Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

Training courses

Each training course takes place 9:00am - 5:00pm on Tuesday, September 11.
In order to maintain a high level of hands-on learning and instructor interaction, each training course is limited in size. To attend a training course, you must register for a Platinum or Training pass; does not include access to tutorials.

Tuesday, September 11

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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1A 03 Level: Intermediate
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 and explains how to choose the right one for your company. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1A 01/02 Level: Beginner
Ian Cook (Cloudera)
Advancing your career in data science requires learning new languages and frameworks—but learners face an overwhelming array of choices, with different syntaxes, conventions, and terminology. The instructor will simplify the learning process by elucidating the abstractions common to these systems. Through hands-on exercises, participants will overcome obstacles to getting started using new tools. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1 E02
Zachary Glassman (The Data Incubator)
The Data Incubator offers a foundation in building intelligent business applications using machine learning. 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 an application using a real-world dataset. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1A 15/16
Dylan Bargteil (The Data Incubator)
The TensorFlow library provides for the use of data flow graphs for numerical computations, with automatic parallelization across several CPUs or GPUs. This architecture makes it ideal for implementing neural networks and other machine learning algorithms. This training will introduce TensorFlow's capabilities through its Python interface. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1E 17 Level: Intermediate
Delip Rao (R7 Speech Science)
Explore machine learning and deep learning with PyTorch and walk you through how to build effective models for real world data. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1A 17
The instructor walks you through the core APIs for using Spark, fundamental mechanisms and basic internals of the framework, SQL and other high-level data access tools, and Spark’s streaming capabilities and machine learning APIs. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1A 04/05
Acquiring machine-learning (ML) technology is relatively straightforward, but ML must be applied to be useful. In this one-day boot camp, we teach students how to apply advanced analytics in ways that reshape the enterprise and improve outcomes. This training is equal parts hackathon, presentation, and group participation. Read more.