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Fundamentals of Blockchain Technology
MGMT X 457.1
This course offers an introduction to blockchain and distributed ledger technology (DLT) grounded in real-world use cases and practical application. The goal of the course is to understand blockchain technology fundamentals that can be applied across any domain, industry and use case in both the public and private sector.
Understand the fundamentals, unique characteristics, and mechanics of distributed ledger (DLT) and blockchain technology, and how it differs from traditional technologies
Appreciate and articulate the paradigm shift that blockchain technology presents and requires
Complement expertise of traditional technologies with an understanding of decentralized and distributed technologies
Demonstrate practical knowledge of how blockchain can improve a response to critical problems and challenges in both public and private sectors
Understand how blockchain technology is different from the sometimes-better-known bitcoin
Participate in meaningful discussions around the merits and risks of blockchain technology
About this course:
The course aims to provide a solid and holistic foundation of the technology which is useful irrespective of the function and role of the student (project management, legal, compliance, operations, business development, IT/technology, digital transformation, finance, strategy and others). It covers the fundamentals, including understanding the difference between decentralization, distributed ledger (DLT), blockchain technology and bitcoin. It also covers blockchain’s unique characteristics which makes it a powerful solution to solve some critical challenges. The course also covers the blockchain structure (public versus private and permission models), smart contracts and the blockchain stack (layers). While it is focused on blockchain technology, the course aims to position the technology in the larger context of digital transformation; traditional technologies; and as a complement to other emerging technologies, e.g., Internet of Things or machine learning. Students get exposure to real organizations, use cases and continuously apply theory to real business problems.
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