Python For Finance

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Python is a versatile language that is widely used in many industries. It has become an essential tool for finance professionals for data analysis, automation, machine learning, and more. 

Our expert instructors will guide you through the basics of Python programming, including data types, variables, functions, and control flow. In particular, our financial experts will teach you the python you need to automate, extend and improve your work in all areas of finance from pricing to treasury, risk management to modelling. You will learn how to use Python to read, manipulate, and visualize financial data, as well as how to automate repetitive tasks.

Our hands-on approach to learning means that you will have plenty of opportunities to practice what you've learned in real-world financial scenarios. By the end of the course, you will be confident in your ability to use Python to solve finance-related problems and make informed decisions based on data in your day-to-day work.

• Data Analysis: Python has become the go-to language for data analysis in many industries, including finance. Python offers a wide range of libraries and frameworks that make it easy to access, analyze and manipulate large datasets.
• Automation: Python is a powerful language for automation and can be used to automate repetitive tasks such as data entry, report generation, and financial modeling. This saves time and reduces operational risk in many areas of finance.
• Flexibility: Python is a versatile language that can be used for a wide range of tasks, including web development, data analysis, automation, and machine learning. This flexibility makes it a valuable skill for finance professionals who need to work and integrate with a variety of tools and technologies.
• Industry Adoption: Python has become one of the most widely used programming languages in many industries, including finance. 
• Machine Learning: Machine learning is increasingly being used in finance to predict market trends, identify investment opportunities, and manage risk. Python is the most popular language for machine learning and has many libraries and frameworks for building and deploying machine learning models.
• Environment: Python naturally supports running snippets of code to allow incremental and feedback development. Tools such as Jupyter notebook allow sharing of python snippets with colleagues.

Content will include

• Introduction to Python: In this section, you will learn the basics of Python programming language, including setting up your python environment, data types, variables, operators, and functions. You will also learn how to use Python's built-in libraries to perform common financial calculations.
• Data Input: You will learn how to access data from files (raw text, Excel CSV, JSON) as well as from web-based data sources (via HTML requests).
• Data Manipulation: You will learn how to clean and preprocess data using Python libraries like Pandas and NumPy. Extensive text manipulation using regex commands.
• Data Visualization: You will learn how to visualize financial data using Python libraries, and how to create different types of charts and graphs that can help you understand financial trends and patterns.
• Time Series Analysis: You will learn how to work with time series data, including how to use Python libraries to analyze and forecast time series data.
• Automation: You will learn how to automate repetitive tasks such as data collection, cleaning, and analysis.
• Machine Learning: You will learn the basics of machine learning and how to use Python libraries to create predictive models for financial data.
• Case Studies: Throughout the course, you will work on real-world case studies that demonstrate how Python can be used to solve common finance-related problems.

Attendees will develop simplified but realistic finance components during the course such as curve  and vol interpolators, swap pricers, file/web IO for data processing and more.

This course is aimed at finance professionals with little or no previous Python experience. 

Course contents and duration can be modified to align with additional client needs. 

Delivery can be on-site, remote or in recorded form.