Investment Banker
Python for Risk Analyst
Overview
Build job-ready Python capability for financial analysis, risk modelling, and automation. Learn data manipulation, statistical methods, forecasting, and visualization to streamline workflows and strengthen decision-making in risk-focused finance roles.
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45 Hours of Learning
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3.4K+ Learners
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25,000 (incl. GST)
Skills You Will Learn
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Python programming in finance
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Data manipulation with Pandas
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Predictive financial modelling
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Risk analysis automation
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Market trend prediction
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Insightful charting & reporting
Course Key Highlights
- Analyse financial data using Pandas and NumPy
- Build regression models for risk and forecasting
- Implement Monte Carlo simulations for risk assessment
- Apply machine learning to financial data predictions
- Use Matplotlib and Seaborn for visual insights
- Forecast market trends using time-series models
- Automate financial workflows using Python scripting
Course Time
Includes:
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Self-paced
Modules -
Case studies
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Quizzes
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45 Hours of Learning
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FAQs
What is the main focus of this course?
It focuses on using Python for data analysis, risk modelling, forecasting, and automation in financial contexts.
Do I need prior Python experience?
No, but familiarity with basic programming concepts can help you progress faster.
Which Python libraries will I learn?
You will work with Pandas, NumPy, Matplotlib, and Seaborn, among others.
How does this course help in risk analysis?
It teaches statistical models, simulations, and ML tools for assessing and forecasting financial risks.
Can the techniques be applied outside finance?
Yes, the Python skills learned are adaptable to multiple data analysis domains.
