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SESSIONS

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HANDS-ON WORKSHOPS

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THE FIRST HANDS-ON SESSIONS

Sinan Ozdemir - AI & LLM Expert | Author | Founder + CTO | LoopGenius

In-Person Training: Aligning Open-source LLMs Using Reinforcement Learning from Feedback

Valentina Alto - Azure Specialist - Data and Artificial Intelligence | Microsoft

In-Person Workshop: The AI Paradigm Shift: Under the Hood of a Large Language Models

In-Person Training: Deep Learning with PyTorch and TensorFlow

In-Person Workshop: Enabling Complex Reasoning and Action with ReAct, LLMs, and LangChain

In-Person Training: NLP with GPT-4 and other LLMs: From Training to Deployment with Hugging Face and PyTorch Lightning

In-Person Workshop: Using Graphs for Large Feature Engineering Pipelines

In-Person Training: Ben Needs a Friend – An intro to building Large Language Model applications

Tamilla Triantoro, PhD - Associate Professor, Business Analytics | Quinnipiac University

In-Person Workshop: Data Synthesis, Augmentation, and NLP Insights with LLMs

Aric LaBarr, PhD - Associate Professor of Analytics Institute for Advanced Analytics | NC State University

In-Person Training: Developing Credit Scoring Models for Banking and Beyond

Matt Harrison - Python & Data Science Corporate Trainer | Consultant | MetaSnake

In-Person Workshop: Idiomatic Pandas

Thomas J. Fan - Senior Machine Learning Engineer | Union.ai

In-Person Training: Introduction to scikit-learn: Machine Learning in Python

Virtual Training: Visualization in Bayesian Workflow Using Python or R

Virtual Workshop: Causal AI: from Data to Action

Virtual Training: Generative AI, AI Agents, and AGI – How New Advancements in AI Will Improve the Products We Build

Virtual Workshop: Everything About Large Language Models: Pre-training, Fine-tuning, RLHF & State of the Art

Dr. Mustafa Hajij - Assistant Professor | University of San Francisco

Virtual Workshop: Topological Deep Learning: Going Beyond Graph Data

Virtual Workshop: Building Using Llama 2

Virtual Workshop: Graphs: The Next Frontier of GenAI Explainability

Virtual Workshop: Build Conversational AI and Integrate into Product Page Using Watsonx Assistant

Virtual Workshop: LLM Best Practises: Training, Fine-Tuning and Cutting Edge Tricks from Research

Adam Breindel - Technical Instructor; Kamil Kaczmarek - Technical Training Lead | Anyscale

In-Person Training: Productionizing AI and LLM Apps with Ray Serve

Mohammad Soltanieh-ha, PhD - Clinical Assistant Professor | Boston University

In-Person Training: LLMs Meet Google Cloud: A New Frontier in Big Data Analytics

 

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Confirmed 2024 Workshop Instructors


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Free Pre-Bootcamp Primer Courses

Data, Coding, and AI preparation courses for ODSC Mini-Bootcamps

ODSC Bootcamp Primer Courses

These primer courses can be taken stand alone or as part of our Mini-Bootcamp series. This foundations series is built from the ground up to boost your understanding of data-centric AI

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Beginner to Advanced Level Training

From the Leading Instructors in the Industry

Planned 2024 Topics Include

Large Language Models & Generative AI

  • Introduction to Large Language Models

  • Introduction to Prompt Engineering

  • Prompting with OpenAI and Prompting Safety Guardrails

  • Fine Tuning Large Language Models & Embedding Models

  • Fine Tuning Embedding Models

  • Building a Q&A Bot with LLMS, Vectors, and LangChain

  • LLMOps – Large Language Model Workflow

  • AI-Assisted Code Generation Techniques

  •  Advanced LLMs – LangChain Agents

  •  Advance LLMs –  Parameter Efficient Fine-Tuning

  •  Advance LLMs –  Retrieval-Augmented Generation (RAG)

