Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
 
2010
Add Big data for managers to your personal schedule
9:00am Big data for managers Michael Li (The Data Incubator), Rich Ott (The Data Incubator)
2014
Add Machine Learning from Scratch in TensorFlow to your personal schedule
9:00am Machine Learning from Scratch in TensorFlow Robert Schroll (The Data Incubator)
2016
Add Hands-On Data Science with Python to your personal schedule
9:00am Hands-On Data Science with Python Zachary Glassman (The Data Incubator)
2018
Add Building a Serverless Big Data Application on AWS to your personal schedule
9:00am Building a Serverless Big Data Application on AWS Jorge A. Lopez (Amazon Web Services)
2020
3016
Add Professional Kafka Development to your personal schedule
9:00am Professional Kafka Development Jesse Anderson (Big Data Institute)
3018
10:30am Morning break | Room: 2nd floor lobby
12:30pm Lunch | Room: 2nd floor lobby
3:00pm Afternoon break | Room: 2nd floor lobby
9:00am-5:00pm (8h) Strata Business Summit AI and machine learning in the enterprise
Big data for managers
Michael Li (The Data Incubator), Rich Ott (The Data Incubator)
Michael Li and Rich Ott offer a nontechnical overview of AI and data science. Learn common techniques, how to apply them in your organization, and common pitfalls to avoid. You’ll pick up the language and develop a framework to be able to effectively engage with technical experts and utilize their input and analysis for your business’s strategic priorities and decision making.
9:00am-5:00pm (8h) Data Science, Machine Learning & AI Deep Learning
Machine Learning from Scratch in TensorFlow
Robert Schroll (The Data Incubator)
The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. This training will introduce TensorFlow's capabilities in Python. It will move from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow with several hands-on applications.
9:00am-5:00pm (8h) Data Science, Machine Learning & AI
Hands-On Data Science with Python
Zachary Glassman (The Data Incubator)
We will walk through all the steps - from prototyping to production - of developing a machine learning pipeline. We’ll look at data cleaning, feature engineering, model building/evaluation, and deployment. Students will extend these models into two applications from real-world datasets. All work will be done in Python.
9:00am-5:00pm (8h) Data Engineering & Architecture AI and Data technologies in the cloud
Building a Serverless Big Data Application on AWS
Jorge A. Lopez (Amazon Web Services)
Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. In this workshop, we show you how to incorporate serverless concepts into your big data architectures, looking at design patterns to ingest, store, and analyze your data. You will build a big data application using AWS technologies such as S3, Athena, Kinesis, and more
9:00am-5:00pm (8h) Data Science, Machine Learning & AI Deep Learning
Expand your data science and machine learning skills with Python, R, SQL, Spark, and TensorFlow
Ian Cook (Cloudera)
Advancing your career in data science requires learning new languages and frameworks—but learners face an overwhelming array of choices, each with different syntaxes, conventions, and terminology. Ian Cook simplifies the learning process by elucidating the abstractions common to these systems. Through hands-on exercises, you'll overcome obstacles to getting started using new tools.
9:00am-5:00pm (8h) Data Engineering & Architecture Streaming and realtime analytics
Professional Kafka Development
Jesse Anderson (Big Data Institute)
Takes a participant through an in-depth look at Apache Kafka. We show how Kafka works and how to create real-time systems with it. It shows how to create consumers and publishers in Kafka. The we look at Kafka’s ecosystem and how each one is used. We show how to use Kafka Streams, Kafka Connect, and KSQL.
9:00am-5:00pm (8h) Data Science, Machine Learning & AI Deep Learning, Financial Services, Temporal data and time-series analytics
Forecasting Financial Time Series with Deep Learning on Azure
Francesca Lazzeri (Microsoft)
Francesca Lazzeri will walk you through the core steps for using Azure Machine Learning services to train your machine learning models both locally and on remote compute resources.
10:30am-11:00am (30m)
Break: Morning break
12:30pm-1:30pm (1h)
Break: Lunch
3:00pm-3:30pm (30m)
Break: Afternoon break