Google IO17 Extended - Hudson Valley (AndroidThings - Plus MLCAMP2017 Kickoff!)

AGENDA:

09:30am: Doors Open

10:00am: Google I/O Recap

We'll recap the news and announcements from Google I/O -- get a sense of what the key technologies and outcomes were.

10:30am: IoT, Android Things & SUNY (Dr. Izadi & Nitya)

The Internet of Things is dominating technology conferences and startups this year. But what is IoT and why should you care? In this talk we will look at this from two perspectives:

• Platforms. What technologies and tools exist for IoT? In particular, we will focus on Android Things, Cloud Core IoT and Firebase as key enablers that we hope to explore further.

• Projects. How can we innovate in IoT? In particular, we will talk about an ongoing collaboration with SUNY where we have worked with Senior Design Project teams to develop ideas and functional prototypes targeting the intersection of IoT and the Share Economy.

== A primary goal for this talk is to motivate community engagement around these efforts, which will be a key focus for GDG HV in 2017-2018.==

11:00am: Let's Talk About the Google Assistant (Allen Firstenberg, GDE For Wearables/Assistant)

One of the hottest topics at I/O this year was the Google Assistant, new places people can use the Assistant, new ways developers can create their own Actions for the Assistant, and new approaches to thinking about how to craft conversations for an Assistant.

The Assistant UX is different than most we've worked with in the past, and requires a new way to think about it and build it. We'll go over some of the major announcements related to the Assistant and start to learn how to create a persona for our application and the tools available to implement it.

== A primary goal for this talk is to motivate community interest and submissions for the ongoing Actions on Google Developer Challenge (https://developers.google.com/actions/challenge/) which concludes in August 2017==

11:30pm: "Crafting a Character" Codelab (Self-Guided Exercise)

Let's spend 30 minutes on an exercise to brainstorm ideas for the Google Developer Challenge & work on understanding how we can "craft a character" for our Assistant using this IO17 Codelab (https://codelabs.developers.google.com/codelabs/conversation-design/index.html?index=..%2F..%2Fio2017#0).

At the end of this segment, we'll go around the room and share our insights into the process, and also ideas for feedback. Hopefully a subset of you will then be empowered to take this to the next level and implement the app :-)

12:00pm Lunch & Networking

13:00pm MACHINE LEARNING CAMP 2017: Kickoff

Those of you interested in the Machine Learning Camp should stick around for the afternoon session where we will discuss the schedule, onboard you into Slack, and get started on first steps.

13:30pm (Group 1) Intro To Python / (Group 2) Intro To Data Analysis

Based on your group, pick the starting course and project for your track, put on your headphones and start working on the exercises and content at your own pace. Ask questions anytime and call a TA if you need help. Our goal is to have every attendee finish at least 1 lesson before the end of this event. Feel free to move ahead if you are familiar with the content (we will share the bigger schedule ahead of time) or work at a slower pace if you are relatively new to coding.

15:00 Survey & Wrap-up

We'll call a halt, do a survey and raffle and plan out the next steps for our ML Camp journey.

About ML Camp:

All camp participants will be invited to Slack and will agree to work on weekly goals and "check-in" with a TA every week to report current status so we can use the information to support individual goals more productively. After that point, any additional in-person meetings will be announced within the Slack group and can occur in smaller groups at different locations.

We will have a final in-venue ML Camp Showcase event in early September where all active participants will meet to share their experiences and insights from this camp, and potentially plan for a follow-up camp (for those that want to continue onwards towards an ML Nanodegree)