Applied Data Science for Finance

Explore essential math symbols for data analysis and optimization, including mu (mean), sigma (std dev), variance, covariance, rho, arg max/min, and set operations like union and intersection.

See how Anaconda, Jupyter, and VSCode streamline Python development by managing environments, notebooks, and code with pre-installed libraries and powerful editing tools.

Dive into Python syntax, variables, and data types, including integers, floats, strings, booleans, and none. Master type conversions, dynamic typing, arithmetic and logical operations, comparisons, and operator precedence.

Explore how Python uses conditional statements and loops to control program behavior, including if, elif, else, for and while loops, range, and break and continue control statements.

Explore modules, packages, and importing libraries in Python, including the standard library and third-party tools like NumPy and pandas; learn import syntax, aliases, and focused imports.

Learn Python file handling by opening, reading, writing, and closing text and CSV files, and using pandas to load, manipulate, filter, and export data.

Learn data cleaning techniques to remove dirty data and fix missing values, duplicates, outliers, and inconsistencies, then standardize, validate, and preprocess with pipelines.

Learn how feature scaling and normalization ensure all data features contribute equally, improve convergence, and support distance-based algorithms like k-nearest neighbors, support vector machines, and k-means.

Standardization transforms features to zero mean and unit variance, ensuring equal contribution and faster training for models such as logistic regression, SVM, and PCA, even across diverse scales.

Explore data visualization basics in Python using Matplotlib and Seaborn to create line plots, bar charts, histograms, heatmaps, violin plots, and customize styles and palettes.

Explore the income statement, balance sheet, and cash flow statement to understand revenue, expenses, assets, liabilities, and equity, and assess cash flow health.

Explore macroeconomics, including GDP, inflation, unemployment, and policy tools. Learn how fiscal and monetary policies, exchange rates, and trade impact growth, stability, and living standards.

Explore how technical analysis uses price, volume, and chart patterns—line, bar, and candlesticks—to identify trends, support and resistance, and signals from indicators like moving averages, RSI, MACD, and Bollinger bands.

Explore financial instruments as contracts representing assets and liabilities; cover equity, debt, derivatives, hybrid instruments, trading venues, valuation methods, and risk factors.