Advanced LLM Systems Bootcamp

---

---

🔗 Register Now: https://forms.gle/kPfbRBTgU1xwTNFm6

The Department of Data Science, Geethanjali College of Engineering and Technology, in association with the IEEE Computational Intelligence Society (CIS) Student Branch Chapter and IEEE Student Branch GCET, proudly presents a 5-Day Intensive Bootcamp on Advanced LLM Systems.

This bootcamp is designed to provide participants with structured, hands-on exposure to modern Large Language Model (LLM) ecosystems, focusing on practical system design rather than a theoretical overview alone. The program introduces students to the architecture, optimization, and deployment of real-world AI systems built using contemporary LLM frameworks.

Unlike conventional introductory sessions, this bootcamp emphasizes applied learning through guided implementation, problem-solving, and system-level understanding aligned with current industry and research practices.

Participants will gain exposure to:

• Foundations of Large Language Models and Transformer Architecture  
• Advanced Prompt Engineering methodologies  
• Retrieval-Augmented Generation (RAG) system design  
• Agentic AI workflows and tool integration  
• Evaluation, optimization, and deployment of LLM-based applications  
• Hands-on development sessions guided by domain experts

The program aims to prepare students for emerging AI roles by bridging the gap between academic concepts and production-level AI system development.

👨‍🏫 Resource Persons:

Dr. Teja Santosh Dandibhotla  
Professor, Department of CSE, CVR College of Engineering

Mr. N.N.S.S.S. Adithya  
Assistant Professor, Department of CSE, CVR College of Engineering

Dr. Venkateswara Rao Kagita  
Assistant Professor, Department of CSE, National Institute of Technology (NIT) Warangal

This bootcamp is ideal for students interested in Artificial Intelligence, Machine Learning, Generative AI, research-oriented development, and next-generation intelligent systems.

 

🔷 REGISTRATION DETAILS

🎟️ Registration is mandatory for participation in the bootcamp.

Participants are requested to complete the registration form using the link below:

🔗 Registration Form:
https://forms.gle/kPfbRBTgU1xwTNFm6

📌 Important Instructions:
• Limited seats available — selection based on confirmation.
• Ensure correct details while filling the form.
• Only registered participants will be allowed to attend.
• Attendance is mandatory for all 5 days.

✅ Confirmation details and further communication will be shared via official channels.

---

---

---

---

📘 BOOTCAMP AGENDA — ADVANCED LLM SYSTEMS

The bootcamp follows a structured progression from foundational concepts to real-world system deployment, ensuring participants develop both conceptual clarity and implementation capability.

────────────────────────

📅 Day 1 — Foundations of LLM Systems
• Evolution of Language Models and Generative AI
• Introduction to Transformer Architecture
• Tokenization Techniques & Embedding Representations
• Training Paradigms and Fine-Tuning Concepts
• Understanding how modern LLMs operate internally

Outcome:
Participants will understand the core building blocks behind modern Large Language Models.

────────────────────────

📅 Day 2 — Prompt Engineering & Optimization
• Principles of Effective Prompt Design
• Zero-shot, One-shot, and Few-shot Learning
• System Prompts and Role-based Interaction Design
• Chain-of-Thought Reasoning
• Techniques to Reduce Hallucinations and Improve Reliability

Outcome:
Students learn how to control and optimize LLM behavior through structured prompting.

────────────────────────

📅 Day 3 — Retrieval-Augmented Generation (RAG)
• Introduction to Retrieval Systems
• Embeddings and Semantic Similarity Search
• Vector Databases and Indexing Concepts
• Designing End-to-End RAG Pipelines
• Data Security and Knowledge Grounding

Outcome:
Participants build knowledge-aware AI systems capable of using external data sources.

────────────────────────

📅 Day 4 — Agentic AI & Tool Integration
• AI Agent Architecture Fundamentals
• Function Calling and Tool Usage
• Connecting LLMs with APIs and External Systems
• Multi-Agent Collaboration Workflows
• Practical Agent Development Patterns

Outcome:
Students understand how autonomous AI systems are designed and orchestrated.

────────────────────────

📅 Day 5 — Deployment & Real-World Systems
• API Integration and System Packaging
• Evaluating LLM Applications (Metrics & Testing)
• Performance Optimization Strategies
• Deployment Considerations and Scaling Basics
• Final Mini Project / Demo Presentation

Outcome:
Participants experience the lifecycle of deploying production-ready LLM applications.

────────────────────────

🎯 Learning Approach:
• Concept → Demonstration → Hands-on Implementation
• Guided coding sessions
• Interactive discussions with resource persons
• Practical system-building exposure

---

📌 Organized by IEEE CIS SB Chapter & IEEE SB GCET  
📌 Department of Data Science, Geethanjali College of Engineering and Technology  
📌 NAAC ‘A+’ Accredited Institution

This bootcamp aims to equip students with practical knowledge in advanced AI and LLM system development through expert-led sessions and hands-on learning.

✨ Empowering students with future-ready AI skills.

---

5-Day Boot Camp on Advanced LLM Systems

The 5-Day Boot Camp on Advanced LLM Systems provided hands-on training in AI, Machine Learning, and Large Language Models. Covering neural networks, transformers, RAG, and fine-tuning techniques, the program combined theory with practical implementation. It enhanced participants’ skills in building, optimizing, and deploying real-world AI solutions.

1.25 MiB

---