Course curriculum

  • 1

    Deep Learning

    • Keynote: Towards Learning Systems that Require Less Annotation - Pieter Abbeel

      FREE PREVIEW

    • Adversarial Attacks On Deep Neural Networks - Sihem Romdhani

    • Deep Learning For Real Time Streaming Data With Kafka And Tensorflow - Dr. Yong Tang

    • Deep Learning From Scratch - Seth Weidman

    • Deep Learning On Mobile - Anirudh Koul

    • Distributed Tensorflow: Scaling Your Model Training - Dr. Neil Tenenholtz

    • Elementary Worldly Data Science - Josh Wills

    • Let's Embed Everything! - Dr. Mayank Kejriwal

    • Practical AI Solutions Within Healthcare And Biotechnology - Dr. Michael Segala

    • RAPIDS: The Platform inside and out - Joshua Patterson

    • Training Data For Your Cnn: What You Need And How To Get It - Dr. Carlo Dal Mutto
  • 2

    Machine Learning

    • Keynote: Power and Limitations of Machine Learning Tools for Clinical Applications - Regina Barzilay

      FREE PREVIEW

    • Building Highly Autonomous Marketing Automation Systems - Ilya Katsov

    • Data Efficiency Through Transfer Learning - Eddie Du

    • Generative Adversarial Networks for Image Synthesis and Translation - Dr. Jan Kautz

    • Neuroevolution-based Automated Model Building: How to Create Better Models - Keith Moore

    • Privacy-Preserving Machine Learning in TensorFlow with TF Encrypted - Yann Dupis, Jason Mancuso

    • Programming Machine Learning with Weak Supervision - Alex Ratner

    • Why Do Tree Ensembles Work? - Dr. Joseph Ross

    • Real-Time Anomaly Detection In Surveillance Feeds - Utkarsh Contractor
  • 3

    Data Visualization

    • Data Storytelling: The Essential Data Science Skill - Isaac Reyers

    • Declarative Data Visualization with Vega-Lite & Altair - Dr. Kanit Wongsuphasawat, Dr. Arvind Satyanarayan

    • Pan-Cancer Machine Learning Predictors Of Primary Site Of Origin And Molecular Subtype - Joshy George

    • Real-Time Intelligence With Dash: A Productive, Open-Source Python Framework For The Modern Data Analyst - Chelsea Douglas
  • 4

    Data Science Management

    • Data Science for Health and Wellness - Dr. Robert Haslinger

    • Defending Open Source & Data Science in the New Era of ML & AI - Peter Wang

    • Making Data Science: Aig, Amazon, Albertsons - Dr. Haftan Eckholdt

    • The Dataops Manifesto - Christopher P. Bergh, Gil Benghiat

    • The Role Of Big Data Analytics In Industry 4.0 - Dr. Aleksandar Lazarevic
  • 5

    Open Source Data Science

    • Build, Run and Manage Risk Models for Performance, Bias, and Explainability - Yong Li

    • From Zero To Airflow: Bootstrapping Into A Best-In-Class Risk Analytics Platform - Ido Schlomo

    • I Like Notebooks - Moonsoo Lee

    • Imitation Learning: Reinforcement Learning For The Real World - Dr. Byron Galbraith

    • Scaling AI Applications With Ray - Richard Liaw

    • State-Of-The-Art Text Classification With Ulmfit - Matthew Teschke

    • Uber's Experimentation Monitoring Tool - Dr. Suman Bhattacharya

    • When The Bootstrap Breaks - Dr. Ryan Harter
  • 6

    Data Science for Good

    • Digital Discrimination: Cognitive Bias in Machine Learning - Maureen McElaney Brendan Dwyer

    • How To Actually "Do" Data Privacy - Dr. Laura Noren

    • What is Data Good for? Bringing Data Strategy to Life at USA for UNHCR - Jennylyn Sy

    • Artificial Intelligence Safety and Security - Dr. Roman Yamploskiy
  • 7

    Accelerate AI Summit (Cross Industry)

    • AI for Good: Bad Guys, Messy Data, & NLP - Christopher Mack

    • Data Art: Seeing the Future - Jane Adams

    • Expanding Nonprofit Workforce with Deep Learning - Richard Palmer, David Woodruff

    • Machine Learned Ranking for LegalTech - Carl Hoffman, Dr. Brian Carrier

    • Leading Data Science Teams: A Framework to Help Guide Data Science Project Managers - Dr. Jeffrey Saltz

    • Building an Analytics Team - Hillary Green-Lerman

    • Data Science + Design Thinking: A Perfect Blend to Achieve the Best User Experience - Michael Radwin

    • Understanding Artificial Intelligence Results to Increase their Value & Avoid Pitfalls - Dr. Linda Zeger

    • Data Science for Risk Mitigation in a Global Economy - Prabhu Sadasivam

    • Thirty Minutes to Answers: Data Science's Great Compression and It's Next Frontier - Benn Stancil

    • What to Expect When You Are Putting A.I. in Production - Dr. David Talby

    • Adopting A Machine Learning Mindset: How To Discover, Develop, And Deliver Automation Solutions Company-Wide - Dr. Marsal Gavalda

    • Artificial Intelligence In Business Gets Real - Dr. Sam Ransbotham

    • Automated Detection of Street-Level Product Displays - Isha Chaturvedi

    • Big Data And Mobility Analytics: What Can We Learn From The Way Things (And Humans) Move - Dr. Anturo Amador

    • Building an Effective Data Science Project Portfolio for your Business - Kerstin Frailey

    • DeepOps: Building an AI First Company - Yuval Greenfield

    • Democratizing Artificial Intelligence In A Business Context - Olivier Blais

    • How Keyence Uses AI To Answer Everyday Business Questions - Brian Neely

    • Improving Data Quality for Superior Results - Kaitlin Andryauskas

    • More Women In Data Science: Creating The Pipeline - Bobbie Carlton

    • Recent Advances In Machine Learning With Applications To Internet Of Things - Adam McElhinney

    • Winning the AI talent race - Gautam Tambay

    • Building an "Automation-First Data Science Team" - Dr. Greg Michaelson

    • Predictive Analytics For Wealth Management And Beyond - Meina Zhou

    • Accelerate AI Development with Transfer Learning - Anjali Shah & Steve Ginger

    • Natural Language Processing: Deciphering The Message Within The Message – Stock Selection Insights Using Corporate Earnings Calls - Frank Azhao

    • Artificial Intelligence To Revolutionize Child Behavioral Diagnostics and Therapeutics - Halim Abbas

    • AI in Medicine: Avoiding Hype and False Conclusions - Michael Zalis

    • Major Applications of AI in Healthcare - Alex Ermolaev

    • Integrating Data Science Into Commercial Pharma: The Good, The Bad, And The Validated - Dr. Adam Jenkins