Machine Learning

  • MLOps and Machine Learning Pipelines

  • No-Code and Low-Code Machine Learning

  • Self Supervised learning; new techniques

  • Federated Learning for Data Privacy

  • Explainable AI and Bias in machine learning

  • Machine Learning at Scale using Apache Spark

  • Safety & Robustness in Machine Learning Modeling

  • Semi-supervised learning

  • Real-time Streaming Analytics

  • Causal Inference with Machine Learning

  • Auto Machine Learning (AutoML)

Deep Learning

  • Deep Reinforcement learning

  • Deep Learning with PyTorch & Tensorflow

  • Deep Learning Deep Dive

  • Computer Vision 1/2 Day Training

  • Deep Learning with Keras

  • Introduction to Deep learning

  • Deepfakes Tutorial

  • Graph Representation Learning

  • Distributed Machine Learning & Deep Learning

NLP

  • Introduction to NLP and Topic Modeling

  • Self Supervised learning; new techniques

  • Transfer Learning in NLP

  • NLP Pre-trained Transformer Models with Bert, Ernie,, and GPT-2

  • State-of-the-Art NLP with PyTorch and Tensorflow

  • Semi-supervised learning

  • Hugging Face Transformer Library Workshop

  • Applications of NLP; Sentiment Analysis, Dialog Systems, and Semantic Search

Beginner to Advanced Level Training

From the Leading Instructors in the Industry

2024 Topics Include

All Levels + Foundational

  • An Introduction to Time Series Forecasting: A Tutorial

  • Introduction to scikit-learn: Machine Learning in Python

  • Introduction to Math for Data Science

  • Introduction to Protein Language Models for Synthetic Biology

  • A Practical Introduction to Data Visualization for Data Scientists

  • Introduction to Linear Regression using Spreadsheets with Real Estate Data

  • Introduction to Machine Learning with Python

  • Introduction to Large Language Models

  • Introduction to NLP

  • Idiomatic Pandas

  • Enabling Complex Reasoning and Action with ReAct, LLMs, and LangChain

Beyond the Basics

  • Deep Learning with PyTorch and TensorFlow

  • Multimodal Retrieval Augmented Generation

  • LLM Best Practises: Training, Fine-Tuning and Cutting Edge Tricks from Research

  • Strategies for Implementing Responsible AI Governance and Risk Management

  • How to Migrate from Batch to Realtime Streaming Data

  • Mastering Langchain for LLM Application Development

  • Everything About Large Language Models: Pre-training, Fine-tuning, RLHF & State of the Art

  • Topological Deep Learning: Going Beyond Graph Data

  • Data Synthesis, Augmentation, and NLP Insights with LLMs

  • Generative AI, AI Agents, and AGI – How New Advancements in AI Will Improve the Products We Build

Advanced deep dives

  • Generative A.I. with Open-Source LLMs: From Training to Deployment with Hugging Face and PyTorch Lightning

  • Using Graphs for Large Feature Engineering Pipelines

  • Ben Needs a Friend – An intro to building Large Language Model applications

  • Aligning Open-source LLMs Using Reinforcement Learning from Feedback

  • State-of-the-art Open Source AI with Hugging Face

  • Machine Learning using PySpark for Text Data Analysis

  • Machine Learning with XGBoost

  •  Advanced LLMs – LangChain Agents

  •  Advance LLMs –  Parameter Efficient Fine-Tuning

  •  Advance LLMs –  Retrieval-Augmented Generation (RAG)

Ai+ Training Tracks

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As part of the global data science community we value inclusivity, diversity,  and fairness in the pursuit of knowledge and learning. We seek to deliver a conference agenda, speaker program, and attendee participation that moves the global data science community forward with these shared goals. Learn more on our code of conductspeaker submissions, or speaker committee pages.

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Access to 40+ training sessions and 70+ workshops.

Hands-on experience with the latest frameworks and breakthroughs in data science.

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Opportunities to connect with other ambitious, like-minded data scientists.

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