I'm currently learning python to better my interests data science.

Here are the key projects I am working on, all centered around the finance sector. The goal is for them to demonstrate my expertise in applying programming, data analysis, and machine learning to solve complex problems in the finance sector. Each project showcases different skills and technologies, including Python, R, SQL, Excel, Power BI, Tableau, and machine learning.

Description: A web-based dashboard that allows users to assess their financial health through various metrics. It features interactive calculators for budgeting, retirement planning, and investment analysis.

Technologies To Be Used: Python, Django, JavaScript, HTML, CSS

Key Features:

• User authentication and data security
• Real-time financial health metrics calculation
• Interactive data visualizations

Description: An R-powered tool for investment portfolio analysis, providing insights into risk, return, and diversification. It also offers optimization strategies and simulates portfolio performance under different scenarios.

Technologies To Be Used: R, Shiny, HTML, CSS

Key Features:

• Portfolio risk and return analysis
• Monte Carlo simulations for forecasting
• Benchmark comparison

Description: A dashboard that visualizes key financial performance indicators (KPIs) for corporate clients, aggregating data from various sources.

Technologies To Be Used: SQL, Excel, Power BI

Key Features:

• Integration with SQL databases
• Data cleaning and analysis in Excel
• Interactive visualizations in Power BI

Description: A web-based tool that uses statistical models to assess market risk, calculating Value at Risk (VaR), and performing Monte Carlo simulations.

Technologies To Be Used: Python or R, Flask or Django for web development

Key Features:

• VaR and CVaR calculation
• User input for custom scenario analysis
• Graphical representation of risk metrics

Description: An interactive dashboard in Tableau tracking key economic indicators to help users understand the economic environment.

Technologies To Be Used: Tableau

Key Features:

• Real-time data integration
• Interactive and engaging visualizations
• Comprehensive economic analysis

Description: A machine learning model that predicts the likelihood of loan default based on financial information, accessible via a web interface.

Technologies To Be Used: Python, scikit-learn or TensorFlow, Flask or Django

Key Features:

• Predictive modeling for credit scoring
• User-friendly web interface for score retrieval
• High accuracy and precision in predictions

Description: An educational game designed to teach financial literacy through interactive scenarios and challenges.

Technologies To Be Used: Python (Pygame) or JavaScript (HTML5 Canvas)

Key Features:

• Engaging gameplay with financial education
• Scenarios covering budgeting, investing, and debt management
• Cross-platform compatibility

A roadmap of certifications I aim to achieve , organized by technology and subject area.

• Power BI: Microsoft Power BI Data Analyst Professional Certificate (Coursera)

• SQL: PostgreSQL Professional Certification

• Excel: Financial Modeling Institute

• Tableau: Tableau Certification

• Microsoft Office Specialist: Excel Expert 2019: MOS Excel Expert 2019

• SQL: Cloudera CCA Data Analyst
• SQL: Microsoft Certified: Azure Database Administrator Associate

• Python: Python Institute - PCEP

• R: IBM Data Analyst Professional Certificate (Coursera)

• Data Structures and Algorithms Specialization: Coursera - Data Structures and Algorithms

• Statistics: SAS Statistical Business Analyst

• AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty
• Cloud Technologies - Beginner: Microsoft Certified: Azure AI Fundamentals

Python(learning)

This part is to communicate the findings from the analysis l would have done in my learning journey