Shravani Kasralikar: LinkedIn; Github

Dhamodharan Kaliyaperumal: LinkedIn

Barbara Hong: LinkedIn

Piliasov Prokhor: LinkedIn

Bowen Chen: LinkedIn; Github

Sathvik Vivek: LinkedIn

Shangze He: LinkedIn

Christopher Ian Steele: LinkedIn

Alicia Wei: LinkedIn

Yuelin Wang: LinkedIn

Victor Qiu: LinkedIn

Xiaodong Ping: LinkedIn

This course will provide a comprehensive and solid understanding of Blockchain and Crypto economics. Topics including smart contracts, cryptocurrencies, and blockchain governance will be elaborated via case studies using Bitcoin, Etherum, and DFINITY as examples. We will also look at how blockchain is empowering decentralized finance applications.

This course equips participants to thrive within the global paradigm shift for data-driven results and research and across many industries globally. It will empower them through both artificial intelligence and business strategy initiatives. We will practice a data-driven methodology and academia/industry collaborative approach to answer research questions at the frontier of Fintech. We will learn from a joint perspective of Academia Researcher, Economist, Data Scientist and Data Engineer.

• Understand the basics of blockchain and crypto economics: the emergence; the problem solved; and the value created.
• Explain in non-technical terms the related concepts including smart contracts, cryptocurrencies, decentralized finance etc.
• Demonstrate and discuss case studies in Blockchain and Crypto Economics and Blockchain governance
• Prosper collaboratively in a team with roles of Economist, Data Scientist, and Data Engineer; provide constructive criticism to peers’ work and contribute to team projects.
• Conduct data-driven research and outlook technology transfer independently through 1) targeting an important and interesting research question of high intellectual merits and broad impacts 2) finding and vetting sources to acquire information 3) deploying strong analytical skills in a team of economist, data scientist, and data engineer 4) communicating research results 5) identifying limitations of current research and future research topics

• The course is open to a diverse background of audience who is interested in the Frontier of Fintech and AI, include but not limited to: --Researcher in academia interested in Fintech and/or the application of their research in Data Science workflow --Economist, Data Scientist, Data Engineer in industry interested in Research questions at the Frontier of Fintech and AI; possesses ambition to develop a systematic way of conducting research and technology transfer independently.

• Students will be invited to join our course Slack channel for interaction in the course and beyond.
• Students will have a well-documented collaborative team project profile for personal publicities and further endeavors
• Upon completing the course successfully, students will be invited to join our course LinkedIn Alumni Group for connections, future opportunities, and much more.

• Understand the basics of blockchain and crypto economics
• Hands-on application in a team setting in the roles of an economist, data scientist, and data engineer
• Synthesize your knowledge and skills by completing a capstone project for your portfolio

• TIme: 1pm – 3 PM PDT on 7/23, 7/30, 8/6, 8/13, 8/20, 8/27
• Prerequisites: Basics in statistics
• Format: Online through Zoom
• Number of Sessions: 6
• Required Tools: Slack, Github, LinkedIn, Google Colab, Lucidchart, iSlides
• Program/Workload: Live training: 2 hrs/week (Including hands-on student activities)

RMDS Lab is an ecosystem service provider that empowers data science professionals and businesses worldwide to achieve successful, data-driven results. Our community members have access to tools and resources that enhance their research and increase the success-rate of their work. Our proprietary web platform uses AI-powered recommendations to connect members to online learning, datasets and workflows, and peers within a collaborative environment. Our community extends offline with hands-on training, conferences, and community events.

RMDS Lab was founded in 2009 by IBM Chief Data Scientist Alex Liu and is headquartered in Pasadena, CA with partners worldwide. It serves more than 35,000 members and affiliates globally. In December 2019, RMDS successfully held IM Data annual conference in the Pasadena Convention Center with 2000+ attendees from all over the world. For more information, visit www.grmds.org.