| 6.2 | Hardware als Treiber für KI-Innovation? |
| 6.2.1 | Quantencomputer und KI |
| 6.3 | Überblick über KI-Trends |
| 6.3.1 | Abschließende Worte |
-
Classroom training
- Do you prefer the classic training method? A course in one of our Training Centers, with a competent trainer and the direct exchange between all course participants? Then you should book one of our classroom training dates!
-
Online training
- You wish to attend a course in online mode? We offer you online course dates for this course topic. To attend these seminars, you need to have a PC with Internet access (minimum data rate 1Mbps), a headset when working via VoIP and optionally a camera. For further information and technical recommendations, please refer to.
-
Tailor-made courses
-
You need a special course for your team? In addition to our standard offer, we will also support you in creating your customized courses, which precisely meet your individual demands. We will be glad to consult you and create an individual offer for you.
You can find the complete description of this course with dates and prices ready for download at as PDF.