AI Programming Course with the SVILUPPATORE MIGLIORE method
Leverage the power of Artificial Intelligence to transform how you build software. Integrate LLMs, Machine Learning and generative AI into your .NET applications
1-on-1 Mentor On YOUR code Measurable results
AI is no longer an experiment. It is a competitive advantage for companies that know how to integrate it into their products and processes.
But the difference between "using ChatGPT" and integrating AI into your own .NET applications is enormous. The first is a commodity. The second is a strategic asset your competitors do not have.
This programme is for .NET teams who want to integrate generative AI, LLMs and Machine Learning into their applications, not as a gimmick, but as core functionality that generates real business value.
What you learn: the complete programme
2 phases, 8 modules of intensive training on YOUR code.
2 phases, 8 modules of intensive training on YOUR code.
PHASE 1: AI Foundations for Developers (Weeks 1-4)
- 1
AI for Developers: understand what you use before you use it
You do not need to become a data scientist to integrate AI into your .NET applications. But using LLMs without understanding how they work leads to costly choices and unreliable output. Here we build the technical foundation every .NET developer needs to make good decisions.
Programma
- Training, inference and fine-tuningHow AI models work and what that means for the technical decisions you make every day
- Transformer architectureHow GPT, Claude and Gemini work, it is not magic, it is a system you can use consciously
- Prompt engineeringHow to write prompts that produce reliable and repeatable output, reducing hallucinations
- Tokens, context and temperatureHow these parameters determine the quality, cost and behaviour of every API call
- Real cost of AI integrationHow to calculate token budgets, forecast API calls and compare providers
- When AI adds valueHow to identify genuine use cases and discard the hype that burns months of development
Risultato
You understand AI as a developer. You know what is possible, what it costs and when it makes sense to integrate it into your product.
- 2
Semantic Kernel: orchestrate AI with structured C# code
Semantic Kernel is the Microsoft SDK for orchestrating AI in .NET. Calling an LLM with concatenated strings is a prototype, not a product: Semantic Kernel transforms calls into structured, maintainable functionality. Here you learn to use it to build AI logic that lasts.
Programma
- Multi-provider configurationHow to connect OpenAI, Azure OpenAI, Ollama and local models from a single unified API
- C# plugins for AIHow to create C# functions that AI can invoke autonomously, turning your business logic into tools
- Planner for complex tasksHow to make AI decompose a goal into steps and execute them in sequence
- Memory with embeddingsHow to add persistent context to conversations without blowing up the token budget
- Chat history managementHow to accumulate context in a controlled way avoiding wasted tokens
- Filters for security and loggingHow to intercept AI input and output at a single centralised point
Risultato
AI orchestrated in .NET with structured patterns. Your applications call LLMs reliably, not with concatenated strings and hope.
- 3
Azure OpenAI: enterprise production with SLA and compliance
Azure OpenAI is the enterprise version of OpenAI with European compliance, SLA and data residency. For enterprise applications with sensitive data, Azure OpenAI has no equal in terms of reliability and regulatory compliance. Here you learn to use it for real production scenarios with real users.
Programma
- Chat Completion with GPT-4How to use system prompts and role messages for consistent, controlled output in production
- Embeddings for semantic searchHow to vectorise text to build enterprise chatbots and search systems
- Function CallingHow to make AI call your APIs, update databases and send emails, not just answer questions
- DALL-E and WhisperHow to integrate image generation and audio transcription into your .NET applications
- API call resilienceHow to handle rate limiting and retry policies to avoid timeouts that block users
- Content filtering on AzureHow to automatically block inappropriate output guaranteeing GDPR compliance
Risultato
Enterprise-grade generative AI. OpenAI calls are secure, resilient and compliant with company policies. You are ready for production.
- 4
ML.NET: native machine learning without Python
Not everything requires an LLM. For classification, anomaly detection and numerical prediction, ML.NET is the native .NET solution. No Python, no cloud, no dedicated data scientist: everything inside your existing .NET project. Here you learn when to use it and how to deploy it in production.
