Course curriculum

  • 1

    ODSC Talks

    • ODSC Keynote: Automate Your AI Lifestyle Management With Auto AI and Watson OpenScale - Nerav Doshi

    • ODSC Keynote: Humans & AI in Financial Services-The Future - Manuela Veloso, PhD & Samik Chandarana

    • ODSC Keynote: The Future is Multiagent! - Michael Wooldridge, PhD

    • A Centralized Customer Relationship Management Approach for Banking - "van Luciano Danesi, PhD & Federica Perugini

    • Augmented Programming - Gideon Mann, PhD

    • Automotive Sales Forecasting using Hierarchical Bayesian Modelling in Stan - Mo Sayed, PhD, & Alice Grout-Smith

    • Building a New Financial Data Set from Scratch with Active Learning and NLP - Zach Anglin

    • Chaos and Pain in Machine Learning, and the ‘DevOps for ML Manifesto’ - Luke Marsden

    • Characterizing GitHub Repositories Using NLP-derived Techniques - Romano Foti, PhD

    • Data Valuation - Valuing the World's Greatest Asset - Andy Neely, PhD

    • Deep Learning for Third Party Risk Identification and Evaluation at Dow Jones - Yulia Zvyagelskaya & Victor Llorente

    • Deep Learning Survival Analysis for Consumer Credit Risk Modelling - Jiahang Zhong, PhD

    • Enabling Human Rights Experts With AI: From Twitter and To Space - Alfredo Kalaitzis, PhD

    • Ethical AI: A Practical Guideline For Data Scientists - Vincent Spruyt

    • Explainable AI - Methods, Applications & Recent Developments - Dr. Wojciech Samek

    • Generative Adversarial Networks for Finance - Alexandre Combessie

    • Identify Heart Disease Risk Factors from Clinical Notes - Sudha Subramanian

    • Industrial Artificial Intelligence - The Driving Force - Diego Galar, PhD

    • Introduction to NLP - Saaed Amen

    • Learning with Limited Labeled Data - Shioulin Sam, PhD

    • Leveraging the advantages of Bayesian methods to build a data science product - Korbinian Kuusisto

    • Machine Learning for Continuous Integration - Andrea Frittoli Kyra Wulffert

    • Making robust business decisions with sparse data - Sarah Jarvis, PhD

    • Meaning Representation for Natural Language Understanding - Mariana Romanyshyn

    • ML in Production: Serverless and Painless - Oliver Gindele, PhD

    • Multi-stakeholder Machine Learning for Marketplaces - Rishabh Mehrotra, PhD

    • Not Always a Black Box: Explainability Applications for a Real Estate Problem - Violeta Misheva, PhD

    • Opportunities and Challenges when Building AI for Autonomous Flight - David Haber

    • Practical Methods to Optimise Model Stability: A Case Study Using Customer-Lifetime Value at Farfetch - Davide Sarra & Kishan Manani, PhD

    • Practical, Rigorous Explainability in AI - Tsvi Lev

    • Road to Responsible AI – Lessons Learned Delivering Machine Learning at Scale - Tom Cronin

    • Supply Chain Analytics and Quantamental Factor Investing - Sheng Quan Zhou, PhD

    • Taking Recommendation Systems to The Masses - Miguel Fierro, PhD & Andreas Argyriou, PhD

    • The How, Why, and When of Replacing Engineering Work with Compute Power - Jannes Klaas

    • The Interplay of Experimentation and ML to Aid in Repayment of Micro-loans in Sub-Saharan Africa - Brianna Schuyler, PhD

    • The Soul of a New AI - Joseph Blue

    • Tools for High Performance Python - Ian Ozsvald

    • Towards Trustable AI for Complex Systems - a Life Science and AIOps Perspective - Dr. Xian Yang

    • Employing XAI Techniques To Identify Relevant Search Space For Evolutionary Algorithms - Adurthi Ashwin Swarup

    • Making Data Useful - Cassie Kozyrkov, PhD

    • Unsupervised Learning and Decision Making - Danilo Jimenez Rezende, PhD
  • 2

    ODSC Workshops

    • Tutorial on Automated Machine Learning - Joaquin Vanschoren,PhD & Pieter Gijsbers

    • An Overview of Responsible Artificial Intelligence - Mehrnoosh Sameki, PhD & Sarah Bird, PhD

    • Automated Machine Learning in Quant Finance: Promise, Practice and Pitfalls - Peter Simon & Ayub Hanif, PhD

    • Anonymous Crowd v. Managed Team: A Study on Quality Data Processing at Scale - Philip Tester & Mark Roulston, PhD

    • Beyond Deep Learning - Differentiable Programming with Flux - Avik Sengupta

    • Bringing Data to the Masses Through Visualisation - Alan Rutter

    • From Research to Production: Performant Cross-Platform ML/DNN Model Inferencing on Cloud and Edge with ONNX Runtime - Faith Xu & Prabhat Roy

    • Building an Industry Classifier With The Latest Scraping, NLP and Deployment Tools - Ido Shlomo

    • Choosing The Right Deep Learning Framework: A Deep Learning Approach - Nick Acosta

    • Integrating Real-Time Video Analysis with Clinical Data to Enable Digital Diagnostics - Wade Schulz, MD, PhD Devin Hosea

    • Machine Learning with R Workshop: Smartphone-Based Indoor Positioning - Guillem Perdigó

    • ML for Social Good: Success Stories and Challenges - Olga Isupova, PhD

    • Price Optimisation: From Exploration to Productionising - David Adey, PhD & Alexey Drozdetskiy, PhD

    • Rule Induction and Reasoning in Knowledge Graphs - Daria Stepanova, PhD

    • Solving the Chaos and Pain: Using Dotscience for ML Collaboration and Deployment - Luke Marsden

    • Tutorial on Credit Card Fraud Detection - Kathrin Melcher & Maarit Widmann

    • Automatic Speech Recognition: a Paradigm Change in Motion - Ralf Schlüter, PhD

    • How to Make Machine Learning Fair and Accountable - Sray Agarwal

    • Introduction to Kubeflow Pipelines - Dan Anghel

    • Learning Gaussian Processes - Barbara Rakitsch, PhD

    • Make Beautiful Web Apps from Jupyter Notebooks - Michal Mucha

    • Probabilistic Deep Learning in TensorFlow: The Why and How - Zach Anglin

    • PyTorch 101: Building A Model Step-by-Step - Daniel Voigt Godoy

    • Sequence Modelling with Deep Learning - Dr. Natasha Latysheva

    • The Perks of On Board Deep Learning: Train, Deploy and Use Neural Nets on a Raspberry Pi - Constant Bridon

    • Tutorial on Provenance - Luc Moreau, PhD & Dong Huynh, PhD