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 15/16 Level: Intermediate
Jesse Anderson (Big Data Institute)
Average rating: *....
(1.00, 1 rating)
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)
Average rating: ****.
(4.80, 5 ratings)
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. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1E 17
Zachary Glassman (The Data Incubator)
Zachary Glassman leads a hands-on dive into building intelligent business applications using machine learning, walking you through all the steps of developing a machine learning pipeline. You'll explore data cleaning, feature engineering, model building and evaluation, and deployment and extend these models into two applications using a real-world dataset. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1A 03
Secondary topics:  Deep Learning
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. Dylan Bargteil introduces TensorFlow's capabilities through its Python interface. Read more.
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9:00am–5:00pm Tuesday, 09/11/2018
Location: 1A 17
Ken Jones (Databricks, Inc.)
Ken Jones 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
Jerry Overton (DXC), Ashim Bose (DXC), Samir Sehovic (DXC)
Average rating: *****
(5.00, 1 rating)
Acquiring machine learning (ML) technology is relatively straightforward, but ML must be applied to be useful. In this one-day boot camp that is equal parts hackathon, presentation, and group participation, Jerry Overton, Ashim Bose, and Samir Sehovic teach you how to apply advanced analytics in ways that reshape the enterprise and improve outcomes. Read more.