# ===================================================================
# MODULE 10, LESSON 6: A VISION FOR THE FUTURE
# ===================================================================

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime, timedelta
import warnings
warnings.filterwarnings('ignore')

print("="*70)
print("A VISION FOR THE FUTURE – SHAPING THE NEXT DECADE")
print("="*70)

# ----------------------------------------------------------------
# PART A: FUTURE TRENDS AND OPPORTUNITIES
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART A: Future Trends and Opportunities")
print("-"*60)

future_trends = pd.DataFrame({
    'Trend': [
        'Generative AI',
        'Quantum Computing',
        'Decentralised Finance (DeFi)',
        'Sustainable Finance / ESG',
        'Explainable AI',
        'Human-AI Collaboration',
        'Data Privacy & Sovereignty',
        'Edge AI & IoT',
        'Autonomous Finance',
        'Federated Learning'
    ],
    'Impact (1-10)': [10, 8, 7, 8, 9, 8, 7, 6, 7, 8],
    'Maturity (1-10)': [6, 2, 4, 5, 6, 5, 4, 5, 3, 4],
    'Opportunity for Me': ['High', 'Medium', 'Medium', 'High', 'High', 'High', 'High', 'Medium', 'Medium', 'High']
})

print("Future Trends and Opportunities:")
print(future_trends.to_string(index=False))

# Visualise
fig, ax = plt.subplots(figsize=(10, 8))
scatter = ax.scatter(future_trends['Maturity'], future_trends['Impact'], 
                     s=200, c=range(len(future_trends)), cmap='coolwarm', alpha=0.7)
for i, row in future_trends.iterrows():
    ax.annotate(row['Trend'], (row['Maturity'] + 0.1, row['Impact'] + 0.1), fontsize=8)
ax.set_xlabel('Maturity')
ax.set_ylabel('Impact')
ax.set_title('Future Trends: Impact vs Maturity')
ax.grid(True, alpha=0.3)
plt.colorbar(scatter, ax=ax, label='Priority')
plt.tight_layout()
plt.savefig('future_trends.png', dpi=300, bbox_inches='tight')
plt.show()
print("Future trends visualisation saved as 'future_trends.png'")

# ----------------------------------------------------------------
# PART B: PERSONAL VISION STATEMENT
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART B: Personal Vision Statement")
print("-"*60)

vision_statement = """
--- MY PERSONAL VISION ---

I envision a future where:
1. ____________________________________________________________
2. ____________________________________________________________
3. ____________________________________________________________

My role in creating this future is:
1. ____________________________________________________________
2. ____________________________________________________________
3. ____________________________________________________________

The legacy I want to leave is:
____________________________________________________________

I will measure my success by:
1. ____________________________________________________________
2. ____________________________________________________________
3. ____________________________________________________________
"""

print("Personal Vision Statement Template:")
print(vision_statement)

# Example vision statement
example_vision = """
--- EXAMPLE PERSONAL VISION ---

I envision a future where:
1. Financial services are accessible, fair, and sustainable for all.
2. AI is trusted and transparent, serving humanity.
3. Data is used responsibly to solve the world's biggest challenges.

My role in creating this future is:
1. Leading the development of responsible, inclusive AI.
2. Advocating for ethical AI policies and standards.
3. Mentoring the next generation of diverse data scientists.

The legacy I want to leave is:
A more equitable world where AI empowers everyone.

I will measure my success by:
1. The number of people whose lives are improved by my work.
2. The adoption of ethical AI standards I helped shape.
3. The success and growth of those I have mentored.
"""

print("\nExample Vision Statement:")
print(example_vision)

# ----------------------------------------------------------------
# PART C: 10-YEAR ACTION PLAN
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART C: 10-Year Action Plan")
print("-"*60)

action_plan = {
    "Year 1-2": {
        "Focus": "Build expertise and establish credibility.",
        "Actions": [
            "Master core ML and financial domain skills.",
            "Build 5 portfolio projects.",
            "Earn 2 certifications.",
            "Attend 4 conferences and 12 meetups.",
            "Write 6 blog posts or articles."
        ],
        "Key Milestones": [
            "Project completed and deployed.",
            "Certifications achieved.",
            "Network of 500+ professionals."
        ]
    },
    "Year 3-5": {
        "Focus": "Lead projects and drive strategy.",
        "Actions": [
            "Lead 3 cross-functional projects.",
            "Mentor 5 junior team members.",
            "Speak at 4 conferences.",
            "Contribute to open-source projects.",
            "Publish a research paper or book chapter."
        ],
        "Key Milestones": [
            "Projects delivered with measurable impact.",
            "Mentees promoted to senior roles.",
            "Thought leadership recognition."
        ]
    },
    "Year 6-8": {
        "Focus": "Shape the field and influence policy.",
        "Actions": [
            "Lead a data science team or function.",
            "Engage with regulators on AI policy.",
            "Found or lead an industry working group.",
            "Publish a book or comprehensive guide.",
            "Build a global network of collaborators."
        ],
        "Key Milestones": [
            "Team impact and growth.",
            "Policy contributions adopted.",
            "Book published and well-received."
        ]
    },
    "Year 9-10": {
        "Focus": "Create lasting impact and legacy.",
        "Actions": [
            "Advise organisations on ethical AI.",
            "Establish a foundation or scholarship.",
            "Mentor a new generation of leaders.",
            "Write a memoir or capstone work.",
            "Leave a lasting legacy in the field."
        ],
        "Key Milestones": [
            "Foundation or initiative established.",
            "Mentees leading in their own right.",
            "Legacy recognised by peers."
        ]
    }
}

