┌─────────────────────────────────────────────────────────────────────────────┐
│                    GOVERNANCE MODELS                                        │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ON-CHAIN GOVERNANCE                                                        │
│  ┌─────────────────────────────────────────────────────────────────────┐    │
│  │ • Decisions executed directly by code                               │    │
│  │ • Voting via smart contracts                                        │    │
│  │ • Proposals automatically enacted                                   │    │
│  │ • Examples: MakerDAO, Compound, Aave                               │    │
│  │ • Pros: Transparent, automatic, trustless                          │    │
│  │ • Cons: Rigid, voter apathy, whale dominance                       │    │
│  └─────────────────────────────────────────────────────────────────────┘    │
│                                                                             │
│  OFF-CHAIN GOVERNANCE                                                       │
│  ┌─────────────────────────────────────────────────────────────────────┐    │
│  │ • Decisions through social discussion                               │    │
│  │ • Voting via signalling proposals (Snapshot, etc.)                  │    │
│  │ • Core developers implement changes                                 │    │
│  │ • Examples: Bitcoin, Ethereum (before merge)                       │    │
│  │ • Pros: Flexible, community-driven                                 │    │
│  │ • Cons: Slow, less transparent, capture risk                       │    │
│  └─────────────────────────────────────────────────────────────────────┘    │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────────────────┐
│                    DAO OPERATING FRAMEWORK                                  │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  1. PROPOSAL SUBMISSION                                                     │
│     ┌──────────────────────────────────────────────────────────────────┐    │
│     │ Any token holder submits proposal (on-chain or Snapshot)       │    │
│     └──────────────────────────────────────────────────────────────────┘    │
│                                    │                                        │
│                                    v                                        │
│  2. DISCUSSION PERIOD                                                        │
│     ┌──────────────────────────────────────────────────────────────────┐    │
│     │ Community discusses, refines, and gains support                │    │
│     └──────────────────────────────────────────────────────────────────┘    │
│                                    │                                        │
│                                    v                                        │
│  3. VOTING PERIOD                                                           │
│     ┌──────────────────────────────────────────────────────────────────┐    │
│     │ Token holders vote (e.g., 7 days)                              │    │
│     │ Quorum + threshold requirements                                 │    │
│     └──────────────────────────────────────────────────────────────────┘    │
│                                    │                                        │
│                                    v                                        │
│  4. EXECUTION                                                                │
│     ┌──────────────────────────────────────────────────────────────────┐    │
│     │ If passed, smart contract executes proposal                    │    │
│     │ (e.g., transfer funds, update protocol)                        │    │
│     └──────────────────────────────────────────────────────────────────┘    │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────────────────┐
│                    REGULATORY APPROACHES                                    │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    PRO-CRYPTO                                        │   │
│  │  • Clear frameworks                                                  │   │
│  │  • Innovation-friendly                                               │   │
│  │  • Examples: Switzerland, Singapore, UAE                           │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    REGULATED PROGRESS                                │   │
│  │  • Developing frameworks                                             │   │
│  │  • Balancing innovation and consumer protection                     │   │
│  │  • Examples: EU (MiCA), UK (FCA), US (State level)                 │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    RESTRICTIVE                                       │   │
│  │  • Bans or severe restrictions                                       │   │
│  │  • Consumer protection focus                                         │   │
│  │  • Examples: China, India (restrictive), Turkey                    │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────────────────┐
│                    REGTECH IN BLOCKCHAIN                                    │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    ON-CHAIN MONITORING                               │   │
│  │  • Real-time transaction monitoring                                  │   │
│  │  • Anomaly detection                                                 │   │
│  │  • Tools: Chainalysis, Elliptic, CipherTrace                       │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    TRAVEL RULE COMPLIANCE                             │   │
│  │  • Secure data sharing protocols                                     │   │
│  │  • Tools: TRISA, Travel Rule Protocol                               │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    SMART CONTRACT AUDITING                            │   │
│  │  • Formal verification                                                │   │
│  │  • Vulnerability scanning                                             │   │
│  │  • Tools: Trail of Bits, Certik, OpenZeppelin                       │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    COMPLIANCE DASHBOARDS                             │   │
│  │  • Real-time compliance reporting                                    │   │
│  │  • Regulatory reporting automation                                   │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

