Course curriculum

  • 1

    Keynotes

    • Prof. James A. Hendler - The Tragedy of the (Data) Commons

    • East 2021 - Ritika Gunnar - Predict Business Outcomes With AI for a Multi-cloud World

    • East 2021 - Bryan Harris, Chris Wright - From Data to Decisions- The Important Role of ModelOps

    • East 2021 - John Montgomery, Emma Ning, Geeta Chauhan - Fostering AI Innovations Through Open Source Projects

    • East 2021 - Mihaela van der Schaar - Why Medicine is Creating Exciting New Frontiers for Machine Learning

    • East 2021 - Michael Stonebraker, PhD - Data Mastering at Scale

    • East 2021 - Ryohei Fujimaki, PhD - Accelerate ML Feature Engineering through Automation

    • East 2021 - Mike Piech - Accelerate AI with the Open Hybrid Cloud

    • Dr. Alicia Frame - Relationships Matter: Using Connected Data for Better Machine Learning
  • 2

    Demo talks

    • East 2021 - Danny Leybzon - Augmented Intelligence_ How Machine Learning + Human Analytics Catches Criminals

    • East 2021-Eric Gu-Recommending Meals for Millions

    • East 2021-Daniel Gray - Embracing the Convergence of AI and BI to Make Smarter Data-Driven Decisions at Scale

    • East 2021 - Ayodele Odubela - Getting Started with Experiment Management

    • East 2021- Stavroula Ntoufa, PhD , Imad Yassin -The application of NLP and AI to uncover evidence from scientific literature

    • East 2021- Rohan Khade - Datatron in Action_ Take Your Ml Models From Training to Production

    • East 2021-Itto Kornecki - Deepnote - a Collaborative Data Science Notebook

    • East 2021-Marius Bogoevici, Sadhana Nandakumar-Applying AI to Critical Challenges in Financial Services_ Fighting Fraud and Digital Banking

    • East 2021-Bob Foreman, Hugo Watanuki-The Kit and Kaboodle for Big Data and Data Science

    • East 2021- Roberto Reif, PhD - Meet The New Metis_ Accelerating Data Science & Analytics Learning for All

    • East 2021-Satish Pala-Operationalizing Text Analytics

    • East 2021-Stef Telford - Comprehending ClearML and MLOps - Enabling the new A-Z

    • East 2021-Richard Lewis-How Mastering Customer Data Through ML Is Driving Results at Santander JJ and Analog Devices

    • East 2021-Manasi Vartak, PhD-What is MLOps, Why do you need it, and Where do you begin_

    • East 2021-Stuart Laurie - Neo4j Demo A Graph Data Science Framework for Enterprise-Stuart Laurie

    • East 2021-Mark Benyovszky - AI-enabled Automation

    • East 2021-Elena Neroslavskaya, Gisle Dankel, Geeta Chauhan - The Next Evolution of PyTorch Performance Debugging.mp4

    • Esast 2021-Aaron Cheng, PhD, Lulu Liu, PhD - Automated Feature Engineering for Enterprise Machine Learning

    • East 2021 - John Thomas - A Look Into Deploying and Operationalizing Data Science Models With IBM

    • East 2021- Phoebe Liu, PhD - Training Conversational Agents on Noisy Data

    • East 2021- Aaron Richter, PhD - Jupyter Notebooks for Teams- Best Practices for Quality, Reproducibility, and Collaboration

    • East 2021-Antonio Cotroneo -Unlocking the Power of AWS Open Data with OmniSci Free

    • East 2021 - Torgil Hellman, Simon Asplen-Taylor-How Does Data Automation Change Working Lives

    • East 2021-Robert Lundberg, Martin Isaksson-Fast Visual and Explainable ML Modeling With PerceptiLabs

    • East 2021-Prabhakar Narasimhadevara-AI for Commercial Excellence – A Stanley Black and Decker Perspective
  • 3

    Career Lab Talks

    • East 2021-Jack Raifer- Build your Own Job

    • East. 2021-Mark R Kanner, PhD-Retention Models in HR_ From Prediction to Action

    • East 2021-Jeremie Harris-How to Run your Job Search Like a Data Scientist

    • East 2021- Sheamus McGovern- 2021 Ai Job Market Review For Data Scientists, Machine Learning Engineers, And Related Roles

    • East 2021-Aadil Hussaini-Am I Ready for a Data Science Job_

    • East 2021-Kirill Eremenko-Land your First Data Science Position in 99 Days (with No Experience)

    • East 2021-Emily Robinson, Dr. Jacqueline Nolis-'Help! My job Search isn’t Working” A Live Recording of the Podcast Build a Career in Data Science
  • 4

    ODSC Talks

    • East 2021 - Ayodele Odubela - Standardizing Machine Learning Experimentation

    • East 2021 - Andrea La Rosa - Dataset Management for Computer Vision Possibly the Most Underrated and Important Component to Delivering Successful Computer Vision Solutions in Real-life

    • East 2021 - Matteo Mortari, Daniele Zonca - eXplainable Predictive Decisioning_ combine ML and Decision Management to promote trust on automated decision making

    • East 2021 - Elliott Ning - Accelerating The Journey To Document Understanding AI

    • East 2021 - Andrey Malevich - Practical Recommendations for Building Recommender Systems

    • East 2021 - Mike Flaxman - Abhishek Damera - The Macroscope Initiative - Building Planetary geoML with OmniSci

