Introducing the Topic Tracks for ODSC East 2024 — Highlighting Gen AI, LLMs, and Responsible AI
ODSC East 2024, coming up this April 23rd to 25th, is fast approaching and this year we will have even more tracks comprising hands-on training sessions, expert-led workshops, and talks from data science innovators and practitioners. Check the ODSC East tracks out below.
NLP and LLMs
The NLP and LLMs track will give you the opportunity to learn firsthand from core practitioners and contributors about the latest trends in data science languages and tools, such as pre-trained models, with use cases focusing on deep learning, speech-to-text, and semantic search. You’ll also explore the current state of LLMs, their applications, and the future landscape of these models.
- Ben Needs a Friend — An intro to building Large Language Model applications
- Data Synthesis, Augmentation, and NLP Insights with LLMs
- LLM Best Practises: Training, Fine-Tuning and Cutting Edge Tricks from Research
Generative AI
Join this track to gain the core skills needed to become a part of this Generative AI movement and to both develop and implement generative AI into your organization or research. These sessions will cover theory, applications, and tools like GPT-4, Gemini, DALL-E, Stable Diffusion, Whisper, and more.
- Deploying Trustworthy Generative AI
- Stable Diffusion: Advancing the Text-to-Image Paradigm
- Multimodal Retrieval Augmented Generation
Machine Learning
This track gathers together the creators and top practitioners in the rapidly expanding fields of deep learning and machine learning to discuss the latest advances, trends, and models in these fields. A wide range of topics will be discussed, such as TensorFlow, neural networks, PyTorch, autonomous machines, recommendation systems, reinforcement learning, and much more.
- An Introduction to Time Series Forecasting: A Tutorial
- Who Wants to Live Forever? Reliability Engineering and Mortality
- No-Code and Low-Code AI: A Practical Project Driven Approach to ML
Multimodal and Deep Learning
Explore how AI can perceive the world like humans, through sight, sound, touch, and more in this new track. You’ll learn about the intelligent systems that truly understand the world around them during talks, tutorials, and workshops from the creators and top practitioners.
- Deep Learning with PyTorch and TensorFlow
- How to Practice Data-Centric AI and Have AI Improve its Own Dataset
- End-to-End Deep Learning for Time Series Forecasting and Analysis
Machine Learning for Biotech and Pharma
The past few years have seen increasing investment in AI in the Pharma, Healthcare, and Biotech industries. The impact of those investments has been particularly significant in the fields of disease identification, drug discovery, and clinical trials. This focus area will cover some of the technology and recent developments underpinning these applications.
- Harnessing Machine Learning to Understand SARS-CoV-2 Variants and Hospitalization Risk
- Introduction to Protein Language Models for Synthetic Biology
- Predicting the Immunogenicity of Protein Therapeutics by Augmenting Deep-Learning based HLA-II Epitope Modeling and Clinical Risk Factors
Machine Learning Safety and Security
Learn how to protect your organization’s models and data through this timely track. Some of the topics that you might encounter during the included training sessions, workshops, and talks are adversarial attacks, backdoor model vulnerabilities, real-world deployment tail risks, risk monitoring, and boosting model defenses.
- Overcoming the Limitations of LLM Safety Parameters with Human Testing and Monitoring
AI Mini-Bootcamp
In this truly immersive experience, you will access an expanse of industry-focused data science topics on a scale not offered elsewhere. You will also get invaluable insights by networking and connecting with hundreds of data science attendees, world-renowned instructors, industry experts, and dozens of top companies seeking the next wave of talent. The Mini-Bootcamp also includes pre-conference live and on-demand virtual training.
Data Visualization and Data Analysis
Join some of the world’s most creative minds that are changing the way we visualize, understand, and interact with data. You’ll also learn the art of storytelling, information communication, and data visualization using the latest open-source tools and techniques.
This track will focus on helping you build skills in text mining, data storytelling, data mining, and predictive analytics through use cases highlighting the latest techniques and processes to collect, clean, and analyze growing volumes of structured data.
- Data Morph: A Cautionary Tale of Summary Statistics
- Visualization in Bayesian Workflow Using Python or R
- Harnessing Bayesian Statistics for Business-Centric Data Science
Data Engineering and Big Data
Join this track to learn the latest techniques and processes to analyze raw data and automate data into mechanical processes and algorithms. You’ll also hear use cases on how data can be used to optimize business performance.
- What it Takes to Stabilize a GenAI-first, Modern Data Lake in a Big Company: The 12 Factor App for Data
- Engineering Knowledge Graph Data for a Semantic Recommendation AI System
- Clean as You Go: Basic Hygiene in the Modern Data Stack
MLOps and LLMOps
As data science is integrated into more aspects of an organization, the challenges of deploying and monitoring models in production, managing data science teams and workflows, and measuring ROI arise. This focus area will utilize use cases, best practices, and anecdotes to show how to effectively incorporate data science practice into your organization.
- Highly Scalable Inference Platform for Models of Any Size
Responsible AI
This track brings together top data ethicists to provide a practical, ethical framework for technologists to develop machine learning systems. Using case studies and existing frameworks, you’ll develop the tools you need to build your own ethical approach to deploying machine learning in the real world. You will learn how to responsibly design human-in-the-loop review processes, monitor bias, build trust transparency, and develop explainable machine learning systems to ensure data and model security.
- How AI Impacts the Online Information Ecosystem
- Resisting AI
- Social and Ethical Implications of Generative AI
- Advancing Ethical Natural Language Processing: Towards Culture-Sensitive Language Models
Register for ODSC East 2024 here
To build the job-ready skills you need in this ever-changing environment, be sure to join us at ODSC East 2024 this April. Plus you’ll save 40% on your ODSC East in-person or virtual pass when you register for the conference today.
Originally posted on OpenDataScience.com
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