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BEGIN:VEVENT
DTSTAMP:20260330T122642Z
UID:0118A708-442E-4D8F-96C1-3D0A46E2472A
DTSTART;TZID=Asia/Kolkata:20260309T090000
DTEND;TZID=Asia/Kolkata:20260313T153000
DESCRIPTION:🔗 Register Now: https://forms.gle/kPfbRBTgU1xwTNFm6\n\nThe D
 epartment of Data Science\, Geethanjali College of Engineering and Technol
 ogy\, 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.\n\nThis bootcamp is des
 igned to provide participants with structured\, hands-on exposure to moder
 n Large Language Model (LLM) ecosystems\, focusing on practical system des
 ign rather than a theoretical overview alone. The program introduces stude
 nts to the architecture\, optimization\, and deployment of real-world AI s
 ystems built using contemporary LLM frameworks.\n\nUnlike conventional int
 roductory sessions\, this bootcamp emphasizes applied learning through gui
 ded implementation\, problem-solving\, and system-level understanding alig
 ned with current industry and research practices.\n\nParticipants will gai
 n exposure to:\n\n• Foundations of Large Language Models and Transformer
  Architecture\n• Advanced Prompt Engineering methodologies\n• Retrieva
 l-Augmented Generation (RAG) system design\n• Agentic AI workflows and t
 ool integration\n• Evaluation\, optimization\, and deployment of LLM-bas
 ed applications\n• Hands-on development sessions guided by domain expert
 s\n\nThe program aims to prepare students for emerging AI roles by bridgin
 g the gap between academic concepts and production-level AI system develop
 ment.\n\n👨‍🏫 Resource Persons:\n\nDr. Teja Santosh Dandibhotla\nPr
 ofessor\, Department of CSE\, CVR College of Engineering\n\nMr. N.N.S.S.S.
  Adithya\nAssistant Professor\, Department of CSE\, CVR College of Enginee
 ring\n\nDr. Venkateswara Rao Kagita\nAssistant Professor\, Department of C
 SE\, National Institute of Technology (NIT) Warangal\n\nThis bootcamp is i
 deal for students interested in Artificial Intelligence\, Machine Learning
 \, Generative AI\, research-oriented development\, and next-generation int
 elligent systems.\n\n🔷 REGISTRATION DETAILS\n\n🎟️ Registration is 
 mandatory for participation in the bootcamp.\n\nParticipants are requested
  to complete the registration form using the link below:\n\n🔗 Registrat
 ion Form:\nhttps://forms.gle/kPfbRBTgU1xwTNFm6\n\n📌 Important Instructi
 ons:\n• Limited seats available — selection based on confirmation.\n
 • Ensure correct details while filling the form.\n• Only registered pa
 rticipants will be allowed to attend.\n• Attendance is mandatory for all
  5 days.\n\n✅ Confirmation details and further communication will be sha
 red via official channels.\n\nAgenda: \n📘 BOOTCAMP AGENDA — ADVANCED 
 LLM SYSTEMS\n\nThe bootcamp follows a structured progression from foundati
 onal concepts to real-world system deployment\, ensuring participants deve
 lop both conceptual clarity and implementation capability.\n\n────
 ────────────────────\n\n📅 Day 1
  — Foundations of LLM Systems\n• Evolution of Language Models and Gene
 rative AI\n• Introduction to Transformer Architecture\n• Tokenization 
 Techniques &amp; Embedding Representations\n• Training Paradigms and Fine-Tu
 ning Concepts\n• Understanding how modern LLMs operate internally\n\nOut