Programma
- Complete ML.NET pipelineHow to load data, train, evaluate and deploy a model without leaving .NET
- Automatic classificationHow to classify documents, emails and support tickets with a model trained on your data
- Predictive regressionHow to forecast numerical values like future demand, customer risk or delivery times
- Anomaly detectionHow to detect fraud, machine failures and abnormal behaviour before they cause damage
- Model Builder in Visual StudioHow to train guided models without writing ML code, in a few clicks
- Deployment as a .NET APIHow to integrate the model as a service with inference in milliseconds
Risultato
Native machine learning in .NET. You classify, predict and detect anomalies without Python, without cloud and without a dedicated data scientist.
PHASE 2: Advanced Scenarios and Production (Weeks 5-8)
- 5
RAG Pattern: AI that answers from your company data
The RAG pattern allows AI to answer questions about your company documents, knowledge base and technical manuals. It is the most requested use case, but building it badly produces chatbots that invent answers worse than not having it at all. Here you learn the correct architecture from indexing to verifiable responses.
Programma
- Complete RAG architectureHow to index documents, retrieve relevant chunks and generate accurate, verifiable responses
- Choosing the vector databaseHow to decide between Qdrant, ChromaDB and Azure AI Search based on data volume and requirements
- Optimal chunking strategyHow to split documents to maximise answer relevance, not at random
- Embedding model for language and domainHow to choose the right model for your language and specialist sector
- Semantic rankingHow to optimise result relevance to get the best answers, not just the first ones found
- End-to-end enterprise chatbotHow to build a system that answers from your internal knowledge base like an always-available expert
Risultato
Enterprise chatbots that answer from your data. AI does not invent: it searches your documents and generates accurate, verifiable responses.
- 6
AI-Assisted Development: multiply team productivity
AI is not just useful in products: it also accelerates development itself. A team that uses GitHub Copilot superficially saves minutes; one that uses it well saves days. Here you learn the advanced techniques that make a real difference to productivity.
Programma
- Advanced GitHub CopilotHow to generate entire methods, tests and refactoring with precise prompts, not just autocomplete
- AI-assisted code reviewHow to find bugs, code smells and architectural violations before the merge
- Automatic test generationHow to go from zero coverage to a complete suite starting from your public methods
- Automated documentationHow to keep XML comments, README and API docs up to date without manual effort
- AI-assisted migrationHow to accelerate conversion from VB to C# and from .NET Framework to .NET 10
- Verifying AI outputHow to recognise when to trust the result and when to verify manually
Risultato
Multiplied productivity. The team writes less boilerplate, receives more feedback and migrates legacy code in less time.
- 7
AI Governance and Quality: total control over output
AI in production without governance is a concrete legal and reputational risk. A hallucination shown to a user is worth zero technical excuses: the responsibility is yours as the developer. Here you learn to control output, costs and compliance systematically.
Programma
- AI output validationHow to verify responses before showing them to users, eliminating dangerous hallucinations
- Guardrails and topic restrictionHow to implement content filtering so AI only responds on what it should
- Bias detection and mitigationHow to guarantee fair responses compliant with company and legal policies
- Token monitoring and budget alertsHow to keep AI costs under control at all times without billing surprises
- AI call audit trailHow to trace every response to make it verifiable and compliant with regulatory requirements
- GDPR and AIHow to comply with the regulation by deciding what to send to providers and what to keep on-premise
Risultato
Controlled and compliant AI. Output is validated, costs are under control and compliance is guaranteed. Ready for enterprise use.
- 8
Production and Scaling: from prototype to system with thousands of users
An AI prototype that works in a demo is easy to build. An AI system in production with thousands of concurrent users is something else entirely: latency, costs and failover require specific architectures. Here you learn everything the tutorials do not show.
