Digital Developer Conference Data & AI – IBM Developer

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Digital Developer Conference

Data & AI

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About the conference

Register for free and get ready to build smart and secure data and AI solutions on hybrid cloud with trust, resilience, and robustness. During the conference, you'll grow your expertise on IBM and open source technologies to build AI-centric platforms. Our selection of developer experts and clients guide you through the essentials, experiences, and exercises to make AI a worthwhile investment.

Reasons to attend

Focused on the AI development community of architects, data scientists, data engineers, developers, and machine learning practitioners, this conference provides a free opportunity to explore the challenges faced when working with data science, artificial intelligence, machine learning algorithms, and deep learning neural networks.

Learn data science and machine learning skills from trusted developer experts. See how other businesses found success by infusing AI into their business with trust and security, and how you can do the same. Get the latest from IBM Research and the open source community on deep learning neural networks and what it means for the industry, plus best practices for your next data competition or open source collaboration.

Your path to AI, ML, and data science certification

During the conference, you’ll earn digital badges from your time spent in the Data & AI Essentials Course—a great way to show your prowess with collecting, organizing, and analyzing data, infusing models, and more. Between this course, the labs, and the rest of the agenda, you’ll have a roadmap to AI, ML, and data science success, capped off with a professional certificate or specialization from Coursera.

Going live during the conference, take a break from learning for some livestreaming fun. Join the watch party and hang out with conference speakers and IBM Developer Advocates while they talk tech, do some live coding, and answer your questions.

Navigating your conference experience

4 dedicated tracks + live watch party

AI in Production

Clients share their challenges, and how they overcame them, through architectural and tooling solutions. Session topics include deploying models on the edge, cloud-based AI development environments, building personalized messaging at scale with AI, and the latest from IBM Research.

5 Hands-on Labs

Focused on the next level AI, ML, and data science these detailed walkthrough cover common design patterns used by developers today for the challenges of tomorrow. Session topics include AI fairness and bias detection and mitigation, deep reinforcement learning in finance, and building AutoAI pipeline for cyberthreat detection.

Data & AI Essentials Course

A condensed version of our popular end-to-end AI course, covering the complete AI ladder: collecting, organizing, and cleansing your data as well as building and infusing AI Models.

Data Competitions & Open Source

Experienced data scientists share best practices on model accuracy and winning data competitions, plus get the latest on the future of open source and state-of-the-art AI and ML, and be the first to learn about a new data competition from IBM.

Watch Party Livestream

IBM Developer Advocates Spencer Krum, JJ Ashgar, and Matt Hamilton host a watch party during the conference. Sessions speakers and other developer experts stop by to hang out, do some live coding, and answer your questions.

Call for Code Spot Challenge on Wildfires

Join a team of coders and data scientists to develop models to forecast potential wildfires in Australia in preparation for the upcoming 2021 wildfires season. We're excited to share data from the IBM Weather Operations Center Geospatial Analytics Center going back to 2005 for this project. Make a difference and maybe win a prize!

Featured speaker spotlight

In an effort to make this our most comprehensive, developer-focused data & AI conference to date, we've gathered some of the biggest names in the areas of data science, AI, and ML.

Industry-recognized data and AI skills

Build smart and secure data and AI solutions on hybrid cloud—essentials, experiences, and labs for devs, data scientists and engineers, and architects.

AI in production

Clients share their challenges, and how they overcame them, through architectural and tooling solutions. Session topics include deploying models on the edge, cloud-based AI development environments, building personalized messaging at scale with AI, and the latest from IBM Research.

Day 1: November 10, 2020

  • Speakers: Justin McCoy

    Make the most out of the client experiences in this track. Take a minute for an overview of the track agenda and the value of open source in the cloud and on the edge designed for AI before you dive deeper.

