Identify the best artificial intelligence (AI) use case to help solve complex challenges in 2020. Whether you are in a government, nonprofit, university, or hospital setting, this webinar series is designed to help educate those new to AI, spark new ideas for business stakeholders, and deep dive technical execution for developers.

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100,000+ databases migrated to AWS 10,000+ data lakes and data warehouses deployed on AWS Hundreds of thousands of customers rely on AWS Databases

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  • At vero eos et accusamus et iusto odio dignissimos
  • Ducimus qui blanditiis praesentium voluptatum
  • Deleniti atque corrupti quos dolores et quas Molestias excepturi sint occaecati cupiditate non
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Event Agenda

45 mins Keynote
  Track 1 - Get started: Moving your data to the cloud Track 2 - Building apps with modern databases Track 3 - Get started: Building your data lake Track 4 - Analyzing and getting insights
40 mins Migrate your Oracle and SQL Server databases to Amazon RDS (200) Which database to choose: Pick the right purpose-built database for the job (200) How to go from zero to data lake in days (200) Amazon Redshift use cases and deployment patterns (400)
Migrate your on-premises Data Warehouse to Amazon Redshift (200) Building large scale data-driven apps with AWS databases (300) Picking the right analytical engine for your needs (200) Processing Big Data with Hadoop, Spark, and other frameworks in Amazon EMR (300)
40 mins Why cloud databases like Amazon Aurora are more scalable and reliable (300) Extreme Performance at Cloud Scale: supercharge your real-time apps with Amazon ElastiCache (300) Breaking the silos: Extending your DW to your data lake (300) Scalable, secure log analytics with Amazon Elasticsearch Service (200)
Deploying open source databases on AWS (200) Databases for building business-critical enterprise apps (300) Big data in the era of heavy privacy regulations (200) Scalable, secure log analytics with Amazon Elasticsearch Service (200)
40 mins Why cloud databases like Amazon Aurora are more scalable and reliable (300) Extreme Performance at Cloud Scale: supercharge your real-time apps with Amazon ElastiCache (300) Breaking the silos: Extending your DW to your data lake (300) Scalable, secure log analytics with Amazon Elasticsearch Service (200)
50 mins Customer spotlight 1: How iRobot built the Roomba to use real-time data to smartly clean your home - 45 min or Customer spotlight 2: Equinox’s Data Warehouse modernization journey - 45 min Conclusion - 5 min

Session Details

  • Track1 Session 1
  • Track2 Session 1
  • Track3 Session 1
  • Track4 Session 1
  • Track5 Session 1
  • Track6 Session 1
  • Track7 Session 1
  • Track8 Session 1
  • Track9 Session 1
  • Track10 Session 1

Track1 Session 1

Migrate your Oracle and SQL Server databases to

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track2 Session 1

Migrate your Oracle and SQL Server databases to

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track3 Session 1

Tab 3 content

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Track4 Session 1

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Track5 Session 1

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Track6 Session 1

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Track7 Session 1

Tab 7 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track8 Session 1

Tab 8 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track9 Session 1

Tab 9 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track10 Session 1

Tab 10 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Multiple City Registration

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Venue

The Meteropolitian
233 south wacker drive, 67th floor, Chicago, Illinois 60606

Watch now »

Episode 1
Introduction to AI

This is an introductory session on AI. In this course, learn what AI is and why it is important in the public sector. Take a look at machine learning and deep learning, which are subsets of AI, and see how AWS uses AI in its products. We recommend this session for individuals who are new to AI and would like an overview of AWS’s services for AI and ML. 

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Episode 2
Apply ML to detect patterns of fraud, waste, and abuse

Machine learning is an effective and well-known solution for identifying fraud. But did you know that machine learning can also be used to detect human error or misuse? By identifying and addressing fraud, waste, and abuse patterns, such as in citizen benefit programs, your organization can more efficiently manage costs and help citizens receive proper support. We recommend this session for individuals who may be new to machine learning as well as proficient developers who would like to learn more about fraud detection use cases. 

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Episode 3
Automate document management and improve search, discovery, and insights with AI

Public sector organizations spend a significant amount of time and resources cataloging and managing documents, forms, records, media, and other types of assets. These processes can be intelligently automated using AI-powered solutions such as transcription, translation, metadata extraction, and classification. The business benefits include the ability to enable search and discovery as well as reduce the time spent on data entry. We recommend this session for individuals who may be new to machine learning as well as proficient developers who would like to learn more about digital content automation use cases.