# ===================================================================
# MODULE 1, LESSON 8: BLOCKCHAIN GOVERNANCE AND REGULATORY FRAMEWORKS
# ===================================================================

import hashlib
import time
import json
import random
from typing import List, Dict, Optional, Set
from dataclasses import dataclass
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import warnings
warnings.filterwarnings('ignore')

print("="*70)
print("BLOCKCHAIN GOVERNANCE AND REGULATORY FRAMEWORKS")
print("="*70)

# ----------------------------------------------------------------
# PART A: SIMPLE GOVERNANCE VOTING SIMULATION
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART A: Governance Voting Simulation")
print("-"*60)

class GovernanceToken:
    def __init__(self, name: str, symbol: str):
        self.name = name
        self.symbol = symbol
        self.balances: Dict[str, int] = {}
        self.total_supply = 0
    
    def mint(self, address: str, amount: int):
        self.balances[address] = self.balances.get(address, 0) + amount
        self.total_supply += amount
    
    def get_balance(self, address: str) -> int:
        return self.balances.get(address, 0)
    
    def get_voting_power(self, address: str) -> int:
        return self.get_balance(address)

class GovernanceProposal:
    def __init__(self, id: int, proposer: str, description: str, target_amount: int = 0):
        self.id = id
        self.proposer = proposer
        self.description = description
        self.target_amount = target_amount
        self.votes_for = 0
        self.votes_against = 0
        self.status = "pending"  # pending, active, executed, rejected
        self.start_time = time.time()
        self.end_time = self.start_time + 30  # 30 seconds voting window
        self.executed = False
    
    def vote(self, voter: str, voting_power: int, support: bool):
        if time.time() > self.end_time:
            print("Voting period has ended.")
            return False
        if support:
            self.votes_for += voting_power
        else:
            self.votes_against += voting_power
        print(f"Voter {voter[:8]} voted {'FOR' if support else 'AGAINST'} with {voting_power} power")
        return True
    
    def get_result(self) -> Dict:
        total = self.votes_for + self.votes_against
        return {
            'for': self.votes_for,
            'against': self.votes_against,
            'total': total,
            'passed': self.votes_for > self.votes_against,
            'quorum_reached': total > 100  # minimum quorum
        }
    
    def execute(self) -> bool:
        result = self.get_result()
        if self.status != "pending":
            return False
        if result['passed'] and result['quorum_reached']:
            self.status = "executed"
            self.executed = True
            print(f"Proposal {self.id} EXECUTED!")
            return True
        else:
            self.status = "rejected"
            print(f"Proposal {self.id} REJECTED.")
            return False

class DAO:
    def __init__(self, name: str, token: GovernanceToken):
        self.name = name
        self.token = token
        self.proposals: List[GovernanceProposal] = []
        self.treasury = 1000  # in native tokens
        self.proposal_counter = 0
        self.members: Set[str] = set()
        self.vote_history: List[Dict] = []
    
    def add_member(self, address: str, initial_tokens: int = 100):
        self.token.mint(address, initial_tokens)
        self.members.add(address)
    
    def create_proposal(self, proposer: str, description: str, amount: int = 0) -> int:
        if proposer not in self.members:
            print("Only members can create proposals.")
            return -1
        self.proposal_counter += 1
        proposal = GovernanceProposal(self.proposal_counter, proposer, description, amount)
        self.proposals.append(proposal)
        print(f"Proposal {self.proposal_counter} created: {description}")
        return self.proposal_counter
    
    def vote(self, proposal_id: int, voter: str, support: bool):
        if voter not in self.members:
            print("Only members can vote.")
            return
        proposal = self.get_proposal(proposal_id)
        if not proposal:
            return
        voting_power = self.token.get_voting_power(voter)
        if voting_power <= 0:
            print(f"{voter} has no voting power.")
            return
        proposal.vote(voter, voting_power, support)
        self.vote_history.append({
            'proposal_id': proposal_id,
            'voter': voter,
            'support': support,
            'voting_power': voting_power,
            'timestamp': time.time()
        })
    
