Global Agentic AI and LLM Bootcamp is on May 16th, 17th and 18th 2025.
The 
Global LLM and Agentic AI Bootcamp
 is an immersive, hands-on program designed to equip participants with cutting-edge skills in 
Large Language Models (LLMs) and Agentic AI
. This intensive bootcamp covers everything from 
foundational concepts to real-world applications
, providing attendees with a deep understanding of 
model development, fine-tuning, and deployment
. Industry experts will lead interactive sessions, workshops, and case studies to ensure participants leave with actionable insights and practical experience.
Corporate:
Why you should send your employees to 
Global LLM and Agentic AI Bootcamp
?
Incorporating 
LLMs and Agentic AI
 into business operations is no longer optional—it's a necessity for staying competitive. This bootcamp enables organizations to:
Upskill teams in AI-driven automation, natural language processing, and intelligent agents.
Accelerate AI adoption by providing employees with practical, hands-on training.
Enhance productivity by leveraging LLMs for knowledge management, customer support, and internal tools.
Gain strategic insights into how LLMs are shaping industries and how to integrate them effectively.
Network with top AI professionals to foster collaboration and innovation
What Makes This Bootcamp Unique?:
Unlike traditional AI and big data training sessions, this bootcamp stands out by:
Focusing on real-world applications – Go beyond theory with hands-on coding exercises, implementation strategies, and live case studies.
Offering practical exposure – Work on end-to-end projects, including fine-tuning, inference optimization, and deploying AI-powered agents.
Providing exclusive industry insights – Learn from AI leaders who have successfully integrated LLMs into their organizations.
Hands-on with latest tools & frameworks – Gain experience with state-of-the-art libraries, APIs, and architectures that power AI innovation.
Who Should Attend:
Software Engineers & AI Developers – Looking to build and deploy LLM-powered applications.
Data Scientists & ML Engineers – Interested in fine-tuning and optimizing models for efficiency.
Startup Founders & Tech Executives – Seeking to integrate AI into products and services.
Researchers & Academics – Exploring the frontiers of language models and agentic AI.
Corporate Leaders & Product Managers – Wanting to understand the strategic impact of AI on business operations
Conference Location
SpringHill Suites by Marriott, 46333 Fremont Blvd, Fremont, CA 94538 ( 
Map
 )
Lab Requirements
Each student should bring their own 64bit laptop ( Windows 7/8 and Mac, Virtualization Enabled, Minimum 8GB Ram and Free 25GB-50GB hard disk ) with administrative privileges and wireless connectivity. If you have AMD laptop, it should be AMD-V enabled. If you have Intel laptop or Mac, it should support Intel-VTx. An extra USB drive of 16gb minimum will be handy if you want to use your personal USB drive for all files and images.
Refund Policy
No refunds will be given for cancellations
If you have any questions concerning 
Global LLM and Agentic AI Bootcamp
, please do not hesitate to contact 
events@globalbigdataconference.com
 or Call 408-400-3769
NOTE:
 
