Data and AI Airlift - Sydney Australia January 2019
Register today for these workshops, designed to give attendees a hands-on view of the scalable Data and AI solutions on Azure. The contents of these 3-day workshops will align to a solution-based approach on how customers look at their Data + AI stack, what challenges they face, and how Azure’s services cater to those challenges.
Date: 30 January - 1 February, 2019
Location: Sydney Harbour Marriott
Time: 08:30-17:00 each day
Cost: $899 AUD
| Operational Databases and Azure | Analytics with Modern Data Warehousing | AI – Machine Learning | AI – Apps and Agents |
| Register | Register | Register | Register |
| Learn how modernizing to SQL Server 2017 and Azure SQL Database Managed Instance helps our customers and partners build modern applications with high-availability, scalability, in-memory performance and security built-in. You will also learn how customers will be able to leverage Azure Cosmos DB, a globally distributed, multi-model NoSQL database with full compatibility with Mongo, Cassandra, Gremlin, and many more. | Learn how to setup a data analytics solution that pans from data ingestion to reporting and visualization. This session will take you through this journey. You will learn how to ingest data, structured and unstructured, store it, analyze it, create a process pipeline and finally report it. | Machine Learning is amongst the most preferred competencies our customers are chasing, to build intelligence into their next gen solutions and understand business behaviors. As a partner, we’d like to enable you to build a strong practice on this competency, by inviting your core team into this deep-dive, hands-on workshop on leveraging Azure Databricks and Azure Machine Learning to build custom AI solution on Azure for customers. | Artificial Intelligence is top of mind for every customer. For our partners to be able to tap into this huge opportunity, we’ve created a hands-on workshop to enable AI Dev teams to be able to build the right practices for design and development of AI solutions. Covering Cognitive Services, Bot Service and Cognitive Search capabilities, this workshop will ready your delivery team to be able to envision and develop the best Applied AI solutions for customers. |
| Agenda | |||
| Day 1: SQL Server 2017· SQL Server 2017 customer use cases and scenarios· What’s new in SQL Server 2017· SQL Server on Linux and Docker Containers· Upgrading to SQL Server 2017 | Day 1: Ingest and Store Data· Modern Data Warehousing patterns and use cases· Data pipeline using Azure Data Factory, Azure SQL DW and Azure Databricks· Introduction to SQL DW | Day 1: Machine Learning Introduction and Spark Concepts· Spark Overview· Spark Internals· Spark MLlib Pipeline API· NLP/Text Classification with Logistic Regression· Built-in featurizers and Algorithms | Day 1: Cognitive Services· Introduction and Context for Cognitive Services· Simplifying Cognitive Services App Development· Creating an Image Classification Application· Developing Intelligent Applications with LUIS |
| Day 2: Azure SQL Database and Managed Instance· Azure SQL Database and Managed Instance Concepts and Architecture· Migrating to Azure SQL Database Managed Instance· Management, Monitoring and Integration of Azure SQL Database Managed Instance | Day 2: Azure Databricks· Azure Databricks and reading structured/unstructured data from multiple sources· Building Data Engineering pipelines with Spark SQL and DataFrames· Publishing curated, cleansed data into Azure SQL DW· Analyzing Spark jobs using the administration UIs inside Databricks. | Day 2: Machine Learning Models and practices· Decision Tree vs. Random Forest· Cross-Validation and Grid Search for Hyperparameter Tuning· Evaluation Metrics· Data Partitioning Strategies· Data imputation with Alternating Least Squares | Day 2: Building intelligent agents· Introduction and Context for Bots· Building Intelligent Bots· Log Chat Conversations in your Bot· Testing your Bot |
| Day 3: Cosmos DB· Azure Cosmos DB core capabilities and use cases· Building Applications using Azure Cosmos DB· Migrating Mongo/C*/Gremlin applications to Azure Cosmos DB· Using Cosmos DB as analytical datastore using Spark· Performance tips and best practices | Day 3: Prep and Train, Model and Serve· Behind the scenes – workings of SQL DW Gen2· Azure SQL DW Security and Performance· Migration from on premises to Azure SQL DW· BI reporting· ETL pipeline creation | Day 3: Machine Learning libraries and DevOps· Clustering with K-Means· Spark integration with Scikit-learn· Neural Networks· Model Management and Deployment | Day 3: Designing intelligent agents, Knowledge mining· Designing and architecting intelligent bot solutions· Developing Intelligent Applications with Azure Cognitive Search |