    def get_proposal(self, proposal_id: int) -> Optional[GovernanceProposal]:
        for p in self.proposals:
            if p.id == proposal_id:
                return p
        return None
    
    def execute_proposal(self, proposal_id: int):
        proposal = self.get_proposal(proposal_id)
        if not proposal:
            return
        # Check time has passed
        if time.time() < proposal.end_time:
            print("Voting period not yet ended.")
            return
        if proposal.execute():
            if proposal.target_amount > 0 and proposal.target_amount <= self.treasury:
                self.treasury -= proposal.target_amount
                print(f"Treasury reduced by {proposal.target_amount}")
        self.vote_history.append({
            'proposal_id': proposal_id,
            'action': 'execute',
            'result': proposal.status,
            'timestamp': time.time()
        })
    
    def get_proposal_summary(self) -> pd.DataFrame:
        data = []
        for p in self.proposals:
            result = p.get_result()
            data.append({
                'ID': p.id,
                'Description': p.description[:30] + "...",
                'For': p.votes_for,
                'Against': p.votes_against,
                'Status': p.status
            })
        return pd.DataFrame(data)
    
    def get_metrics(self) -> Dict:
        total_votes = len(self.vote_history)
        executed = sum(1 for p in self.proposals if p.status == "executed")
        return {
            'proposals': len(self.proposals),
            'executed': executed,
            'total_votes': total_votes,
            'members': len(self.members),
            'treasury': self.treasury
        }

# Create DAO
dao_token = GovernanceToken("Governance Token", "GOV")
dao = DAO("Digital Finance DAO", dao_token)

# Add members
members = [
    "0xAlice", "0xBob", "0xCharlie", "0xDavid", "0xEve", 
    "0xFrank", "0xGrace", "0xHenry", "0xIvy", "0xJack"
]

print("DAO Members:")
for i, member in enumerate(members):
    initial_tokens = random.randint(50, 200)
    dao.add_member(member, initial_tokens)
    print(f"  {member}: {initial_tokens} GOV")

# Create proposals
dao.create_proposal("0xAlice", "Upgrade protocol to version 2.0", 0)
dao.create_proposal("0xBob", "Allocate 100 tokens for marketing", 100)
dao.create_proposal("0xCharlie", "Add new lending pool for stablecoins", 0)

# Simulate voting
print("\n--- Voting ---")
for i in range(10):
    voter = random.choice(members)
    proposal_id = random.randint(1, 3)
    support = random.choice([True, False])
    dao.vote(proposal_id, voter, support)

# Execute proposals
time.sleep(1)  # Wait for voting to complete
print("\n--- Execution ---")
for i in range(1, 4):
    dao.execute_proposal(i)

# Show summary
print("\n--- Proposal Summary ---")
print(dao.get_proposal_summary().to_string(index=False))

print(f"\n--- DAO Metrics ---")
metrics = dao.get_metrics()
for k, v in metrics.items():
    print(f"  {k}: {v}")

# ----------------------------------------------------------------
# PART B: REGULATORY COMPLIANCE FRAMEWORK
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART B: Regulatory Compliance Framework")
print("-"*60)

class ComplianceCheck:
    def __init__(self):
        self.checklist = []
        self.passed = []
        self.failed = []
    
    def add_check(self, name: str, test_func, description: str):
        self.checklist.append({
            'name': name,
            'test': test_func,
            'description': description
        })
    
    def run_checks(self, data: Dict):
        for check in self.checklist:
            result = check['test'](data)
            if result:
                self.passed.append(check['name'])
                print(f"✓ {check['name']}: {check['description']} - PASSED")
            else:
                self.failed.append(check['name'])
                print(f"✗ {check['name']}: {check['description']} - FAILED")
        return len(self.failed) == 0
    
    def get_summary(self) -> Dict:
        return {
            'total': len(self.checklist),
            'passed': len(self.passed),
            'failed': len(self.failed),
            'status': 'COMPLIANT' if len(self.failed) == 0 else 'NON-COMPLIANT'
        }

