Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
 
212 A-B
Add Apache® Spark™ Programming to your personal schedule
9:00am Apache® Spark™ Programming Brooke Wenig (Databricks)
212 C
212 D
Add Data Science for Managers to your personal schedule
9:00am Data Science for Managers Angie Ma (ASI)
111
114
Add Real-time systems with Spark Streaming and Kafka to your personal schedule
9:00am Real-time systems with Spark Streaming and Kafka Jesse Anderson (Big Data Institute)
San Jose Ballroom (salon 1&2)
Add Machine Learning with PyTorch to your personal schedule
9:00am Machine Learning with PyTorch Delip Rao (Joostware), Brian McMahan (Joostware)
Willow Glen (1&2)
9:00am-5:00pm (8h) Data science and machine learning
Apache® Spark™ Programming
Brooke Wenig (Databricks)
This 2-day course is for data engineers, analysts, architects; software engineers; IT operations; and technical managers interested in a thorough, hands-on overview of Apache Spark. It covers the core APIs for using Spark, fundamental mechanisms and basic internals of the framework, SQL and other high-level data access tools, as well as Spark’s streaming capabilities and machine learning APIs.
9:00am-5:00pm (8h)
Cloudera Data Scientist Training
This 2-day workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business...
9:00am-5:00pm (8h)
Data Science for Managers
Angie Ma (ASI)
The course provides you with a condensed introduction to the key concepts and techniques of data science and machine learning. It will allow you to know what is and is not possible with these exciting new tools, and understand how they can benefit your organization.
9:00am-5:00pm (8h) Data science and machine learning
Machine learning with TensorFlow
The instructors demonstrate TensorFlow's capabilities through its Python interface and explore TFLearn, a high-level deep learning library built on TensorFlow. Join in to learn how to use TFLearn and TensorFlow to build machine learning models on real-world data.
9:00am-5:00pm (8h) Big data and data science in the cloud
Real-time systems with Spark Streaming and Kafka
Jesse Anderson (Big Data Institute)
To handle real-time big data, you need to solve two difficult problems: how do you ingest that much data and how will you process that much data? Jesse Anderson explores the latest real-time frameworks (both open source and managed cloud services), discusses the leading cloud providers, and explains how to choose the right one for your company.
9:00am-5:00pm (8h)
Machine Learning with PyTorch
Delip Rao (Joostware), Brian McMahan (Joostware)
We take you through a two-day journey that explores PyTorch's capabilities, how to build deep learning models, and how to apply them to real world problems. PyTorch is a recent deep learning framework from Facebook that is gaining massive momentum in the Deep Learning community. Its fundamentally flexible design makes building and debugging models straightforward, simple, and fun!
9:00am-5:00pm (8h)
Hands-on Data Science with Python
Details to come.