Technical Programs

Comprehensive courses designed by practicing engineers for developers seeking to build production-grade distributed systems, blockchain applications, and machine learning solutions.

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Our Approach

ChainLogic courses emphasize practical implementation skills alongside theoretical understanding. Each program is structured around building progressively complex projects that mirror real-world development scenarios. Students work with the same tools, frameworks, and workflows used by professional engineering teams, ensuring that what they learn translates directly to production environments.

Our instructors are engineers currently working on production systems in their respective domains. This practitioner-led approach ensures curriculum reflects current industry practices rather than outdated methodologies or purely academic perspectives. Students gain insights from professional experience including common pitfalls, architectural patterns proven effective in production, and practical considerations that documentation often fails to address.

The curriculum design balances fundamental principles with contemporary tools and frameworks. We emphasize understanding why certain approaches are preferred in professional contexts, enabling students to make informed architectural decisions and adapt as technologies evolve. This foundation proves more valuable than memorizing specific APIs or following tutorials without deeper comprehension of underlying concepts.

Course Catalog

Three specialized programs covering critical domains in modern software development where practical, production-oriented education is notably scarce.

Blockchain development environment with smart contract code

Blockchain Development Fundamentals

Build decentralized applications and smart contracts on leading blockchain platforms. This comprehensive course covers blockchain architecture, consensus mechanisms, and cryptographic principles essential for distributed systems development.

Core Topics

  • Solidity programming for Ethereum smart contracts
  • Token standards implementation (ERC-20, ERC-721)
  • DApp development with Web3.js integration
  • DeFi protocols and decentralized storage with IPFS

Projects

Students develop cryptocurrency tokens, NFT marketplace applications, and decentralized voting systems. Projects emphasize security patterns, gas optimization, and production deployment considerations for blockchain applications.

¥63,000 View Details
Rust programming with systems architecture

Rust Systems Programming

Master systems programming with Rust for performance-critical and memory-safe applications. Learn ownership concepts, lifetime management, and concurrent programming without data races.

Core Topics

  • Ownership system and lifetime management
  • Async programming with Tokio runtime
  • FFI for C integration and WebAssembly compilation
  • Embedded systems and network service development

Projects

Build command-line tools, network services, and operating system components. Projects focus on performance optimization, concurrent programming patterns, and building high-performance web servers with proper error handling.

¥52,000 View Details
Machine learning model training and deployment

Machine Learning Engineering

Implement and deploy machine learning models in production environments at scale. Cover feature engineering, model training pipelines, and deployment strategies using MLOps practices.

Core Topics

  • TensorFlow and PyTorch framework implementation
  • Model optimization and A/B testing for ML systems
  • Model versioning, monitoring drift, and explainable AI
  • Cloud ML platforms and recommendation systems

Projects

Develop fraud detection systems, natural language processing pipelines, and real-time prediction services. Projects emphasize production deployment, model monitoring, and building computer vision applications at scale.

¥67,000 View Details

Course Comparison

Feature Blockchain Rust ML Engineering
Prerequisites JavaScript knowledge, basic web development Programming experience in any language Python proficiency, basic statistics
Duration 12 weeks 10 weeks 14 weeks
Focus Area Decentralized applications Systems-level programming Production ML deployment
Career Path Blockchain developer, DApp engineer Systems programmer, infrastructure engineer ML engineer, MLOps specialist
Investment ¥63,000 ¥52,000 ¥67,000

Selecting Your Course

Consider your background and career objectives when selecting a program. Blockchain Development suits developers interested in decentralized systems and cryptocurrency technology. Rust Systems Programming appeals to those seeking performance-critical application development or infrastructure work. Machine Learning Engineering targets developers wanting to deploy models in production environments.

All programs share emphasis on production-grade implementations and professional development practices. The technical depth and project-based approach remain consistent across courses, with content tailored to each domain's specific requirements and industry standards.

Technical Standards

Code Quality Requirements

All programs maintain consistent expectations for code quality, documentation, and engineering practices. Students learn to write maintainable code with appropriate testing coverage, clear documentation, and adherence to language-specific conventions. Code review processes mirror professional development environments, providing feedback on implementation choices and architectural decisions.