# Simulate KYC check functions
def kyc_check(user_data: Dict) -> bool:
    required_fields = ['name', 'date_of_birth', 'nationality', 'id_number']
    return all(field in user_data for field in required_fields)

def sanctions_check(user_data: Dict) -> bool:
    # Simulate sanctions list check
    sanctions_list = ['John Doe', 'Jane Smith']
    return user_data.get('name') not in sanctions_list

def aml_check(user_data: Dict) -> bool:
    # Simulate AML risk assessment
    risk_factors = ['high_risk_jurisdiction', 'pep', 'unusual_tx_pattern']
    return not any(factor in user_data.get('risk_indicators', []) for factor in risk_factors)

def tax_check(user_data: Dict) -> bool:
    # Simulate tax reporting requirements
    required = ['tax_id', 'tax_country', 'reporting_status']
    return all(field in user_data for field in required)

def data_privacy_check(user_data: Dict) -> bool:
    # Simulate GDPR/CCPA compliance
    privacy_fields = ['consent_given', 'data_retention_policy', 'right_to_erasure']
    return all(field in user_data.get('privacy', {}) for field in privacy_fields)

# Create compliance framework
compliance = ComplianceCheck()
compliance.add_check("KYC", kyc_check, "KYC documents provided and verified")
compliance.add_check("Sanctions", sanctions_check, "Not on sanctions watchlist")
compliance.add_check("AML", aml_check, "AML risk assessment passed")
compliance.add_check("Tax", tax_check, "Tax reporting requirements met")
compliance.add_check("Data Privacy", data_privacy_check, "Data privacy compliance (GDPR/CCPA)")

# Test user data
test_user = {
    'name': 'Alice Johnson',
    'date_of_birth': '1990-01-01',
    'nationality': 'US',
    'id_number': 'ID123456',
    'risk_indicators': ['pep'],  # High risk indicator
    'tax_id': 'TAX-12345',
    'tax_country': 'US',
    'reporting_status': 'compliant',
    'privacy': {
        'consent_given': True,
        'data_retention_policy': '5 years',
        'right_to_erasure': 'acknowledged'
    }
}

print("Running compliance checks for Alice Johnson...")
compliance.run_checks(test_user)
print(f"\nCompliance Summary: {compliance.get_summary()}")

# ----------------------------------------------------------------
# PART C: REGULATORY JURISDICTION COMPARISON
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART C: Regulatory Jurisdiction Comparison")
print("-"*60)

jurisdiction_comparison = pd.DataFrame({
    'Jurisdiction': [
        'EU (MiCA)',
        'US (SEC)',
        'Singapore (MAS)',
        'UK (FCA)',
        'Switzerland (FINMA)',
        'UAE (DFSA)',
        'Hong Kong (SFC)'
    ],
    'Stablecoin Regulation': [
        'Full (reserve, audit)',
        'Through SEC/CFTC',
        'Comprehensive',
        'E-money rules',
        'Fully regulated',
        'In development',
        'In development'
    ],
    'Exchange Licensing': [
        'Yes (MiCA)',
        'State-level',
        'Yes (PSA)',
        'Yes',
        'Yes',
        'Yes',
        'Yes'
    ],
    'Custody Rules': [
        'Comprehensive',
        'Safekeeping rules',
        'Comprehensive',
        'Custody rules',
        'Comprehensive',
        'Comprehensive',
        'Guidelines'
    ],
    'Tax Treatment': [
        'Varies by country',
        'Property tax',
        'Digital assets',
        'Capital gains',
        'Wealth tax',
        'No tax',
        'Capital gains'
    ],
    'DeFi Approach': [
        'Regulating (under MiCA)',
        'Enforcement-based',
        'Innovation-friendly',
        'Risk-based',
        'Regulatory sandbox',
        'Innovation-friendly',
        'Guidance'
    ]
})

print("Jurisdiction Regulatory Comparison:")
print(jurisdiction_comparison.to_string(index=False))

# ----------------------------------------------------------------
# PART D: COMPLIANCE COST ANALYSIS
# -----------------------------------------------------------------

print("\n" + "-"*60)
print("PART D: Compliance Cost Analysis")
print("-"*60)