Agenda and speakers subject to change without notice
Day 1: Foundations of Generative AI
Morning Session (9:00 AM - 12:00 PM)
Introduction to Generative AI (9:00 - 10:15)
- Welcome and workshop overview
- What is generative AI?
- History and evolution of generative models
- Key differences between discriminative and generative models
- Current landscape of generative AI technologies
- Real-world applications and impact
Coffee Break (10:15 - 10:30)
Foundation Models and Architecture (10:30 - 12:00)
- Neural networks primer: essential concepts
- Transformer architecture explained
- Attention mechanisms and their importance
- Training methodologies: supervised, unsupervised, and reinforcement learning
- Understanding parameters, tokens, and context windows
- Brief overview of leading foundation models (GPT, Claude, LLaMA, etc.)
Lunch Break (12:00 - 1:00 PM)
Afternoon Session (1:00 PM - 5:00 PM)
Prompt Engineering Fundamentals (1:00 - 3:00)
- What is prompt engineering?
- Basic prompt structures and components
- Zero-shot and few-shot prompting
- Chain-of-thought and step-by-step reasoning
- Role-based prompting techniques
- System prompts vs. user prompts
Coffee Break (3:00 - 3:15)
Practical Workshop: Basic Prompt Engineering (3:15 - 5:00)
- Hands-on exercises with various LLMs
- Prompt templates and frameworks
- A/B testing different prompt strategies
- Best practices for consistent results
- Common pitfalls and how to avoid them
- Group exercise: solving real-world problems with effective prompts
Day 2: Advanced Techniques and Implementations
Morning Session (9:00 AM - 12:00 PM)
Advanced Prompt Engineering (9:00 - 10:30)
- Context management strategies
- Recursive prompting techniques
- Retrieval-augmented generation (RAG)
- Prompt chaining and workflows
- Evaluation metrics for prompt effectiveness
- Ethical considerations in prompt design
Coffee Break (10:30 - 10:45)
Embedding Models Deep Dive (10:45 - 12:00)
- Understanding vector embeddings
- How embedding models work
- Text embeddings vs. multimodal embeddings
- Leading embedding models compared (OpenAI, Cohere, BERT, etc.)
- Semantic search implementation
- Visualizing and analyzing embeddings
Lunch Break (12:00 - 1:00 PM)
Afternoon Session (1:00 PM - 5:00 PM)
Building RAG Systems (1:00 - 3:00)
- Architecture of retrieval-augmented generation
- Document processing and chunking strategies
- Vector databases (Pinecone, Weaviate, Chroma, etc.)
- Similarity search techniques
- Hybrid search approaches
- Evaluation metrics for RAG systems
Coffee Break (3:00 - 3:15)
Practical Workshop: Implementing a RAG System (3:15 - 5:00)
- Hands-on implementation of a simple RAG application
- Document ingestion and processing pipeline
- Building and querying a vector database
- Integrating search results with LLM generation
- Troubleshooting and optimization techniques
- Group exercise: developing custom RAG solutions for domain-specific use cases
Day 3: Advanced Topics and Production Deployment
Morning Session (9:00 AM - 12:00 PM)
Fine-tuning and Transfer Learning (9:00 - 10:30)
- When and why to fine-tune models
- Data preparation and cleaning techniques
- Fine-tuning methodologies and best practices
- Parameter-efficient fine-tuning (PEFT, LoRA, QLoRA)
- Evaluating fine-tuned models
- Cost-benefit analysis of fine-tuning vs. prompt engineering
Coffee Break (10:30 - 10:45)
Multimodal AI and Beyond Text (10:45 - 12:00)
- Introduction to multimodal AI systems
- Text-to-image models (DALL-E, Midjourney, Stable Diffusion)
- Image-to-text capabilities
- Video generation technologies
- Audio and speech models
- Multimodal prompt engineering techniques
Lunch Break (12:00 - 1:00 PM)
Afternoon Session (1:00 PM - 5:00 PM)
Production Deployment and MLOps (1:00 - 2:30)
- LLM application architectures
- Model serving infrastructure
- Scaling considerations and optimization
- Monitoring and observability
- Caching strategies
- Cost management and optimization
- Security and privacy considerations
Coffee Break (2:30 - 2:45)
AI Agents and Autonomous Systems (2:45 - 4:00)
- AI agent frameworks and architectures
- Tool use and function calling
- Planning and reasoning capabilities
- Multi-agent systems
- Memory and context management
- Evaluation frameworks for agent systems
Workshop Conclusion and Future Directions (4:00 - 5:00)
- Recap of key concepts and learnings
- Emerging trends in generative AI
- Resources for continued learning
- Q&A session
- Feedback collection
- Closing remarks
Pre-Workshop Requirements
Technical Requirements
- Basic programming knowledge (Python preferred)
- Laptop with internet connection
- Development environment setup (instructions will be provided)
- API keys for various AI services (optional, but recommended)
Recommended Pre-Reading
- Introduction to machine learning concepts
- Basic neural network principles
- Python programming fundamentals (if needed)
Post-Workshop Resources
- Workshop slides and materials
- Code repositories and examples
- Recommended reading list
- Community forum access
- Certificate of completion
Information Source: Global Big Data Conference | eventbrite

Alameda County

United States

Fremont

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