Conference: April 10-11, 2018

Workshops: April 9, 2018

San Francisco, CA

Applied AI for Developers

Software Development Conference is a conference for senior software engineers and architects on the patterns, practices, and use cases for applying Artificial Intelligence / Machine Learning in engineering.

April 9 - 11, 2018
Parc 55 - A Hilton Hotel, San Francisco, CA

Register before Jan 6th & save up to $200

Benefits of attending

  • Applied Software Engineering Practices with Machine Learning / Artificial Intelligence
  • Conference with over 30 sessions across 2 days
  • 1 day of optional workshops
  • Practitioners over evangelists
  • Never hidden marketing

AI and Machine Learning Software Development Conference

2018 Tracks

  • Deep Learning Applications & Practices

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe across machine translation, computer vision.

  • Predictive Data Pipelines & Architectures

    Best practices for building real-world data pipelines doing interesting things like predictions, recommender systems, fraud prevention, ranking systems, and more.

  • ML in Action: Security & Risk

    Applied Machine Learning track demonstrating how to train, score, and handle security and fraud use cases.

  • Real-world Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.

  • Handling Sequential Data Like an Expert / ML Applied to Operations

    Discussing the complexities of time, including hyper loglog, count min sketch, and more / Machine Learning in the data center. Exploring topics like Dynamic rebalancing in Dataflow, Predictive auto-scaling, and fault prediction.

  • AI Meets the Physical World

    AI use cases from drones to self-driving cars. The track where AI touches the physical world.


Why Senior Developers, Architects, and Software Engineers are looking for AI and Machine Learning Topics geared towards them? Applied AI for software engineers rather than data scientists
Charles Humble
Editor in Chief,

AI and machine learning are key emerging trends that have broad applicability in a whole range of industries. will be a practical, real-world event for software engineers, architects and technical managers who want to learn about the successes and use-cases for AI.

Wesley Reisz

Software Engineer and Principal Tech Advisor

We have the data… What I need is to better understand the insights in that data. What are the trends, where is the direction heading, what early indicators are there. I know there are libraries and tools out there that can help me.

Haley Tucker

Software Engineer, Netflix

What I’d like to look more into and spend more time on is the machine learning space. I keep running into problems in my current job that just feels like there is a machine learning solution to it. I think there is alot of value in spending time in that space.

Software is changing the world.
AI is changing software

Software development is always evolving. And Software engineers continue to evolve with it.

Before DataEng became a thing, we had DBA’s and ETL folks. Software Engineers became more involved with the work and created the DataEng field. Before DevOps, we had Operations/Systems Administrators. Software Engineers became more involved with the work and created DevOps. We are seeing the same thing happen in SecOps… security folks who have operational SE skillsets.

Now, AI and machine learning are changing and shaping the future of software. Traditionally, this has been the field for PhD level data scientists. But as tooling and libraries are becoming more available and understood, that’s changing. Software engineers are moving into this field creating new roles, such as Machine Learning Engineers.

Our hypothesis is that there are large numbers of software engineers who have the talent to harness data in how they work, but don’t know the right problems to solve with AI and machine learning in engineering. When should you use a machine learning algorithm? When is a rules engine the right approach? At, we’ll help senior software engineers and architects uncover the real-world patterns, practices, and use cases for applying artificial intelligence/machine learning in engineering.

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Past QCon Speakers

Sr. Director @Salesforce Einstein
Shubha Nabar
Security Director & Previous Chief Architect @Coinbase
Rob Witoff
Director of Research @FastForwardLabs
Mike Lee Williams
Leading voice on Bias in Data & Author of Weapons of Math Destruction
Cathy O'Neal
CEO and Co-Founder @MastodonC
Fran Bennett
Software Engineer @GoogleBrain
Anjuli Kannan
Co-Creator Apache Kafka/Co-Founder and CTO @Confluent
Neha Narkhede
More speakers to be announced

Attendees talk about the Speakers

  • of QCon attendees feel they are learning from an expert peer

  • of QCon attendees rate the level of content as expert San Francisco Venue & Hotel

Parc 55 San Francisco

Parc 55 San Francisco - A Hilton Hotel

This contemporary, high-rise hotel is 1 block from Union Square with stunning views all around and close to popular attractions, events, and shopping. The conference venue is at the same location as the hotel.



Parc 55 San Francisco – a Hilton Hotel
55 Cyril Magnin Street
San Francisco, California
94102 USA
Tel: +1-415-392-8000


QCon special rate starting at $269/night*.
*first-come-first serve basis and possibility of early sell-out

Online Reservations