 come:\nParticipants will understand the core building blocks behind modern
  Large Language Models.\n\n───────────────
 ─────────\n\n📅 Day 2 — Prompt Engineering &amp; Optimiz
 ation\n• Principles of Effective Prompt Design\n• Zero-shot\, One-shot
 \, and Few-shot Learning\n• System Prompts and Role-based Interaction De
 sign\n• Chain-of-Thought Reasoning\n• Techniques to Reduce Hallucinati
 ons and Improve Reliability\n\nOutcome:\nStudents learn how to control and
  optimize LLM behavior through structured prompting.\n\n──────
 ──────────────────\n\n📅 Day 3 — R
 etrieval-Augmented Generation (RAG)\n• Introduction to Retrieval Systems
 \n• Embeddings and Semantic Similarity Search\n• Vector Databases and 
 Indexing Concepts\n• Designing End-to-End RAG Pipelines\n• Data Securi
 ty and Knowledge Grounding\n\nOutcome:\nParticipants build knowledge-aware
  AI systems capable of using external data sources.\n\n──────
 ──────────────────\n\n📅 Day 4 — A
 gentic AI &amp; Tool Integration\n• AI Agent Architecture Fundamentals\n• 
 Function Calling and Tool Usage\n• Connecting LLMs with APIs and Externa
 l Systems\n• Multi-Agent Collaboration Workflows\n• Practical Agent De
 velopment Patterns\n\nOutcome:\nStudents understand how autonomous AI syst
 ems are designed and orchestrated.\n\n────────────
 ────────────\n\n📅 Day 5 — Deployment &amp; Real-W
 orld Systems\n• API Integration and System Packaging\n• Evaluating LLM
  Applications (Metrics &amp; Testing)\n• Performance Optimization Strategies
 \n• Deployment Considerations and Scaling Basics\n• Final Mini Project
  / Demo Presentation\n\nOutcome:\nParticipants experience the lifecycle of
  deploying production-ready LLM applications.\n\n────────
 ────────────────\n\n🎯 Learning Approach
 :\n• Concept → Demonstration → Hands-on Implementation\n• Guided c
 oding sessions\n• Interactive discussions with resource persons\n• Pra
 ctical system-building exposure\n\nGeethanjali college of engineering and 
 technlogy\,cheeryal\, Hyderabad\, Telengana\, India\, 501301
LOCATION:Geethanjali college of engineering and technlogy\,cheeryal\, Hyder
 abad\, Telengana\, India\, 501301
ORGANIZER:laxmimtech@gmail.com
SEQUENCE:54
SUMMARY:Advanced LLM Systems Bootcamp
URL;VALUE=URI:https://events.vtools.ieee.org/m/544012
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;🔗 Register Now: &lt;a href=&quot;https://forms.
 gle/kPfbRBTgU1xwTNFm6&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://forms.gle/kP
 fbRBTgU1xwTNFm6&lt;/a&gt;&lt;/p&gt;\n&lt;p&gt;The Department of Data Science\, Geethanjali C
 ollege of Engineering and Technology\, in association with the IEEE Comput
 ational Intelligence Society (CIS) Student Branch Chapter and IEEE Student
  Branch GCET\, proudly presents a 5-Day Intensive Bootcamp on Advanced LLM
  Systems.&lt;/p&gt;\n&lt;p&gt;This bootcamp is designed to provide participants with s
 tructured\, hands-on exposure to modern Large Language Model (LLM) ecosyst
 ems\, focusing on practical system design rather than a theoretical overvi
 ew alone. The program introduces students to the architecture\, optimizati
 on\, and deployment of real-world AI systems built using contemporary LLM 
 frameworks.&lt;/p&gt;\n&lt;p&gt;Unlike conventional introductory sessions\, this bootc
 amp emphasizes applied learning through guided implementation\, problem-so