Version Control Practices

Students use Git workflows common in professional teams including feature branching, pull requests, and merge conflict resolution. Projects are managed through version control from the beginning, developing habits that transfer directly to collaborative development environments. Commit messages, branching strategies, and repository organization follow industry standards.

Testing Methodologies

Testing receives explicit attention across all courses. Students implement unit tests, integration tests, and appropriate testing strategies for their domain. Blockchain students test smart contracts for security vulnerabilities. Rust students write tests for concurrent code. ML students validate model performance and implement data quality checks. Testing is integrated throughout development rather than treated as optional.

Professional Tools

Students work with professional development tools including IDEs, debuggers, profilers, and monitoring systems relevant to their domain. Blockchain students use development frameworks like Hardhat and Truffle. Rust students utilize cargo and system profiling tools. ML students work with experiment tracking and model registry systems. Tool selection reflects current industry practice.

Frequently Asked Questions

What are the prerequisites for enrolling in a course?
Prerequisites vary by program. Blockchain Development requires JavaScript knowledge and basic web development experience. Rust Systems Programming needs programming experience in any language, though C or C++ background helps. Machine Learning Engineering requires Python proficiency and basic statistics understanding. All programs assume comfort with command line interfaces and development environments.
How are courses structured and delivered?
Courses combine self-paced learning with structured milestones. Students access recorded lectures, written materials, and project specifications on their schedule. Weekly check-ins with instructors provide guidance and feedback. Projects have defined deadlines to ensure consistent progress. This structure accommodates working professionals while maintaining accountability.
What time commitment do courses require?
Students typically invest 15-20 hours per week across lectures, projects, and practice. Time requirements vary based on prior experience and learning pace. Projects demand significant time for implementation and debugging. The flexible structure allows adjusting weekly time investment while meeting milestone deadlines. Most students complete programs within the estimated duration.
Can I take multiple courses simultaneously?
While technically possible, we generally recommend focusing on one program at a time given the time commitment required. Students who attempt multiple simultaneous courses often struggle to dedicate sufficient attention to projects in each domain. Sequential enrollment allows deeper engagement with each topic and better portfolio development.
What support is available during the course?
Students have access to instructors through scheduled office hours, code review sessions, and asynchronous communication channels. Technical questions receive responses typically within 24 hours during weekdays. Project feedback includes specific guidance on implementation improvements. Students also connect with peers through course discussion forums for collaborative problem-solving.
Do you provide career services or job placement?
We do not offer formal job placement services or guarantee employment outcomes. Our focus is technical education and skill development. However, our portfolio-building approach helps students demonstrate capabilities to potential employers. We can provide general guidance on presenting technical work and discussing projects in interviews, but career advancement depends on individual effort and market conditions.
What happens if I need to pause my enrollment?
Students who encounter circumstances requiring a pause can discuss options with program administration. Depending on how far into the program, options may include temporary suspension with later resumption or withdrawal with partial refund. Each situation is evaluated individually. We aim to accommodate legitimate needs while maintaining program standards.
Will I receive any certification upon completion?
Students who successfully complete all projects and requirements receive a certificate of completion from ChainLogic. This certificate confirms participation and project completion but is not a professional certification or license. The primary value comes from portfolio projects and demonstrated technical capabilities rather than credentials. Employers typically evaluate technical skills through project work and interviews.
What technologies and tools will I need?
Students need a computer capable of running development environments for their chosen course. Blockchain students need Node.js and Ethereum development tools. Rust students need the Rust toolchain and appropriate IDE. ML students need Python environment with TensorFlow or PyTorch. Specific setup instructions are provided upon enrollment. Cloud computing credits are provided for courses requiring significant computational resources.
How current is the course content?
Course content is reviewed and updated regularly by instructors who work with current production systems. When significant framework versions release or industry practices evolve, curriculum is modified to reflect these changes. Students learn current best practices rather than outdated approaches. The emphasis on fundamental principles ensures concepts remain applicable even as specific tools evolve.

Begin Your Learning Journey

Connect with our program advisors to discuss which course aligns with your professional development objectives. We can provide detailed information about prerequisites, project requirements, and program structure.

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