Course description
This course offers an intensive hands-on introduction to the use of Python in financial data analysis, utilizing powerful libraries to apply modern analytical techniques. Practical case studies using real-world data from tickers to stock indices provide hands-on experience in the Python Jupyter notebook environment.
Delegates will learn how to code in Python, a fast-growing programming language used for rapid application development, task automation and data analytics. The training will then move to specialized, data analytics applications of Python, finishing with modern, statistical and machine learning techniques.
Upcoming start dates
Suitability - Who should attend?
This course is ideal for financial analysts, business analysts, portfolio analysts, quantitative analysts, risk managers, model validators, quantitative developers and information systems professionals. No prior coding experience is necessary. Those who want to harness the power of the growing amount of data available, and move beyond using Excel to analyse large financial datasets and begin using the Python programming language to clean, analyse and visualise complex financial data.
Outcome / Qualification etc.
Key Learning Outcomes:
- Effectively use Python in a data analysis context to import, clean, reshape and analyze data
- Describe the Python libraries that are relevant to data analytics and use them fluently
- Critically evaluate and deploy a range of advanced statistical and analytical techniques to extract insights and make predictions from data using the Python programming language
- Communicate analytical insights and observations to both technical and non-technical stakeholders using sophisticated data visualization techniques
- Leverage modern machine learning techniques when analyzing data in the financial services sector
- Draw informed conclusions that facilitate data driven decisions.
Why choose Fitch Learning
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Over 1,300 clients worldwide
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Fitch Learning
Part of the Fitch Group, Fitch Learning partners with clients to enhance knowledge, skills and conduct. With centers in London, New York, Singapore, Dubai and Hong Kong, we are committed to questioning and understanding client needs across the globe and...