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Episode 4
Improve student outcomes with ML

With remote online learning becoming prevalent, new technologies can support new models of teaching and learning. Attend and discover how AI can detect patterns and improve the remote learning experience with a focus on student engagement and success. Solutions covered include tracking student absenteeism to intervene early and prevent dropouts, as well as helping college transfer students identify majors. Customer examples are highlighted from K12 organizations like Chesterfield County Public Schools to higher education institutions like Portland State University. We recommend this webinar for those who are new to machine learning and developers who want to learn more about education use cases.

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Episode 5
Extract insights from unstructured medical data with AI

Hospitals generate a vast amount of medical data, including doctor’s notes, clinical trial reports, patient health records, and tele-medicine appointments. This data is often unstructured, making it difficult to digitize, organize, and cross-reference. This session shows you the possibilities for automating transcription and extraction of medical information from documents and forms using AI. We recommend this session for those who are new to machine learning as well as developers who would like to learn about healthcare use cases.

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Episode 6
ML for forecasting service demand and planning capacity

More and more organizations are using advanced analytics based on historical records to plan resource allocation. While ML solutions have recently been proven to be a good alternative to forward models in predicting demand, traditional techniques – mainly models based on the current state of the system – are still preferred in many applications. This session provides an overview of common challenges you may face when evaluating your machine learning or forward models. We recommend this session to developers proficient in building and deploying machine learning models. 

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Episode 7
Monitoring and modifying ML models when major events occur

Machine learning models are built and optimized based on a data set at a given point in time. If the underlying data behind the ML model changes quickly or dramatically, the model may have difficulty automatically adjusting and its accuracy could be impacted. This session provides best practices for monitoring, alerting, and retraining your ML models should a major event impact the data. We recommend this session to developers proficient in building, deploying, and monitoring machine learning models.

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Session Proficiency Levels Explained

  • Level 100

    Introductory

    Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic

  • Level 200

    Intermediate

    Sessions will focus on providing best practices, details of service features and demos with the assumption that attendees have introductory knowledge of the topics

  • Level 300

    Advanced

    Sessions will dive deeper into the selected topic. Presenters assume that the audience has some familiarity with the topic, but may or may not have direct experience implementing a similar solution

  • Level 400

    Expert

    Sessions are for attendees who are deeply familiar with the topic, have implemented a solution on their own already, and are comfortable with how the technology works across multiple services, architectures, and implementations

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Featured Speakers


  • Video 1

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  • Raju Gulabani, VP of Databases, Analytics & AI, AWS

    Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.

  • Ryan Kelly, Data Architect, Equinox

    Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox

  • Richard Boyd, Cloud Data Engineer, iRobot

    Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.

  • Raju Gulabani, VP of Databases, Analytics & AI, AWS

    Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.

  • Ryan Kelly, Data Architect, Equinox

    Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox

  • Richard Boyd, Cloud Data Engineer, iRobot

    Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.

  • Raju Gulabani, VP of Databases, Analytics & AI, AWS

    Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.

  • Ryan Kelly, Data Architect, Equinox

    Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox

  • Richard Boyd, Cloud Data Engineer, iRobot

    Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.

Customer Highlights

Epic Logo Image

Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.

Epics Games

Yelp Logo Image

Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.

Yelp

Airbnb Logo Image

Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.

Airbnb

Lyft Image

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FAQS

  1. Where is AWS Innovate hosted?
  2. What is the price of attending AWS Innovate?
  3. Who should attend AWS Innovate?
  4. How do I get the certificate of attendance?
Q: Where is this event?

A: This event is an online event, hosted by AWS on the INXPO platform.

Q: Who should attend this event?

A: Developers building data-driven apps; DBAs and data engineers who are building analytics infrastructure and data pipelines; Analysts and data scientists who are deriving insights that answer complex business quesions and building/trainining machine learning models.

Q: How much does this event cost?

A: There is no cost to attend this event.

Q: What are the prerequisites before attending the event?

A: There are no prerequisites for attending the event. We encourage attendees to browse the Database and Analytics pages on the AWS website to get a brief overview of the services available to them.