The learning outcomes of Python Programming For Finance is understanding the basics of Python programming and how to use it for financial tasks. Participants will be able to work with financial data using Python libraries such as Pandas and NumPy. Python Programming For Finance also teaches visualizing financial data and results using Python libraries such as Matplotlib and Seaborn.
Python Programming is also useful for developing micro-projects to large-scale enterprise online services, as well as supporting other programming languages.
Despite the fact that it is a high-level language capable of doing difficult tasks, Python is simple to learn and has a clean syntax. As a result, it is suitable for both beginner and experienced programmers.
Training Duration: 5 Days
Minimum private group training class: 5 Participants
- Certificate Of Completion Available
- Group Private Class
- VILT Class Available
- SBL-Khas Claimable
Related training:
- Python Essentials
- Python Programming
- Data Science With Python
- PTN-107: Artificial Intelligence, Data Science and Machine Learning with Python
For Technical Finance:
For more details, may check out the entire series and blogs at Learn Python with GemRain. Learn Python Programming today. Chat us up!
In the past decade, the demand for data has increased exponentially. The industry has begun to realise the potential goldmine of summarised information collected online. The various processes in data science are collect, collate and disseminate.
The industry is also investigating on various applications that can streamline the valuable information for analytics processes and making the data collection simple and efficient. The industry is expected to be worth over $128 billion by 2022, a predicted 36 per cent growth from 2016. With the Data Analytics Industry becoming dynamic, the prospects for someone looking to make Data Science as their career are high.
Although the amount of collected data is impressive, the data is useless without it is being analysed and insights leading transformation. Without enough manpower to work out on the information, it is pointless collecting the data in the first place.Businesses are also starting to react to the data scientist shortage and are collaborating with other firms and educational establishments to close the gap before it becomes too large.
Through this Python course, we have focused on the practical challenges that organisations are experiencing by merging disciplines to develop a teaching programme that makes the link between business, management and data analytics.
This Python Programming training course includes the fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as group by, merge, and pivot tables effectively. By the end of this course, participants will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.