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Course Outline
Introduction to Open-Source LLMs
- Overview of DeepSeek, Mistral, LLaMA, and other open-source models
- How LLMs work: Transformers, self-attention, and training
- Comparing open-source LLMs vs. proprietary models
Fine-Tuning and Customizing LLMs
- Data preparation for fine-tuning
- Training and optimizing LLMs using Hugging Face
- Evaluating model performance and bias mitigation
Building AI Agents with LLMs
- Introduction to LangChain for AI agent development
- Designing agent-based workflows with LLMs
- Memory, retrieval-augmented generation (RAG), and action execution
Deploying LLM-Based AI Agents
- Containerizing AI agents with Docker
- Integrating LLMs into enterprise applications
- Scaling AI agents with cloud services and APIs
Security and Compliance in Enterprise AI
- Ethical considerations and regulatory compliance
- Mitigating risks in AI-driven automation
- Monitoring and auditing AI agent behavior
Case Studies and Real-World Applications
- LLM-powered virtual assistants
- AI-driven document automation
- Custom AI agents for enterprise analytics
Optimizing and Maintaining LLM-Based Agents
- Continuous model improvement and updating
- Deploying monitoring and feedback loops
- Strategies for cost optimization and performance tuning
Summary and Next Steps
Requirements
- Strong understanding of AI and machine learning
- Experience with Python programming
- Familiarity with large language models (LLMs) and natural language processing (NLP)
Audience
- AI engineers
- Enterprise software developers
- Business leaders
21 Hours
Delivery Options
Private Group Training
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- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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