数据、人工智能和云计算课程

• 基本的技能水平
• 4.7+
• 4.5K

Build Python skills to elevate your finance career. Learn how to work with lists, arrays and data visualizations to master financial analyses.

• 中间的技能水平
• 4.7+
• 2.1K

Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.

• 中间的技能水平
• 4.5+
• 2.1K

Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

• 中间的技能水平
• 4.7+
• 1.4K

Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.

• 基本的技能水平
• 4.6+
• 1.2K

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

• 中间的技能水平
• 4.7+
• 768

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

• 中间的技能水平
• 4.7+
• 708

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

• 中间的技能水平
• 4.6+
• 649

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

• 基本的技能水平
• 4.8+
• 625

Learn essential finance math skills with practical Excel exercises and real-world examples.

• 基本的技能水平
• 4.6+
• 599

Using Python and NumPy, learn the most fundamental financial concepts.

• 先进的技能水平
• 4.6+
• 537

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

• 中间的技能水平
• 4.4+
• 489

You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.

• 中间的技能水平
• 4.5+
• 474

In this course, youll learn how to import and manage financial data in Python using various tools and sources.

• 基本的技能水平
• 4.8+
• 429

Learn key financial concepts such as capital investment, WACC, and shareholder value.

• 先进的技能水平
• 4.7+
• 395

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.

• 基本的技能水平
• 4.5+
• 386

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

• 中间的技能水平
• 4.7+
• 380

Discover how to use the income statement and balance sheet in Power BI

• 中间的技能水平
• 4.1+
• 362

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

• 基本的技能水平
• 4.4+
• 361

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

• 中间的技能水平
• 4.3+
• 340

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.

• 中间的技能水平
• 4.7+
• 322

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

• 中间的技能水平
• 4.7+
• 270

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

• 基本的技能水平
• 4.4+
• 247

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

• 基本的技能水平
• 4.5+
• 232

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

• 基本的技能水平
• 4.8+
• 219

Learn business valuation with real-world applications and case studies using discounted cash flows (DCF).

• 中间的技能水平
• 4.1+
• 211

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

• 先进的技能水平
• 4.5+
• 200

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

• 中间的技能水平
• 4.6+
• 179

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

• 中间的技能水平
• 4.6+
• 140

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

• 中间的技能水平
• 4.6+
• 119

Learn how to access financial data from local files as well as from internet sources.