Training > Blockchain > 開発者が学ぶHyperledger Fabric (LFD272-JP)
Training Course

開発者が学ぶHyperledger Fabric (LFD272-JP)

Hyperledger Fabric for Developers helps you build expertise and obtain practical skills in implementing business logic by writing chaincode – Fabric’s smart contracts – and creating enterprise blockchain-based applications. 

Please note the course content is in Japanese.

Who Is It For

This course is designed for developers who want to master their skills in the Hyperledger Fabric chaincode and application development.
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What You’ll Learn

In this course, you’ll learn how to implement and test a chaincode in Node.js for any use case, manage the chaincode life cycle, create Node.js client applications interacting with Hyperledger Fabric networks, control access to the information based on a user identity, set up and use private data collections and much more.
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What It Prepares You For

This course will help you build expertise and obtain practical skills in implementing business logic by writing the Chaincode and creating enterprise blockchain-based applications.
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To best benefit from this course you should have:

  • Understanding of Hyperledger Fabric architecture and components: Ledger, Channel, Chaincode, types of network nodes (Endorser, Committer, Orderer, etc.), transaction flow, Certificate Authority (CA)
  • Experience with NodeJS:
    – Ability to install NodeJS, run applications from the cli; knowledge of basic language constructions; familiarity with package management
  • Knowledge of Docker basics:
    – Ability to install docker daemon, run docker containers locally, understand and use basic commands
  • Experience with the command line/shell of a Linux operating system
  • Familiarity with NoSQL databases and general understanding of CouchDB
  • We highly recommend that you first take the Blockchain for Business: An Introduction to Hyperledger Technologies (LFS171x) MOOC which is free to audit on edX.
Lab Info
Lab exercises in this course are designed to work either on native hardware, or using a virtual machine (VM), under a hypervisor, such as those in the KVM, VMWare, or Virtual Box families. Detailed instructions to set up your lab environment are provided in the course.