Financial Data Analysis Courses and Certifications

Coursera

Financial Data Analysis with Excel, Python and Power BI

Master financial data analysis across Excel, Python, R, and Power BI to transform raw data into actionable business insights with advanced formulas, automation, and interactive dashboards.

• Coursera
• 12 hours 53 minutes
• Self-Paced
• Paid Course

Coursera

Transform Raw Data into Financial Insights

Master data transformation techniques to convert raw transaction files into structured financial spreadsheets for enhanced analysis and reporting accuracy.

• Coursera
• 1 hour 9 minutes
• Self-Paced
• Paid Course

Coursera

Cleanse, Analyze and Validate Financial Data

Master advanced Excel and Power Query techniques to transform messy financial data into reliable, automated dashboards with robust validation frameworks for trusted analysis.

• Coursera
• 2 hours 13 minutes
• Self-Paced
• Paid Course

Coursera

Analyze Financial Data: Reconciliation Fast

Master transaction-level financial data analysis, build pivot reports, and perform full reconciliations across ERP, GL, and data warehouse systems for accurate insights.

• Coursera
• 2 hours 32 minutes
• Self-Paced
• Paid Course

Coursera

Analyze Spend: Uncover Hidden Cost Savings

Unlock hidden cost savings through strategic spend analysis using data categorization, cleaning techniques, and pivot tables to transform financial data into actionable insights.

• Coursera
• 2 hours 30 minutes
• Self-Paced
• Paid Course

Professional Certificate: Finance Data Analysis & Analytics

416 ratings at Udemy

Financial Data Analysis, Statistical Analysis in Finance, Analysis of Finance Markets data, Data Analytics in Finance

• Udemy
• 8 hours 35 minutes
• Self-Paced
• Paid Course

Credential

Analyze Financial Data with Python

Master Python for financial analytics through hands-on data processing, visualization, and portfolio optimization using NumPy, Pandas, and APIs.

• Codecademy
• 26 hours
• Self-Paced
• Free Trial Available

EDUCBA

Apply Python for Practical Financial Data Analysis

Master Python programming for financial analysis, visualizing market trends, and interpreting key indicators using real-world datasets and industry-relevant techniques.

• Coursera
• 5 hours 13 minutes
• Self-Paced
• Paid Course

Part Time Larry

Detecting Price and Volume Patterns with SQL and TimescaleDB

Learn to detect stock price patterns using SQL and TimescaleDB. Explore PostgreSQL functions, TimescaleDB features, and analyze real-world examples to identify bullish engulfing and three-bar breakout patterns.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

Derek Banas

Stock Market Prediction Using Regression Analysis - Python for Finance

Learn stock market prediction using Python, covering regression analysis, forecasting, and ARIMA models to guide investment decisions based on past performance.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Fields Institute

Learning From Transaction-Level Investment Account Data

Explore machine learning techniques for analyzing transaction-level investment data, focusing on practical applications in wealth management and financial decision-making.

• YouTube
• 56 minutes
• Self-Paced
• Free Video

Fields Institute

Market Graph Clustering via QUBO and Digital Annealing

Explore innovative market graph clustering techniques using QUBO and Digital Annealing, uncovering insights into complex financial networks and data structures.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Intermediate R for Finance

11 ratings at DataCamp

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

• DataCamp
• 5 hours
• Self-Paced
• Free Trial Available

Introduction to Portfolio Analysis in Python

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Time Series with data.table in R

Master time series data manipulation using data.table in R. Learn efficient techniques for handling large datasets, performing feature engineering, and building statistical models with financial data.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available