Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training Semantic Kernel - Developing Intelligent AI Agents training are: Mastery of C# or Python, AI basics, experience with OpenAI/Azure AI APIs. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Semantic Kernel - Developing Intelligent AI Agents training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training Semantic Kernel - Developing Intelligen... | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Training Semantic Kernel - Developing Intelligent AI Agents training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Training Semantic Kernel - Developing Intelligent AI Agents training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training Semantic Kernel - Developing Intelligent AI Agents training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training objectives

Master Semantic Kernel to orchestrate professional AI agents

Develop advanced plugins and skills in enterprise settings

Implement intelligent memory and planning management

Design AI applications connected to multiple APIs

Optimize and deploy certified Semantic Kernel solutions

Acquire generative AI skills for complex projects

Training program

Module 1Advanced Fundamentals of Semantic Kernel

Configuration of Semantic Kernel environment .NET/Python. Review of kernels and pipelines. Creation of custom native functions. Integration of Azure/OpenAI LLM models. Hands-on enterprise case. Initialization of capstone project AI agent. Prompt optimization exercises. Kernel unit tests. Advanced debugging. Preparation for complex skills.

Module 2Developing Plugins and Skills in Semantic Kernel

Design of native plugins and HTTP connectors. Implementation of advanced semantic skills. Dynamic parameter management. Hands-on RAG concrete cases. Integration of external tools like GitHub Copilot. Professional chaining skills exercises. Capstone project: intelligent search skill. Performance validation. Enterprise best practices. Local plugin deployment.

Module 3Memory and Planning Management in Semantic Kernel

Implementation of volatile/persistent memory. Configuration of vector stores Pinecone/Chroma. Sequential hierarchical planning. Hands-on multi-step agents. Enterprise data analysis exercises. Capstone project: conversational memory. Embedding optimization. Hybrid search integration. Scalability tests. Validated professional skills.

Module 4Orchestrating Agents with Semantic Kernel

Creation of autonomous multi-agents. Coordination via advanced planners. Intelligent error handling and retries. Hands-on enterprise chatbot scenarios. Professional decision-making agents exercises. Capstone project: AI agents orchestra. OAuth security integration. OpenTelemetry trace monitoring. Deployment best practices. Skills validation.

Module 5Deployment and Optimization of Semantic Kernel

Deployment on Azure/AWS with Docker containers. Scaling Semantic Kernel applications. LLM cost monitoring. Hands-on latency optimization. Production concrete cases exercises. Finalization of complete capstone agent project. Security audit. CI/CD with GitHub Actions. Enterprise performance evaluation. Skills certification delivery. Post-training support.