Sep 23–26, 2019
 
1A 15/16
Add Hands-on data science with Python to your personal schedule
9:00am Hands-on data science with Python Michael Cullan (The Data Incubator)
1A 01/02
Add Big data for managers to your personal schedule
9:00am Big data for managers Michael Li (The Data Incubator), Ana Hocevar (The Data Incubator)
1A 03
Add Recommendation System using Deep Learning to your personal schedule
9:00am Recommendation System using Deep Learning Bargava Subramanian (Binaize Labs), Amit Kapoor (narrativeVIZ Consulting)
1E 06
Add Professional Kafka development to your personal schedule
9:00am Professional Kafka development Jesse Anderson (Big Data Institute)
1A 17
Add Building a serverless big data application on AWS to your personal schedule
9:00am Building a serverless big data application on AWS Jorge Lopez (Amazon Web Services)
1A 18
1E 07
Add Machine learning from scratch in TensorFlow to your personal schedule
9:00am Machine learning from scratch in TensorFlow Dylan Bargteil (The Data Incubator)
12:30pm Lunch | Room: Lunch
10:30am Morning break | Room: Break
3:00pm Afternoon break | Room: Break
9:00am-5:00pm (8h) Data Science, Machine Learning, & AI Deep dive into specific tools, platforms, or frameworks
Hands-on data science with Python
Michael Cullan (The Data Incubator)
Michael Cullan walks you through developing a machine learning pipeline, from prototyping to production. You'll learn about data cleaning, feature engineering, model building and evaluation, and deployment and then extend these models into two applications from real-world datasets. All work will be done in Python.
9:00am-5:00pm (8h) Strata Business Summit
Big data for managers
Michael Li (The Data Incubator), Ana Hocevar (The Data Incubator)
Michael Li and Ana Hocevar 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, Media and Advertising, Retail and e-commerce
Recommendation System using Deep Learning
Bargava Subramanian (Binaize Labs), Amit Kapoor (narrativeVIZ Consulting)
In this two-days workshop, you will learn the different paradigms of recommendation systems and get introduced to the usage of deep-learning based approaches . By the end of the workshop, you will have enough practical hands-on knowledge to build, select, deploy and maintain a recommendation system for your problem.
9:00am-5:00pm (8h) Data Engineering and Architecture Data Integration and Data Processing, Deep dive into specific tools, platforms, or frameworks
Professional Kafka development
Jesse Anderson (Big Data Institute)
Jesse Anderson offers an in-depth look at Apache Kafka. You'll learn how Kafka works and how to create real-time systems with it as well as how to create consumers and publishers. Jesse then walks you through Kafka’s ecosystem, demonstrating how to use tools like Kafka Streams, Kafka Connect, and KSQL.
9:00am-5:00pm (8h) Data Engineering and Architecture Cloud Platforms and SaaS, Data Integration and Data Processing, Data, Analytics, and AI Architecture, Deep dive into specific tools, platforms, or frameworks
Building a serverless big data application on AWS
Jorge Lopez (Amazon Web Services)
Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. Join in to learn how to incorporate serverless concepts into your big data architectures. You'll explore design patterns to ingest, store, and analyze your data as you 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
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 Science, Machine Learning, & AI Deep dive into specific tools, platforms, or frameworks, Deep Learning
Machine learning from scratch in TensorFlow
Dylan Bargteil (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. Dylan Bargteil offers an overview of TensorFlow's capabilities in Python, demonstrating how to build machine learning algorithms piece by piece and how to use TensorFlow's Keras API with several hands-on applications.
12:30pm-1:30pm (1h)
Break: Lunch
10:30am-11:00am (30m)
Break: Morning break
3:00pm-3:30pm (30m)
Break: Afternoon break

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