for period, details in action_plan.items():
    print(f"\n{period}:")
    print(f"  Focus: {details['Focus']}")
    print("  Actions:")
    for action in details['Actions']:
        print(f"    • {action}")
    print("  Key Milestones:")
    for milestone in details['Key Milestones']:
        print(f"    • {milestone}")

# ----------------------------------------------------------------
# PART D: MY CONTRIBUTION TO THE FIELD
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART D: My Contribution to the Field")
print("-"*60)

contribution_areas = {
    "Technical Contributions": [
        "Build open-source tools for financial AI.",
        "Publish research on explainable AI.",
        "Develop best practices for model validation.",
        "Create educational resources for data scientists."
    ],
    "Community Contributions": [
        "Mentor junior data scientists.",
        "Organise meetups and conferences.",
        "Lead special interest groups.",
        "Write articles and books."
    ],
    "Policy Contributions": [
        "Engage with regulators on AI policy.",
        "Shape industry standards for ethical AI.",
        "Advocate for financial inclusion.",
        "Promote sustainable finance."
    ],
    "Cultural Contributions": [
        "Foster a culture of ethics and responsibility.",
        "Promote diversity and inclusion.",
        "Encourage collaboration and openness.",
        "Inspire the next generation."
    ]
}

print("Areas of Contribution:")
for area, contributions in contribution_areas.items():
    print(f"\n{area}:")
    for contribution in contributions:
        print(f"  • {contribution}")

# ----------------------------------------------------------------
# PART E: REFLECTION ON THE JOURNEY
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART E: Reflection on the Journey")
print("-"*60)

reflection_questions = [
    "What are the most important things I have learned?",
    "How have I grown as a data scientist and a leader?",
    "What are my proudest achievements?",
    "What challenges have I overcome?",
    "What has surprised me about this journey?",
    "What advice would I give to my younger self?",
    "What do I still want to learn?",
    "How do I want to contribute to the field?",
    "What legacy do I want to leave?",
    "What will I do next?"
]

print("Reflection Questions:")
for i, question in enumerate(reflection_questions, 1):
    print(f"{i}. {question}")

# ----------------------------------------------------------------
# PART F: COMMITMENT TO THE FUTURE
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART F: Commitment to the Future")
print("-"*60)

commitment_template = """
--- MY COMMITMENT ---

I, {name}, commit to:

1. Continuous Learning:
   ____________________________________________________________

2. Ethical Leadership:
   ____________________________________________________________

3. Community Engagement:
   ____________________________________________________________

4. Making a Difference:
   ____________________________________________________________

Signed: __________________
Date: __________________
"""

print("Commitment Statement Template:")
print(commitment_template)

# Example commitment
example_commitment = """
--- EXAMPLE COMMITMENT ---

I, [Your Name], commit to:

1. Continuous Learning:
   Dedicate at least 5 hours per week to learning new skills and exploring emerging technologies.

2. Ethical Leadership:
   Lead by example in promoting responsible, transparent, and fair AI.

3. Community Engagement:
   Mentor at least one person per year, contribute to open source, and speak at conferences.

4. Making a Difference:
   Apply my skills to solve problems that matter – financial inclusion, sustainability, and equity.

Signed: __________________
Date: __________________
"""

print("\nExample Commitment Statement:")
print(example_commitment)

# ----------------------------------------------------------------
# PART G: FINAL MESSAGE
# ----------------------------------------------------------------

print("\n" + "="*70)
print("PART G: Final Message")
print("="*70)

final_message = """
--- A MESSAGE TO YOU ---

You have completed the Diploma in Financial Data Analytics.

This journey has taken you through:
- Data Engineering and Warehousing
- Exploratory Data Analysis
- Statistical Foundations
- Predictive Modelling and Machine Learning
- Risk Analytics
- Advanced Topics in AI and Finance
- Emerging Technologies
- Practical Implementation and Leadership
- Capstone Project
- Career Development and Community Engagement

You are now equipped with the knowledge, skills, and mindset to lead in the rapidly evolving field of financial data science.

The future is not something that happens to us – it is something we create.

As you go forward:
- Stay curious and keep learning.
- Lead with integrity and purpose.
- Build bridges and collaborate.
- Make a difference and leave a legacy.

The world needs ethical, skilled, and visionary data scientists.

You are now one of them.

Go forth and make your mark.

--- THE END ---
"""

print(final_message)

print("="*70)
print("END OF LESSON 6 – MODULE 10")
print("="*70)
print("END OF THE DIPLOMA IN FINANCIAL DATA ANALYTICS")
print("="*70)