 lving\, and system-level understanding aligned with current industry and r
 esearch practices.&lt;/p&gt;\n&lt;p&gt;Participants will gain exposure to:&lt;/p&gt;\n&lt;p&gt;&amp;bu
 ll\; Foundations of Large Language Models and Transformer Architecture &amp;nb
 sp\;&lt;br&gt;&amp;bull\; Advanced Prompt Engineering methodologies &amp;nbsp\;&lt;br&gt;&amp;bull
 \; Retrieval-Augmented Generation (RAG) system design &amp;nbsp\;&lt;br&gt;&amp;bull\; A
 gentic AI workflows and tool integration &amp;nbsp\;&lt;br&gt;&amp;bull\; Evaluation\, o
 ptimization\, and deployment of LLM-based applications &amp;nbsp\;&lt;br&gt;&amp;bull\; 
 Hands-on development sessions guided by domain experts&lt;/p&gt;\n&lt;p&gt;The program
  aims to prepare students for emerging AI roles by bridging the gap betwee
 n academic concepts and production-level AI system development.&lt;/p&gt;\n&lt;p&gt;
 👨&amp;zwj\;🏫 Resource Persons:&lt;/p&gt;\n&lt;p&gt;Dr. Teja Santosh Dandibhotla &amp;nbs
 p\;&lt;br&gt;Professor\, Department of CSE\, CVR College of Engineering&lt;/p&gt;\n&lt;p&gt;
 Mr. N.N.S.S.S. Adithya &amp;nbsp\;&lt;br&gt;Assistant Professor\, Department of CSE\
 , CVR College of Engineering&lt;/p&gt;\n&lt;p&gt;Dr. Venkateswara Rao Kagita &amp;nbsp\;&lt;b
 r&gt;Assistant Professor\, Department of CSE\, National Institute of Technolo
 gy (NIT) Warangal&lt;/p&gt;\n&lt;p&gt;This bootcamp is ideal for students interested i
 n Artificial Intelligence\, Machine Learning\, Generative AI\, research-or
 iented development\, and next-generation intelligent systems.&lt;/p&gt;\n&lt;p&gt;&amp;nbs
 p\;&lt;/p&gt;\n&lt;p&gt;🔷 &lt;strong&gt;REGISTRATION DETAILS&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;🎟️ Reg
 istration is mandatory for participation in the bootcamp.&lt;/p&gt;\n&lt;p&gt;Particip
 ants are requested to complete the registration form using the link below:
 &lt;/p&gt;\n&lt;p&gt;🔗&lt;strong&gt; Registration Form:&lt;/strong&gt;&lt;br&gt;&lt;a href=&quot;https://form
 s.gle/kPfbRBTgU1xwTNFm6&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://forms.gle/
 kPfbRBTgU1xwTNFm6&lt;/a&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;📌 Important Instructions:&lt;/strong
 &gt;&lt;br&gt;&amp;bull\; Limited seats available &amp;mdash\; selection based on confirmat
 ion.&lt;br&gt;&amp;bull\; Ensure correct details while filling the form.&lt;br&gt;&amp;bull\; 
 Only registered participants will be allowed to attend.&lt;br&gt;&amp;bull\; Attenda
 nce is mandatory for all 5 days.&lt;/p&gt;\n&lt;p&gt;✅ Confirmation details and furt
 her communication will be shared via official channels.&lt;/p&gt;&lt;br /&gt;&lt;br /&gt;Age
 nda: &lt;br /&gt;&lt;p&gt;&lt;strong&gt;📘 BOOTCAMP AGENDA &amp;mdash\; ADVANCED LLM SYSTEMS&lt;/
 strong&gt;&lt;/p&gt;\n&lt;p&gt;The bootcamp follows a structured progression from foundat
 ional concepts to real-world system deployment\, ensuring participants dev
 elop both conceptual clarity and implementation capability.&lt;/p&gt;\n&lt;p&gt;──
 ──────────────────────&lt;/p&gt;\n&lt;p
 &gt;&lt;strong&gt;📅 Day 1 &amp;mdash\; Foundations of LLM Systems&lt;/strong&gt;&lt;br&gt;&amp;bull\
 ; Evolution of Language Models and Generative AI&lt;br&gt;&amp;bull\; Introduction t
 o Transformer Architecture&lt;br&gt;&amp;bull\; Tokenization Techniques &amp;amp\; Embed
 ding Representations&lt;br&gt;&amp;bull\; Training Paradigms and Fine-Tuning Concept
