Introducing the Topic Tracks for ODSC East 2025: Spotlight on Gen AI, AI Agents, LLMs, & More
As AI continues to advance at an unprecedented pace, the demand for cutting-edge skills and practical knowledge has never been greater. At ODSC East 2025, we’re excited to present 12 curated tracks designed to equip data professionals, machine learning engineers, and AI practitioners with the tools they need to thrive in this dynamic landscape.
Whether you want to master generative AI, deploy AI agents, or streamline your machine learning pipelines with MLOps, ODSC East 2025 has something for you.
Let’s take a closer look at this year’s standout tracks.
Generative AI Track — Build the Future with Gen AI
Generative AI has captured the world’s attention with tools like ChatGPT, DALL-E, and Stable Diffusion revolutionizing how we create content and automate tasks. This track will help you go beyond the hype to develop hands-on skills in building and deploying generative AI models in your organization.
Topics Include:
- Generative AI Foundations
- Ethical Use & Bias Mitigation in Gen AI
- Autonomous AI Agents
- Stable Diffusion for Image & Video Generation
- AI Code Assistants
- Synthetic Data Generation
- Open Source Agents, RAG, LLMs, and Tools
Who Should Attend: Machine Learning Engineers, Data Scientists, Developers, and Product Managers eager to implement generative AI in their work.
AI Agents Track — Harness the Power of Autonomous Systems
AI agents are transforming how businesses operate by performing complex tasks independently, improving productivity and decision-making. This track dives into the design, development, and deployment of intelligent agents that leverage LLMs and machine learning.
Topics Include:
- Agentic AI Design Patterns
- LLMs & RAG for Agents
- Agent Architectures & Chaining
- Evaluating AI Agent Performance
- Building with LangChain and LlamaIndex
- Real-World Applications of Autonomous Agents
Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.
Large Language Models & RAG Track — Master LLMs & Retrieval-Augmented Generation
Large language models (LLMs) and retrieval-augmented generation (RAG) have become foundational to AI development. This track will cover the latest techniques, tools, and applications to help you deploy more accurate, reliable, and contextually aware language models.
Topics Include:
- LLMs & Small Language Models (SLMs)
- Building & Implementing RAG Systems
- Fine-Tuning & Model Efficiency
- Metadata Filtering & Cross-Modal Retrieval
- GPT-4o, LLaMA 3, Mixtral, and Open-Source Models
- Guardrails for LLM Safety & Reliability
Who Should Attend: NLP Specialists, ML Engineers, Data Scientists, and AI Researchers interested in the future of LLMs.
What’s Next in AI Track — Explore the Cutting-Edge
Stay ahead of the curve with insights into the future of AI. This track brings together industry pioneers and leading researchers to showcase the breakthroughs shaping tomorrow’s AI landscape.
Topics Include:
- Innovations in LLMs & Next-Gen Architectures
- AI for Robotics & Automation
- AI Assistants for Workplace Productivity
- Legal Implications of AI Content
- Ethical Considerations & Bias in Advanced Systems
Who Should Attend: Senior Data Professionals, AI Researchers, Business Leaders, and Developers planning for the future of AI.
Machine Learning Track — Deepen Your ML Expertise
Machine learning remains the backbone of AI innovation. This track is designed to help practitioners strengthen their ML foundations while exploring advanced algorithms and deployment techniques.
Topics Include:
- Advanced ML Algorithms & Ensemble Methods
- Hyperparameter Tuning & Model Optimization
- AutoML & Real-Time ML Systems
- Explainable AI & Ethical AI
- Time Series Forecasting & NLP Techniques
Who Should Attend: ML Engineers, Data Scientists, and Technical Practitioners working on production-level ML solutions.
AI Engineering Track — Build Scalable AI Systems
Learn how to bridge the gap between AI development and software engineering. This track will focus on AI workflow orchestration, efficient data pipelines, and deploying robust AI solutions.
Topics Include:
- AI Workflow Orchestration
- Low-Code/No-Code AI Development
- Scalability & Infrastructure Cost Management
- AI for Software Testing & Quality Assurance
- AI Copilots & Code Assistants
Who Should Attend: Software Engineers, Developers, and AI Practitioners building production-ready AI systems.
Deep Learning & Multi-Modal Models Track — Push Neural Networks Further
Dive into the latest advancements in neural networks, multimodal learning, and self-supervised models. This track provides practical guidance on building and optimizing deep learning systems.
Topics Include:
- CNNs, RNNs, GANs, and Autoencoders
- Multimodal Learning Techniques
- Deep Reinforcement Learning
- Hyperparameter Tuning & Model Deployment
- Scalable Deep Learning Architectures
Who Should Attend: Deep Learning Practitioners, Data Scientists, and AI Researchers working on state-of-the-art models.
AI in Life Sciences Track — Transforming Healthcare with AI
AI is driving innovation in healthcare, from drug discovery to diagnostics. This track will explore how AI and machine learning are accelerating breakthroughs in life sciences.
Topics Include:
- AI-Driven Drug Discovery
- Precision Medicine & Bioinformatics
- Medical Imaging & Remote Monitoring
- Generative AI for Biologics
- Ethical and Legal Challenges in Healthcare AI
Who Should Attend: Healthcare Professionals, Bioinformaticians, and Data Scientists applying AI to life sciences.
MLOps & LLMOps Track — Operationalizing AI at Scale
Productionizing machine learning and large language models requires specialized tools and processes. This track will cover the latest best practices for managing AI models from development to deployment.
Topics Include:
- MLOps Fundamentals
- LLM Deployment & Monitoring
- Cloud Infrastructure for LLMs
- Observability & Cost Management
- Operationalizing Local LLMs Responsibly
Who Should Attend: MLOps Engineers, Data Scientists, and AI Developers responsible for deploying AI systems.
Responsible AI Track — Build Ethical, Fair, and Safe AI
As AI systems become more powerful, ensuring their responsible development is more critical than ever. This track will guide you in aligning AI systems with ethical standards and minimizing bias.
Topics Include:
- Principles to Practice: Implementing Responsible AI
- Mitigating Bias in Hiring & Decision-Making
- AI Governance, Regulation & Alignment
- Human-AI Interaction Best Practices
Who Should Attend: AI Researchers, Ethicists, Data Scientists, and Business Leaders developing fair and transparent AI systems.
Data Visualization Track — Communicating Insights Through Data
Transform raw data into compelling visual narratives. This track will help you master the art of data storytelling and interactive dashboards.
Topics Include:
- Storytelling with Data
- UX Principles in Visualization
- Building Interactive Dashboards
- Visualization with Generative AI
Who Should Attend: Data Analysts, Designers, and Developers crafting impactful visualizations.
Data Engineering Track — Build the Data Foundation for AI
Data engineering powers every AI system. This track offers practical guidance on building scalable data pipelines and ensuring data quality.
Topics Include:
- Data Ingestion, Integration & Processing
- Real-Time Insights & Performance Optimization
- Data Security, Governance, & Privacy
Who Should Attend: Data Engineers, Analysts, and Developers Optimizing Data Infrastructure.
Join Us at ODSC 2025 — Secure Your Spot in the AI Revolution.
No matter your specialization, ODSC East 2025 has a track designed to help you future-proof your skill set and stay at the forefront of AI and data science.
Take the next step in your career — Register today and join thousands of professionals from around the world at ODSC East 2025.