  • Speakers: Sriram Raghavan

    At IBM Research, our innovation agenda in AI is focused on advancing the scientific and technical foundations of the field while also enabling enterprises to operationalize and deploy AI at scale. In this talk, we will provide a window into our work with examples of exciting projects and innovations from three areas, First, we will describe our work in scaling AI by driving automation into the entire lifecycle of building deploying and managing AI modes, all while addressing enterprise needs for security scale and compliance. Second, we will talk about our innovations in trustworthy AI and our open toolkits that address the key elements of fairness, robustness, explainability and transparency of AI models. Finally, we will talk about our leading edge innovations in natural language processing (NLP) and how we are bringing in advances from exciting grand challenges such as Project Debater to meet the requirements and needs of enterprise NLP.

  • Speakers: Rama Akkiraju

    Recent advancements in Cloud computing, which makes compute available for rent, Natural Language Processing via pre-trained language models such as Bi-directional Encoder Representations from Transformers (BERT) for language understanding, and Machine Learning via interpretable and explainable machine learning models are all making it possible to infuse AI into and to optimize traditional business processes. For example, AI can be put to use into Information Technology (IT) operations management process for increasing application availability, early problem detection and prediction, and efficient problem resolution and problem avoidance leading to self-aware, self-healing and self-managing operations processes.

    In this talk, I will discuss the AI involved in preparing IT data for AI, the AI behind optimizing IT Operations Management, and the AI platform that powers the first two AIs. The AI in preparing IT data for AI includes entity extraction, entity resolution, and topology derivation. The AI pipelines in IT Operations Management include log and metric-based anomaly prediction, event grouping, fault localization, incident similarity, next best action prediction, and change risk prediction. The AI platform concerns include AI model training, feedback gathering, retraining, model monitoring and AI life cycle management. I will touch upon the differences between the role of a data scientist who builds the analytical pipelines in the product versus an operations person who manages the analytical pipelines in production in a customer environment and stress upon how AI platforms must be built differently for these two personas.

    This session is for Data & AI product builders, data scientists and engineering managers who aim to build consumable AI-infused products.

    Attendees will gain an understanding of the concerns and topics involved in building consumable, and production ready AI-infused solutions.

  • Speakers: David Bartram-ShawKarima Zmeril

    The session is covering a unique challenge where we had to help our client predict the impact of Media on in store and online sales (over 100 stores). We/WPP as a group own multiple data assets, those data assets are siloed given their nature and what this data is used for historically.
    As a media agency we knew that we had to understand the non-media driver of sales in each geography using Wunderman Identity Network to which we layered in the media spend and engagement data as well as client sales data at a point of sales level.
    The volume of data we have access is larger than any typical Media Mix Model which is usually limited to media and macro level data modeled at a weekly level.
    We connected the data that was siloed and sitting with different business units, and we had a vision on how this data work together. We leverage the capabilities our IBM partners brought to the table from Data and AI portfolio and expertise to build a new product that will evolve our business and knowledge of consumers and their behaviors. This is approach allowed us to go to micro targeting and personalization with remaining complaining to laws and regulations around privacy.
    The attendees will gain insight on the approach to define the ask and how we solved for the siloed data challenges.

  • Speakers: Peter Wang

    This talk covers some of the lessons we've learned at Anaconda as we see businesses try to adopt open source data science. It's primarily for a business or manager audience, although we do touch on some deeper technical topics. Attendees will walk away with a deeper appreciation for the unique challenges of the data science revolution, and how to better think about some of the problems that arise between data scientists, software devs, and IT folks.

  • Speakers: Don Scott

    2020 marks the 400th anniversary of the original Mayflower voyage from Plymouth, UK to Plymouth, USA. To commemorate this anniversary, we have built the Mayflower Autonomous Ship - a 'Mayflower' for the 21st century that embodies the pioneering spirit of the original voyage but embraces ground-breaking technology encompassing design, propulsion and autonomous vehicle control. The ship is completely unmanned and will have limited contact as it traverses the unpredictable North Atlantic. The ship is controlled by an AI Captain, enabled by key IBM technology offerings such as Maximo Visual Insights, Edge, ODM, CPlex Optimizer, and the Weather Company. Join us in a presentation on the challenges of designing, building, and testing the ultimate edge device.