# Simulated compliance costs over time
years = ['2022', '2023', '2024', '2025', '2026']
base_costs = [200000, 350000, 500000, 650000, 800000]  # USD
regtech_costs = [50000, 120000, 200000, 300000, 400000]  # USD
total_costs = [base_costs[i] + regtech_costs[i] for i in range(len(years))]

cost_data = pd.DataFrame({
    'Year': years,
    'Base Compliance': base_costs,
    'RegTech Investment': regtech_costs,
    'Total': total_costs
})

print("Compliance Cost Projection (Annual):")
print(cost_data.to_string(index=False))

# Visualise
fig, ax = plt.subplots(figsize=(10, 5))
ax.plot(years, base_costs, marker='o', label='Base Compliance', color='red', alpha=0.7)
ax.plot(years, regtech_costs, marker='s', label='RegTech Investment', color='green', alpha=0.7)
ax.plot(years, total_costs, marker='^', label='Total', color='blue', alpha=0.7)
ax.set_xlabel('Year')
ax.set_ylabel('Cost (USD)')
ax.set_title('Compliance Cost Projection')
ax.legend()
ax.grid(True, alpha=0.3)
plt.tight_layout()
plt.savefig('compliance_costs.png', dpi=300, bbox_inches='tight')
plt.show()
print("Compliance cost chart saved as 'compliance_costs.png'")

# ----------------------------------------------------------------
# PART E: GOVERNANCE METRICS DASHBOARD
# -----------------------------------------------------------------

print("\n" + "-"*60)
print("PART E: Governance Metrics Dashboard")
print("-"*60)

governance_metrics = pd.DataFrame({
    'Metric': [
        'Total Proposals',
        'Proposal Success Rate',
        'Average Voter Turnout',
        'Voting Power Gini Coefficient',
        'Proposal Execution Time (avg)',
        'Treasury Value',
        'Active Members',
        'Delegated Votes'
    ],
    'Value': [
        '45',
        '62%',
        '28%',
        '0.72',
        '7.3 days',
        '$5.2M',
        '1,847',
        '34%'
    ],
    'Target': [
        '> 50/year',
        '> 70%',
        '> 40%',
        '< 0.65',
        '< 3 days',
        'Growing',
        '> 2,000',
        '> 50%'
    ],
    'Status': ['🟡', '🟡', '🔴', '🟡', '🔴', '🟢', '🟢', '🟡']
})

print(governance_metrics.to_string(index=False))

# ----------------------------------------------------------------
# PART F: REGULATORY TIMELINE
# -----------------------------------------------------------------

print("\n" + "-"*60)
print("PART F: Key Regulatory Developments Timeline")
print("-"*60)

regulatory_timeline = {
    "2013": "FinCEN issues first virtual currency guidance.",
    "2015": "NYDFS BitLicense framework created.",
    "2018": "EU 5th AML Directive includes crypto.",
    "2019": "FATF Travel Rule extended to VASPs.",
    "2020": "SEC v. Ripple lawsuit filed.",
    "2022": "MiCA framework agreed in EU.",
    "2023": "MiCA officially adopted.",
    "2024": "Global stablecoin regulations emerge.",
    "2025+": "Expected: DeFi regulation, CBDC frameworks."
}

for year, event in regulatory_timeline.items():
    print(f"{year}: {event}")

# ----------------------------------------------------------------
# PART G: COMPLIANCE SCORECARD FOR A DIGITAL BANK
# -----------------------------------------------------------------

print("\n" + "-"*60)
print("PART G: Compliance Scorecard for a Digital Bank")
print("-"*60)

compliance_scorecard = {
    "KYC/AML": {
        "Customer Identification Program": "✅",
        "Ongoing Monitoring": "✅",
        "Transaction Screening": "✅",
        "Enhanced Due Diligence": "⚠️",
        "PEP Screening": "✅"
    },
    "Licensing": {
        "Operating License": "✅",
        "Registration with Regulator": "✅",
        "Reporting Requirements": "⚠️",
        "Capital Requirements": "✅"
    },
    "Data Protection": {
        "GDPR/CCPA Compliance": "✅",
        "Data Breach Response Plan": "⚠️",
        "Privacy Policy": "✅",
        "Data Retention Policy": "✅"
    },
    "Blockchain Specific": {
        "Smart Contract Audits": "✅",
        "Token Classification Review": "⚠️",
        "Wallet Security Standards": "✅",
        "Bridge/Cross-chain Risk Assessment": "🔴"
    }
}

print("Compliance Scorecard:")
for category, items in compliance_scorecard.items():
    print(f"\n{category.upper()}:")
    for item, status in items.items():
        print(f"  {status} {item}")

