20–23 April 2020

In-depth Training Courses

These expert-led presentations on Monday 20 April and Tuesday 21 April give you a chance to dive deep into the subject matter. These courses often sell out, so reserve your spot today.

2-Day Training (Mon & Tue) 1-Day Training (Tue)

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10:00 - 17:30 Monday, 20 April & 9:00 - 17:00 Tuesday, 21 April
Location: Capital Suite 13
Nikki Rouda (Amazon Web Services)
Nikki Rouda walks you through the steps of building a data lake on Amazon S3 using different ingestion mechanisms, performing incremental data processing on the data lake to support transactions on S3, and securing the data lake with fine-grained access control policies. Read more.
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10:00 - 17:30 Monday, 20 April & 9:00 - 17:00 Tuesday, 21 April
Location: Capital Lounge 1/2
Grishma Jena (IBM)
Data science is rapidly changing every industry. This has resulted in a shift away from traditional software development and toward data-driven decision making. Grishma Jena uses Python to extract, wrangle, explore, and understand data so you can leverage it in the real world. Read more.
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10:00 - 17:30 Monday, 20 April & 9:00 - 17:00 Tuesday, 21 April
Location: Capital Suite 15
Thomas Nield (Nield Consulting Group)
There's been an explosion of tools for machine learning, but two have emerged as practical go-to solutions: scikit-learn and Apache Spark. Using Python, Thomas Nield leads a deep dive into examples in parallel (no pun intended) for both of these tools and learn how to tackle machine learning at small, medium, and large scales. Read more.
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10:00 - 17:30 Monday, 20 April & 9:00 - 17:00 Tuesday, 21 April
Location: Capital Suite 16
Hugo Bowne-Anderson (DataCamp)
Hugo Bowne-Anderson walks you through the basics of the math and stats you need to know to do data science and interpret your results correctly (the calculus, linear algebra, statistical intuition, and probabilistic thinking, among others) through hands-on examples from machine learning, online experiments and hypothesis testing, natural language processing, data ethics, and more. Read more.
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9:0017:00 Tuesday, April 21, 2020
Location: Capital Suite 11
Oliver Hughes (Pivotal), Alberto C. Ríos (Pivotal)
Today's data engineer needs a deep understanding of the key tools and concepts within the vast, rapidly evolving Kubernetes ecosystem. This training will provide developers with a thorough grounding on Kubernetes concepts, suggest best practices and get hands-on with some of the essential tooling. Topics will include Read more.
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9:0017:00 Tuesday, April 21, 2020
Location: Capital Suite 12
Pramod Singh (Walmart Labs ), Rajesh Shreedhar Bhat (Walmart Labs)
With the latest developments and improvements in the field of deep learning and artificial intelligence, many demanding natural language processing tasks become easy to implement and execute. Text summarization is one of the tasks that can be done using attention networks. Read more.
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9:0017:00 Tuesday, April 21, 2020
Location: Capital Suite 10
Alex Thomas (John Snow Labs), Maziyar Panahi (John Snow Labs)
This is a hands-on training covering applying the latest advances in deep learning for common NLP tasks such as named entity recognition, document classification, sentiment analysis, spell checking and OCR. Learn to build complete text analysis pipelines using the highly performant, high scalable, open-source Spark NLP library in Python. Read more.
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9:0017:00 Tuesday, April 21, 2020
Location: Capital Suite 2
Dean Wampler (Anyscale)
Surprisingly, there is no simple way to scale up Python applications from your laptop to the cloud. Ray is an open source framework for parallel and distributed computing that makes it easy to program and analyze data at any scale by providing general-purpose high-performance primitives. This training will show how to use Ray to scale up Python applications, data processing, and machine learning Read more.
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9:0017:00 Tuesday, April 21, 2020
Location: Capital Suite 14
Janisha Anand (Amazon Web Services), Nikki Rouda (Amazon Web Services)
Learn how to build a serverless data lake on AWS. In the workshop you'll ingest Instacart's online grocery shopping public dataset to the data lake and draw valuable insights on consumer shopping trends. You’ll build data pipelines, leverage data lake storage infrastructure, configure security and governance policies, create a persistent catalog of data, perform ETL, and run ad-hoc analysis. Read more.
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9:0017:00 Tuesday, April 21, 2020
Location: S11 D
Nathalie Rauschmayr (Amazon Web Services), Satadal Bhattacharjee (Amazon Web Services), Aparna Elangovan (Amazon Web Services)
Build, train, and deploy a deep learning model on Amazon SageMaker with Nathalie Rauschmayr, Satadal Bhattacharjee, and Aparna Elangovan, and learn how to use some of the latest SageMaker features such as SageMaker Debugger and SageMaker Model Monitor. Read more.

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