Course Outline
Introduction
Setting Up the Development Environment
- Local vs. Online Programming: Anaconda and Jupyter
Python Programming Fundamentals
- Control structures, data types, functions, data structures, and operators
Extending Python's Capabilities
- Modules and Packages
Building Your First Python Application
- Calculating start and end dates and times
Accessing External Data with Python
- Importing and exporting, including reading and writing CSV data
- Retrieving data from SQL databases
Organizing Data with Arrays and Vectors in Python
- NumPy and vectorized functions
Data Visualization with Python
- Matplotlib for 2D and 3D plotting, pyplot, and SciPy
Data Analysis 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
- Conducting 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
Deploying Your Python Application to Production
- Integrating your application with Excel and other web applications
Application Performance
- Optimizing application efficiency
- Parallel Computing and Multiprocessing
Troubleshooting
Closing Remarks
Requirements
- Foundational knowledge of finance (including securities, derivatives, etc.)
- General understanding of probability and statistics
- Basic 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
