Business Analytics - Business Analytics II - Phyton 101
Dates: 19 October 2018 (8.30am - 1.00pm)
Venue: Securities Commission Malaysia
Accreditation: SIDC CPE-approved: 10 CPE points
Python is a general-purpose programming language that is becoming one of the common tools used in data science applications. Python in the capital market industry has been used for quantitative and qualitative analysis. Activities such as stock market analysis, predictions, deep learning and machine learning have been done using Python. Python programming can be used to acquire, organize, proces, and analyse large amounts of data and use basic statistics concepts to identify trends and patterns and solve computing challenges. There are multinational companies that use Python to gather insights from data to gain a competitive edge. They includes tech giants like Google, Instagram, Pinterest, Yahoo!, Disney, IBM and Nokia.
This programme will explain how and why Python is being used in capital market industry applications. It will also discuss the basic mechanics behind Python programming
Upon completion of this programme, participants will be able to:
- Describe the basics of python
- Explain the use cases of python
- Determine the benefits of machine learning algorithms
- Discuss python in finance and the capital market
Interactive presentations, Discussions and Question-and-Answer (Q&A) sessions
- What is Python?
- Key Advantages
- Multiple Uses of Python
- What are Machine Learning Algorithms?
- Python in Finance and Business Analytics – Case Examples
- How to Code In Python for Capital Market Applications?
||Functional (Technical Skills) - Digital Technology Application
Behavioural (Self-Management) – Analytical Thinking
||What is Phyton?
- Phyton Basics
- Expressions and variables
- String operations
- Key advantages
||Multiple Uses of Python
What are Machine Learning Algorithms?
- Trading infrastructure
- Securitisation and structuring
- Risk monitoring systems
- Stock market data analysis
- Artificial intelligence (AI)
- Primary aim
- Machine learning methods i.e. supervised machine learning algorithms
||Python in Finance and Business Analytics:
How to Code In Python for Capital Market Applications?
- Getting stock price data
- Predicting stock prices
- Case Examples
||End of Programme