  • Speakers: Francesca Rossi

    AI is going to bring huge benefits in terms of scientific progress, human wellbeing, economic value, and the possibility of finding solutions to major social and environmental problems. Supported by AI, we will be able to make more grounded decisions and to focus on the main values and goals of a decision process rather than on routine and repetitive tasks. However, such a powerful technology also raises some concerns, related for example to the black-box nature of some AI approaches, the possible discriminatory decisions that AI algorithms may recommend, and the accountability and responsibility when an AI system is involved in an undesirable outcome. Also, since many successful AI techniques rely on huge amounts of data, it is important to know how data are handled by AI systems and by those who produce them. These concerns are among the obstacles that hold AI back or that cause worry for current AI users, adopters, and policy makers. Without answers to these questions, many will not trust AI, and therefore will not fully adopt it nor get its positive impact. In this talk I will present the main issues around AI ethics, describe some of the proposed technical solutions, and mention some of the many initiatives that have been built in the past few years to address the technical, policy, and legal challenges, as well as the ethical concerns, around AI.

  • Speakers: Aaron Baughman

    Take a dive into how we are applying AI to the world of ESPN Fantasy Football with 'Player Insights with Watson', and our new feature this year 'Trade Assistant with Watson'. You will learn about AI techniques that increase in complexity up to neural optimization approaches that are delivered 2 billion times per day to millions of users around the world. This session is for AI and sports enthusiasts who want to understand continuously on-demand and at-scale AI. We will introduce OpenShift, AI algorithms, NLP, Watson Discovery, OpenScale, Watson Machine Learning and many other exciting capabilities.

  • Speakers: Bill HigginsJustin McCoyMisha Sulpovar

    In March 2020, as COVID-19 exploded across the United States, a self-assembled team of IBM Data, AI, and Cloud developers self-assembled and built a scalable data lake of trusted COVID-19 incident data with granularity down to a U.S. county level. In just one week they went from an empty Slack channel to a deployed solution available to 300 million users. This task was especially challenging because the data was fragmented across various state web sites, and often buried in PDF documents and PNG images for which we needed to use our Watson Natural Language Processing to accurately parse.

    This is a story of climbing the AI ladder in a hyper-accelerated manner, and is an excellent story of business and technical agility, and breaking down organizational silos to achieve great user outcomes.

  • Speakers: Ruchir Puri

    It is said that Software is eating the world! As the impact of AI on Society continues to expand, we will discuss the question “Can AI eat software?.” In some ways, that goal is a reality today. Thousands of lines of painstakingly written computer vision, speech and natural language understanding code can be replaced by automatically trained Data driven AI models. However, the goal of AI to truly understand software remains elusive. Just like human languages, programming languages have context. The meaning of a particular statement on a line actually is related to what occurs before, and deriving that context and making the translation, just like human languages, takes a lot of effort and time and resources. And the larger the program gets, the harder it gets to translate it over, even more so than human languages. While in human language, the context may be limited to that paragraph or maybe that particular document, here the context can actually relate to multiple libraries and other services that are related to that particular program. In this talk, we will discuss where we are in AI’s journey to ease our pain points as software developers.

  • Speakers: Maggie Lin

    Critical enterprise applications often run on IBM Z and can generate the majority of an organizations high-value data. This session will introduce you to Watson Machine Learning for z/OS, an end to end machine learning offering that delivers unique value to your mission critical applications with AI and machine learning initiatives. You get the opportunity to see demos of how you can build models on your platform of choice and readily deploy those models directly within your production applications on Z.

  • Speakers: Vaclav Pavlin

    Big data and AI/ML infrastructure is quite challenging problem space, but we believe it is worth exploring. Let’s take a look at what roles Red Hat OpenShift can play in this space and how it can help developers and data scientists to achieve more by making sharing easier.
    We’ll also discuss the challenge of enabling and managing specialized hardware across the technology stack and touch on why automation is key when we move our data exploration tools from our laptops to hybrid clouds. A brief peak into the Open Data Hub project will connect the dots from the talk and provide immediate next steps for interested participants in the audience.

