[100% Off] Oracle Financials Business Interview Q&Amp;S Practice Test
Learn Python, Pandas, Matplotlib & more to analyze financial data, measure risk, and backtest trading strategies
What you’ll learn
- Master core Python libraries (Pandas
- NumPy
- Matplotlib) for financial data manipulation and analysis
- Learn to fetch
- clean
- and process real-world financial data from stock market APIs and public datasets.
- Perform quantitative analysis
- including time-series analysis
- calculating returns
- and measuring volatility.
- Build and backtest simple algorithmic trading strategies based on technical indicators.
Requirements
- A basic understanding of Python programming (variables
- data types
- loops
- and functions) is required.
Description
Unlock the power of data in the world of finance. This course will teach you how to use the Python programming language to perform in-depth financial data analysis, make data-driven decisions, and build a foundational toolkit for quantitative finance.
The financial industry is undergoing a data revolution. Whether you’re an aspiring data scientist, a finance professional, or a developer looking to enter the high-demand field of FinTech, your ability to analyze financial data is a critical skill. This course is your complete guide to mastering it using Python, the #1 language for data science.
We will start from the ground up, assuming you have a basic grasp of Python. You’ll first learn how to set up your professional data analysis environment. Then, we dive hands-on into the libraries that power modern data science.
What you’ll master in this course:
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Data Manipulation with Pandas: Learn to use the powerful Pandas library to import, clean, and wrangle complex financial datasets, from CSVs to real-time stock APIs.
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Time-Series Analysis: Finance runs on time! You’ll master time-series data, learning how to resample, calculate returns, and understand stock movements over time.
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Financial Statistics: Go beyond basic analysis. You will learn to calculate key metrics like volatility (risk), moving averages, and correlations between different assets.
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Data Visualization with Matplotlib: Create stunning, insightful financial charts. You’ll learn to plot candlestick charts, moving averages, and portfolio returns to visually communicate your findings.
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Build & Backtest a Trading Strategy: In a capstone project, you will apply everything you’ve learned to build a simple, rules-based trading strategy and backtest its performance against historical data.
This course is 100% practical. You will follow along with a professional instructor and write real code to solve real-world financial problems. By the end, you won’t just know the theory—you’ll have a portfolio of projects and the confidence to apply for financial data analyst roles.
Enroll today and take the first step towards becoming a quantitative finance professional.