Programma
- Scaling on containersHow to deploy AI systems with automatic scaling from 10 to 10,000 users without changing code
- Intelligent LLM cachingHow to reduce costs by 60-80% by avoiding identical calls to the provider
- Background jobs for AIHow to process heavy tasks in a queue without making the user wait in the foreground
- AI monitoring in productionHow to track latency, error rate and response quality with automatic alerts
- A/B testing between modelsHow to measure the impact of different prompts and models before applying them to all users
- Fallback strategyHow to guarantee system operation with graceful degradation when AI does not respond
Risultato
AI system in production that scales. Performance is monitored, costs are optimised and fallbacks are handled. From prototype to enterprise product.
Who this programme is for
CTO who wants AI as a competitive advantage
You want to integrate AI into your products but do not know where to start. You are looking for a pragmatic approach, not academic, AI that generates real business value.
.NET developer who wants to integrate AI
You want to master AI integration in .NET to build intelligent features: chatbots, predictive analytics, automation, virtual assistants.
Team that wants to add AI to existing products
You have .NET applications in production and want to enrich them with AI features without rewriting them. Semantic Kernel, RAG, LLM integration, all with C#.
Who is Matteo Migliore
What professionals who have followed the programme say
Those who study with Matteo have the opportunity to access a very meaningful and concrete experience, entering the world of software development with a reliable and competent guide.
His training is a real opportunity for young people who want to pursue a career as a software architect.
I definitely recommend him, especially for the professionalism he has always shown and his ability to explain numerous topics that are normally not covered in these types of courses.
The WPF course I had the fortune to take with Matteo Migliore literally opened up an incredible world for me, allowing me to acquire all the techniques that will enable me to tackle increasingly important projects.
I definitely recommend Matteo for the technical content and the experience he brings; the training journey was also rich in anecdotes where he shared his experiences going all the way back to when he was a child.
I recommend Matteo's course especially to beginners and anyone who needs to learn how to structure an application, because this way you can start already with a correctly built architecture.
One difference I notice compared to other courses is a great passion for training, understood in a very broad sense. It is a mission for them, and beyond the specific WPF course topics, I always find tips and suggestions on cross-cutting subjects like design, software control and testing — which gives me something extra in my overall development approach.
Often there is little time and great difficulty managing on your own the issues you encounter daily, and if you tend to limit yourself to your own knowledge you end up stuck in your own mistakes.
Going back over things I had studied at university, explained step by step in a new language I had not studied before, was extremely useful.
I turned to our consultant, Matteo Migliore, to enter this new world.
Thanks to the course I learned a programming approach built in a much more sensible way than what I was doing before.
I recommend Matteo because he is a very competent person who loves his work and cares about helping others, making them more productive and more capable of mastering technology.
What I liked most was the new management of the project structure: separating the UI from the design layer, and in particular not writing code directly in the UI but structuring it properly.
Matteo doesn't simply read from a pre-prepared script but is able to go deeper into syntactic elements and design patterns, perfectly following the needs of whoever is learning.
Investment and programme
Programmes are tailored to the number of participants, duration and project complexity.
Fill in the form to receive the complete programme and a personalised quote based on your specific needs.
Individual Programme
1 participant, personalised mentoring
- 8 complete modules
- Biweekly live 1-to-1 sessions
- Platform access for 12 months
- Continuous chat support
Team Programme
2-3 participants, department transformation
- 8 complete modules
- AI integration on company codebase
- AI reference architecture
- Platform access for 12 months for all
Intensive Workshop
1-2 days on specific topics
- Focus on Semantic Kernel, RAG or LLM integration
- Up to 5 participants
- Complete training materials
- Follow-up session at 30 days
Ready to integrate AI into your .NET applications?
Fill in the form and receive all the information about the AI programme for .NET developers. We analyse your scenario and the best path for you or your team.
Free analysis We assess the AI opportunities for your applications
Talk to one of our tutors Not a salesperson, but a real expert who will guide you
Practical advice You receive useful guidance even if you decide not to continue