# ----------------------------------------------------------------
# PART H: SUMMARY AND RECOMMENDATIONS
# ----------------------------------------------------------------

print("\n" + "="*70)
print("PART H: Summary and Recommendations")
print("="*70)

print("""
Blockchain Governance and Regulatory Frameworks – Key Takeaways:

1. Governance ensures protocol upgrades, conflict resolution, and community alignment.
2. On-chain governance is transparent and automated; off-chain is flexible and social.
3. DAOs are decentralised organisations controlled by token holders.
4. Key regulations: MiCA (EU), FATF Travel Rule, SEC enforcement, FCA registration.
5. Jurisdictions vary from pro-crypto (Switzerland, UAE) to restrictive (China).
6. Compliance areas: KYC/AML, Travel Rule, tax reporting, licensing, data privacy.
7. RegTech tools enable automated compliance monitoring and reporting.

Recommendations:
  - Design governance with clear quorum and threshold requirements.
  - Implement a robust KYC/AML program early.
  - Stay informed on regulatory developments in operating jurisdictions.
  - Consider regulatory compliance from the start of any blockchain project.
  - Use RegTech tools to automate compliance monitoring.
  - Engage with regulators through sandbox and consultation programs.
  - Prepare for evolving DeFi and stablecoin regulations.
""")

print("="*70)
print("END OF LESSON 8 – MODULE 1")
print("="*70)

# ----------------------------------------------------------------
# PART I: MODULE 1 COMPLETE – FINAL SUMMARY
# ----------------------------------------------------------------

print("\n" + "="*70)
print("MODULE 1 COMPLETE – FINAL SUMMARY")
print("="*70)

print("""
Congratulations! You have completed Module 1: Foundations of Blockchain Technology.

This module covered:

┌─────────────────────────────────────────────────────────────────────────────┐
│  LESSON 1: Introduction to Blockchain Technology                          │
│  • Definition, history, key characteristics, types, architecture          │
│                                                                             │
│  LESSON 2: Cryptographic Foundations of Blockchain                        │
│  • Hash functions, public-key cryptography, digital signatures, Merkle   │
│                                                                             │
│  LESSON 3: Consensus Mechanisms                                           │
│  • PoW, PoS, DPoS, PBFT, forks, chain selection                          │
│                                                                             │
│  LESSON 4: Smart Contracts and Decentralised Applications                 │
│  • Smart contract execution, DApps, token standards, security            │
│                                                                             │
│  LESSON 5: Blockchain Wallets and Digital Identity                       │
│  • HD wallets, BIP standards, seed phrases, SSI, DIDs                   │
│                                                                             │
│  LESSON 6: Blockchain Scalability – Layer 2 and Sharding                 │
│  • Layer 1/Layer 2, payment channels, rollups, sharding                 │
│                                                                             │
│  LESSON 7: Interoperability and Cross-Chain Technology                   │
│  • Bridges, atomic swaps, interoperability protocols, oracles           │
│                                                                             │
│  LESSON 8: Blockchain Governance and Regulatory Frameworks               │
│  • On/off-chain governance, DAOs, global regulations, compliance        │
└─────────────────────────────────────────────────────────────────────────────┘

Skills developed:
  • Understanding of blockchain architecture and fundamentals
  • Cryptographic principles and their application
  • Python implementations of blockchain concepts
  • Evaluation of consensus mechanisms and scaling solutions
  • Knowledge of governance and regulatory frameworks
  • Practical compliance considerations for digital finance

Next Module: Module 2 – Digital Finance Ecosystems
  • Lesson 1: Overview of Digital Finance
  • Lesson 2: Central Bank Digital Currencies (CBDCs)
  • Lesson 3: DeFi Ecosystem and Protocols
  • Lesson 4: Stablecoins and Payment Systems
  • Lesson 5: Digital Asset Exchanges
  • Lesson 6: Tokenisation and Asset Management
  • Lesson 7: Digital Lending and Credit
  • Lesson 8: Risk Management in Digital Finance
""")