  • Speakers: Jake Collins

    In this session, I will cover our current journey to containerising Cora, the Bank’s conversational assistant. This involves moving from the existing Cloud Foundry centric method supported by manual delivery procedures to a Cloud First approach. I will explain how using Cloud Pak for Apps allows the Bank to leverage containerisation and CI/CD and remove the manual work, so that we can significantly accelerate benefit for customers. Also, I will talk through how implementing CI/CD in Urban Code Deploy (UCD), can put changes to AI and content in the hands of the business and significantly reduce the need for technology involvement in these types of changes. We will example the simplified deployment process and how it offers the business the agility to deliver change to customers quickly while maintaining the necessary level of governance and auditability.

Meet the speakers

Developer experts and leaders in artificial intelligence, machine learning, and data science have come together to share their expertise to elevate your skills.

  • Aaron Baughman

    Distinguished Engineer

  • Bill Higgins

    Distinguished Engineer

  • Dale Davis

    VP and IBM Distinguished Engineer

  • David Bartram-Shaw

    Director Data Science & Engineering - Wunderman-Thompson

  • David Carew

    Software Developer

    View this speaker
  • Don Scott

    CTO - Mayflower Autonomous Ship & MarineAI

  • Fernando Perez

    Associate Professor, Statistics, UC Berkeley, co-founded Project Jupyter, NumFOCUS, BIDS, and

  • Francesca Rossi

    IBM Fellow and AI Ethics Global Leader

  • Greg Bramble

    Research Software Engineer

  • Hania Abrahim

    Developer Advocate

  • Hendrik Hamann

    Chief Scientist for Geoinformatics and PAIRS Geoscope

  • Ibrahim Haddad

    Executive Director, LF AI & Data Foundation

  • Jake Collins

    NatWest Group

  • Justin McCoy

    Program Director - IBM Cloud and Cognitive Software

    View this speaker
  • Karen Matthys

    Executive Director, Institute for Computational and Mathematical Engineering at Stanford

  • Karima Zmeril

    Chief Data Science Officer, Wavemaker Global

  • Lisa Seacat DeLuca

    Director, Emerging Solutions - Weather, Digital Twin & Agile Accelerator

  • Maggie Lin

    IBM Machine Learning Development

  • Margriet Groenendijk

    Developer Advocate

  • Misha Sulpovar

    AI Leader - The Weather Company

  • Omid Meh

    Developer Advocate

  • Patrick Titzler

    Developer Advocate - CODAIT: Center for OpenSource

  • Peter Wang

    CEO, Anaconda Inc

  • Pooja Mistry

    Developer Advocate

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  • Priyanka Sharma

    General Manager of CNCF at the Linux Foundation

  • Rama Akkiraju

    IBM Fellow, CTO AIOps

  • Romeo Kienzler

    Chief Data Scientist IBM Center for Open Source Data and AI Technologies

  • Ruchir Puri

    Chief Scientist, IBM Research

  • Saishruthi Swaminathan

    Data Scientist / Developer Advocate- CODAIT

  • Scott D'Angelo

    Developer Advocate

  • Sriram Raghavan

    VP, IBM Research AI

  • Sulakshan Vajipayajula

    STSM - IBM Security

  • Sundar Saranathan

    Software Architect

  • Susan Malaika

    STSM: Data & AI Open Tech Special Projects

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  • Todd Moore

    VP - Open Technology, CTO DEG

  • Vaclav Pavlin

    Principle Software Engineer, Red Hat

See all the speakers

Featured ecosystem partners

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Earn digital badges

A digital badge is an online, sharable, industry-recognizable form of achievement. Use them to showcase your hard work, knowledge, and commitment to professional growth.

Special offer from IBM & Coursera

An exclusive offer to attendees of the conference, get your first month free on select specializations or professional certifications on the following AI, ML, and data science courses:

IBM AI Enterprise Workflow Specialization
IBM Machine Learning Professional Certificate
IBM Data Science Professional Certificate
Advanced Data Science with IBM Specialization

Restrictions apply. Offer valid only for attendees to the conference. Offer expires March 30, 2021. Offer may not be combined with other discounts. Additional details provided after registration.