<aside> 🔑 The goal is to expose students or club members working on ML/Deep Learning on challenging domain-specific problems (computational biology, quantum VQAEs, deepfakes and CGI, etc.) with a popular, novel ML development

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WHO: Speaker (1) → An employee/engineer/professor/grad working on this unique intersection who will give a talk on their subject (which we can curate based on interest/polls) and provide an interactive demo for students to work through

  *Assistant Student (1-2)* → The goal of the student would be to bring over their own insights and questions with their experience in ML

  *Audience (15-20)* → anyone with a strong foundation for either the ML side or domain side as the goal is to give both sides exposure to the other and ultimately provide a new way to think about the work that they do on a daily basis, should have a basic understanding of programming and prior background knowledge

• Fundamentally, the student's goal is to connect with an audience that has a computer background, while the expert's goal is to connect with the general and interested audience

WHAT: The speaker would prepare an interactive talk to get the audience familiar and directly explore (almost like a classroom and less of a lecture) → a good outline for what the expert should talk about and the types of activities could be:

Intro: 20 Mins

1. 5 Mins: Who they are and what they've done → clearly define their background and connect with the audience
2. 5 Mins: The motivation behind they're work → why this field is important to work on and provide some intuition for where ML can be applied
3. 6 Mins: Pose some challenging questions that field is trying to answer and ask audience to brainstorm why they think they haven't been solved → goal is to use breakout rooms
4. 5 Mins: Clearly define the goal and outcome of the workshop → most likely is to build a method for tackling domain-problems from a ML approach (mental and practical)

Exploration: 30 Mins

1. 10 Mins: A brief intro on the field, some fundamental concepts → this is to build understanding obviously but always ask questions to audience to get them to think critically
2. 15 Mins: Get the workshop to do their own research to stay prepared → almost like collaborating to solve the problem defined in the intro + research helps bring on better understanding/datapoints
3. 5 Mins: Answer any knowledged-based assumptions/ideas that are needing to be explored before moving on → necessary to get the most value out of the exercises

Collaborate: ~ 70 Mins

1. 20 Mins Activity 1/Notebook 1 → Pose the question, give the template code, and develop small groups for them to solve the questions posed → students and speakers can go from room to room providing help
2. 5 Mins Coming Together where speaker provides answer, intuition as to why, and provides new key ideas
3. 20 Mins Activity 2/Notebook 2 → Pose the question, give the template code, and develop small groups for them to solve the questions posed based on new knowledge gained