 s&lt;br&gt;&amp;bull\; Understanding how modern LLMs operate internally&lt;/p&gt;\n&lt;p styl
 e=&quot;padding-left: 40px\;&quot;&gt;&lt;strong&gt;Outcome:&lt;/strong&gt;&lt;br&gt;Participants will un
 derstand the core building blocks behind modern Large Language Models.&lt;/p&gt;
 \n&lt;p&gt;───────────────────────
 ─&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;📅 Day 2 &amp;mdash\; Prompt Engineering &amp;amp\; Optimiza
 tion&lt;/strong&gt;&lt;br&gt;&amp;bull\; Principles of Effective Prompt Design&lt;br&gt;&amp;bull\; 
 Zero-shot\, One-shot\, and Few-shot Learning&lt;br&gt;&amp;bull\; System Prompts and
  Role-based Interaction Design&lt;br&gt;&amp;bull\; Chain-of-Thought Reasoning&lt;br&gt;&amp;b
 ull\; Techniques to Reduce Hallucinations and Improve Reliability&lt;/p&gt;\n&lt;p&gt;
 &lt;strong&gt;Outcome:&lt;/strong&gt;&lt;br&gt;Students learn how to control and optimize LL
 M behavior through structured prompting.&lt;/p&gt;\n&lt;p&gt;────────
 ────────────────&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;📅 Day 
 3 &amp;mdash\; Retrieval-Augmented Generation (RAG)&lt;/strong&gt;&lt;br&gt;&amp;bull\; Introd
 uction to Retrieval Systems&lt;br&gt;&amp;bull\; Embeddings and Semantic Similarity 
 Search&lt;br&gt;&amp;bull\; Vector Databases and Indexing Concepts&lt;br&gt;&amp;bull\; Design
 ing End-to-End RAG Pipelines&lt;br&gt;&amp;bull\; Data Security and Knowledge Ground
 ing&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Outcome:&lt;/strong&gt;&lt;br&gt;Participants build knowledge-awar
 e AI systems capable of using external data sources.&lt;/p&gt;\n&lt;p&gt;────
 ────────────────────&lt;/p&gt;\n&lt;p&gt;📅 
 &lt;strong&gt;Day 4 &amp;mdash\; Agentic AI &amp;amp\; Tool Integration&lt;/strong&gt;&lt;br&gt;&amp;bul
 l\; AI Agent Architecture Fundamentals&lt;br&gt;&amp;bull\; Function Calling and Too
 l Usage&lt;br&gt;&amp;bull\; Connecting LLMs with APIs and External Systems&lt;br&gt;&amp;bull
 \; Multi-Agent Collaboration Workflows&lt;br&gt;&amp;bull\; Practical Agent Developm
 ent Patterns&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Outcome:&lt;/strong&gt;&lt;br&gt;Students understand how 
 autonomous AI systems are designed and orchestrated.&lt;/p&gt;\n&lt;p&gt;────
 ────────────────────&lt;/p&gt;\n&lt;p&gt;📅 
 &lt;strong&gt;Day 5 &amp;mdash\; Deployment &amp;amp\; Real-World Systems&lt;/strong&gt;&lt;br&gt;&amp;b
 ull\; API Integration and System Packaging&lt;br&gt;&amp;bull\; Evaluating LLM Appli
 cations (Metrics &amp;amp\; Testing)&lt;br&gt;&amp;bull\; Performance Optimization Strat
 egies&lt;br&gt;&amp;bull\; Deployment Considerations and Scaling Basics&lt;br&gt;&amp;bull\; F
 inal Mini Project / Demo Presentation&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Outcome:&lt;/strong&gt;&lt;br
 &gt;Participants experience the lifecycle of deploying production-ready LLM a
 pplications.&lt;/p&gt;\n&lt;p&gt;─────────────────
 ───────&lt;/p&gt;\n&lt;p&gt;🎯 &lt;strong&gt;Learning Approach:&lt;/strong&gt;&lt;br&gt;
 &amp;bull\; Concept &amp;rarr\; Demonstration &amp;rarr\; Hands-on Implementation&lt;br&gt;&amp;
 bull\; Guided coding sessions&lt;br&gt;&amp;bull\; Interactive discussions with reso
 urce persons&lt;br&gt;&amp;bull\; Practical system-building exposure&lt;/p&gt;
END:VEVENT
END:VCALENDAR