Course Outline
Introduction
Setting Up the Development Environment
- Programming locally versus online: Anaconda and Jupyter
Python Programming Fundamentals
- Control structures, data types, functions, data structures, and operators
Extending Python's Capabilities
- Modules and Packages
Your First Python Application
- Estimating start and end dates and times
Accessing External Data with Python
- Importing and exporting, reading and writing CSV data
- Accessing data within an SQL database
Organizing Data Using Arrays and Vectors in Python
- NumPy and vectorized functions
Visualizing Data with Python
- Matplotlib for 2D and 3D plotting, pyplot, and SciPy
Analyzing Data with Python
- Data analysis using scipy.stats and pandas
- Importing and exporting financial data (Excel, web data, etc.)
Simulating Asset Price Trajectories
- Monte Carlo simulation
Asset Allocation and Portfolio Optimization
- Performing capital allocation, asset allocation, and risk assessment
Risk Analysis and Investment Performance
- Defining and solving portfolio optimization problems
Fixed-Income Analysis and Option Pricing
- Performing fixed-income analysis and option pricing
Financial Time Series Analysis
- Analyzing time series data in financial markets
Taking Your Python Application into Production
- Integrating your application with Excel and other web applications
Application Performance
- Optimizing your application
- Parallel Computing and Multiprocessing
Troubleshooting
Closing Remarks
Requirements
- A solid understanding of finance (including securities, derivatives, etc.)
- A general grasp of probability and statistics
- Fundamental knowledge of differential and integral calculus
Testimonials (3)
Experience of the trainer and his way of conveying the content
Roggli Marc - Bechtle Schweiz AG
Course - FinOps
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
The trainer was very available to answer all te kind of question I did