    • East 2021 - Artur Saudabayev - The Causaly Machine-Reading Platform_ From finding documents to finding evidence

    • East 2021 - Michael Tamir, PhD - Information Flow and Deep Representation Learning

    • East 2021 - Scott Gorlin, PhD, Anton Aboukhalil, Sc.D, Noah Jensen - The Data Science Challenge_ How to Innovate, Upskill, and Inspire an Enterprise

    • East 2021 - Diego Oppenheimer - What is ML governance and why I should care_

    • East 2021 - Saurya Das - Enterprise ready ML Model Training on Hybrid Cloud, leveraging Kubernetes

    • East 2021 - Mythili Krishnan - Data Visualization and Lock-down Analysis Using Global Covid-19 Data

    • East 2021 - Byron Galbraith - Alternatives to Reinforcement Learning for Real World Problems-Byron Galbraith, PhD

    • East 2021 - Sebastian Raschka - Machine Learning and AI in 2021_ Recent Trends, Technologies, and Challenges

    • East 2021 - Stephanie Kirmer - Going Beyond Matplotlib and Seaborn_ A survey of Python Data Visualization Tools

    • East 2021 - Julia Neagu - Ian Bakst, PhD - The Healthy Approach - Organic Data Enrichment Through Entity Extraction

    • East 2021 - Veysel Kocaman, PhD - Introduction to Spark NLP

    • East 2021 - Robert Crowe - Irene Giannoumis-From Experimentation to Products_ The Production ML Journey

    • East 2021 - Hannah Arnson, PhD, Danielle Aring - Building a Holistic Risk Profile_ Near Real-Time Approach to Insider Threat Detection

    • East 2021 - Violeta Misheva, PhD - AI Explainability in The Real World

    • East 2021 - Jakub Jurovych-The Future of Data Science Notebooks is Collaborative-Jakub Jurovych

    • East 2021 - Han Shu - Challenges in Merchandising, Recommendation, and Search for Local Delivery Commerce

    • East 2021 - Pierre Marchard - Journey to Data Automation

    • East 2021 - Dr. Gerald Friedland - A New Measurements-Based Approach to Machine Learning

    • East 2021 - Dr. Tanveer Syeda-Mahmood - The Medical Sieve Radiology Grand Challenge on Chest X-rays

    • East 2021 - Paige Roberts - Python + MPP Database = Large Scale AI-ML Projects in Production Faster

    • East 2021 - Margaret Good, PhD - Responsible Use of AI in Health Care

    • East 2021 - Cal Al-Dhubaib - Building an Ethical Data Science Practice

    • East 2021 - Joe Hellerstein, PhD - The State of Serverless and Applications to AI

    • East 2021 - David Linthicum - Building Multi Cloud Success for Cross Database Usage

    • East 2021 - Anatoli Gorchet - What Kind of AI Can Help Manufacturing Adapt to a Pandemic

    • East 2021 - Toby Cappello - Build and Scale AI With Trust & Transparency

    • East 2021 - Yuandong Tian, PhD - Learning to Optimize High-Dimensional Optimization Problems

    • East 2021 - Sam Bail, PhD - Building a Robust Data Pipeline with the 'dag Stack'_ dbt, Airflow, and Great Expectations

    • East 2021 - Sharon Yixuan Li - Reliable Open-World Learning Against Out-of-distribution Data

    • East 2021 - Manasi Vartak - Simplifying MLOps with Model Registry

    • East 2021 - Amber Chin Carlos Martinez - Narrative Extraction for Disinformation Detection

    • East 2021 - Haniyeh Mahmoudian - Tackling AI Bias

    • East 2021 - Hagay Lupesko - Introduction to Deep Learning for Recommendation Systems
  • 5

    Aix Business Talks

    • East 2021 - Marko Kangrga - Modern NLP Techniques for Dynamic Topic Modeling

    • East 2021 - Mark Weber - Overcoming Obstacles to AI Execution_ Trust, Scale, and Reasoning

    • East 2021 - Srinivas Chilukuri-Improving Structured Data ML Processes with Generative Adversarial Networks

    • East 2021 - Richard Sheng - Managing Data Science as Products

    • East 2021 - Siddharth Goyal - Open Catalyst Project Using AI to Model And Discover New Catalysts-Siddharth Goyal

    • East 2021 - Leo Anthony Celi, PhD - The Myth of Generalisability in Clinical Research and Machine Learning in Health Care

    • ODSC East - Anand Ranganathan- Chat with your Data_ Accessing Insights through Conversational Analytics

    • East 2021 - Lore Dirick - Using Survival Analysis to Model Credit Risk_ What, Why and How_

    • East 2021 - Serena Yeung - The Clinicians AI Partner Augmenting Clinician Capabilities Across the Spectrum of Healthcare

    • East 2021 - Anitha Kannan - AI-Powered Best Healthcare for Everyone

    • East 2021 - Nishan Subedi - Architectural Patterns in Machine Learning to Generate Sustainable Business Value

    • East 2021 - Gideon Mendels - Building Effective Machine Learning Teams

    • East 2021 - Kerry Weinberg - Challenges and Opportunities for Data Science in Digital Health

    • East 2021 - James Zou - Computer Vision for Healthcare and Medicine

    • East 2021 - Brooke Jamieson - The Persuasion Equation - How to Effectively Communicate Results to People Who Don’t Want to Listen