Course
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Overview
The intersection of artificial intelligence and blockchain is redefining secure banking and financial transactions. While blockchain ensures transparency and immutability, AI can detect anomalies, predict risks, and enhance system reliability. This course explores how AI integrates with blockchain technology to create secure, efficient, and intelligent transaction systems. AI is a powerful enabler, but it cannot replace human judgment entirely. Participants will learn how to apply these technologies effectively while understanding their limitations and practical challenges.
Features
- Learn how AI enhances blockchain-based transaction security.
- Explore smart contracts and automated verification processes.
- Gain practical skills in designing secure and efficient blockchain systems.
- Study real-world case studies where AI and blockchain improved banking operations.
- Understand compliance, privacy, and ethical considerations in AI-blockchain integration.
- Practice interpreting AI-generated insights to make informed decisions.
- Develop strategies for proactive risk detection and fraud prevention.
- Stay current on emerging trends in fintech innovation.
Target audiences
- This course is designed for professionals who want to leverage AI and blockchain for secure banking operations, including:
- IT Security Specialists
- Blockchain Developers
- Compliance Officers
- Innovation Managers
- Senior Banking Executives
- Digital Transformation Leaders
- Even those with prior experience in fintech or blockchain will find new insights and practical approaches to enhance transaction security.
Requirements
- Basic understanding of banking operations and digital transactions.
- Willingness to engage with hands-on exercises and case studies.
- No prior AI or blockchain coding experience required.
- A computer with internet access for exercises and simulations.
Curriculum
- 7 Sections
- 77 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Section 1: Introduction to AI and Blockchain in Banking13
- 1.1Overview of AI and blockchain technologies in finance
- 1.2Evolution of digital banking systems
- 1.3Understanding blockchain fundamentals
- 1.4Introduction to smart contracts and their role in banking
- 1.5Basics of AI applications in transaction monitoring
- 1.6Comparing traditional vs. blockchain-based systems
- 1.7Benefits of AI-blockchain integration for banks
- 1.8Limitations and challenges of adoption
- 1.9Case studies of AI and blockchain in global banks
- 1.10Key banking processes impacted by AI-blockchain
- 1.11Building a foundation for further learning
- 1.12Section review and Q&A
- 1.13Quiz 10 Questions
- Section 2: Blockchain Architecture and AI-Driven Security12
- 2.1Core components of blockchain architecture
- 2.2Public, private, and hybrid blockchains
- 2.3How blockchain ensures transaction integrity
- 2.4Consensus mechanisms: Proof of Work, Proof of Stake, others
- 2.5Understanding smart contract execution flow
- 2.6Security implications in blockchain design
- 2.7AI-driven anomaly detection in transactions
- 2.8Pattern recognition for fraud prevention
- 2.9Real-time detection vs. historical analysis
- 2.10Case study: AI catching suspicious crypto transactions
- 2.11Section review and exercises
- 2.12Quiz 20 Questions
- Section 3: Designing Secure AI-Blockchain Solutions13
- 3.1Planning AI-blockchain system architecture
- 3.2Choosing the right blockchain platform
- 3.3Selecting AI tools for financial applications
- 3.4Integration challenges between AI models and blockchain
- 3.5API and data pipeline design for secure communication
- 3.6Smart contract development best practices
- 3.7Machine learning model deployment on blockchain systems
- 3.8Risk mitigation in AI-blockchain integration
- 3.9Testing and validation of secure systems
- 3.10Case study: cross-border payment security
- 3.11Simulated project setup for learners
- 3.12Section review and discussion
- 3.13Quiz 30 Questions
- Section 4: Predictive Analytics and Real-Time Monitoring12
- 4.1Introduction to predictive analytics in blockchain banking
- 4.2Forecasting transaction patterns with AI
- 4.3Real-time monitoring system architecture
- 4.4AI methods for detecting irregularities instantly
- 4.5Data sources for blockchain-based fraud prediction
- 4.6Implementing dashboards for live tracking
- 4.7Analysing high-volume transactions with AI
- 4.8Stress-testing AI monitoring systems
- 4.9Hands-on: building a simple predictive model
- 4.10Case study: preventing fraud in crypto exchanges
- 4.11Section review and reflection
- 4.12Quiz 40 Questions
- Section 5: Ethics, Compliance, and Cybersecurity11
- 5.1Ethical considerations in AI-blockchain banking
- 5.2Regulatory frameworks for digital finance
- 5.3GDPR, CCPA, and other privacy laws
- 5.4Cybersecurity threats in blockchain systems
- 5.5Best practices for data privacy protection
- 5.6Creating audit-ready systems
- 5.7Security standards for AI-blockchain banking
- 5.8Incident response planning
- 5.9Case studies of compliance success and failure
- 5.10Section review and knowledge check
- 5.11Quiz 50 Questions
- Section 6: Optimization, Scalability, and Human Oversight12
- 6.1Improving AI-blockchain performance
- 6.2Scaling transaction systems for high demand
- 6.3Reducing computational overhead
- 6.4Load balancing in blockchain networks
- 6.5AI model optimization for speed and accuracy
- 6.6Combining automation with human decision-making
- 6.7Fail-safe mechanisms in AI-blockchain workflows
- 6.8Troubleshooting common operational challenges
- 6.9Maintenance and upgrade planning
- 6.10Case study: scaling a bank’s blockchain platform
- 6.11Section review and applied exercises
- 6.12Quiz 60 Questions
- Section 7: Capstone Project and Strategic Application11
- 7.1Planning the final secure transaction system project
- 7.2Selecting appropriate AI and blockchain tools
- 7.3Designing the system architecture
- 7.4Building and coding the smart contracts
- 7.5Integrating AI monitoring components
- 7.6Testing for performance and reliability
- 7.7Documenting the entire project
- 7.8Preparing a compliance and security report
- 7.9Presenting the system to stakeholders
- 7.10Reflection and lessons learned for real-world application
- 7.11Quiz 70 Questions
FAQs
No. The course is designed to guide you through AI and blockchain step by step, even if you are new to these technologies.
Yes. Successfully completing all modules, exercises, and projects will earn you a Certificate of Completion, which can enhance your professional profile.
You will have lifetime access to lessons, case studies, and any future updates.
Absolutely. Each module includes practical case studies from banks and fintech companies to show AI and blockchain applications in action.
Yes. Our support team is available via email, and discussion forums provide peer-to-peer learning opportunities.
IT security specialists, blockchain developers, compliance officers, innovation managers, senior banking executives, and digital transformation leaders. Even those with prior experience in fintech will gain valuable insights.
Yes. Group enrolment options are available with discounts and customized corporate training packages.
Instructor
Path
I'm Path, I'm a developer with a passion for teaching. I'm the lead instructor at the London App Brewery, London's leading Programming Bootcamp. I've helped hundreds of thousands of students learn to code and change their lives by becoming a developer. I've been invited by companies such as Twitter, Facebook and Google to teach their employees.
My first foray into programming was when I was just 12 years old, wanting to build my own Space Invader game. Since then, I've made hundred of websites, apps and games. But most importantly, I realised that my greatest passion is teaching.
