Data Analytics with Python and Generative AI (Module 2)
About This Course
In today's data-driven world, the ability to analyse, interpret and leverage large datasets is becoming increasingly important across all industries and job functions. At the same time, Generative AI is transforming the way executives perform their data analytics tasks.
This course is Module 2 of the Data Analytics with Python and Generative AI programme offered by Nanyang Business School. It is specially designed to equip both analysts and managers with the essential skills to analyse data effectively and make data-driven decisions that improve business results and insights.
Consisting of 2 modules of 3 days each, this practical programme introduces the key data analytics tools and techniques as well as the use of Generative AI to enhance participants’ learning of Python and execution of various data analytics tasks. This comprehensive hands-on workshop emphasizes real-world applications of data analytics, enabling participants to hone their skills for tasks such as statistical modelling, time series modelling, text analysis, clustering and data visualisation. The datasets and discussions focus primarily on marketing, finance, insurance, healthcare and customer behaviour, to help participants solve relevant business problems.
Course Objectives/Learning Outcomes
Upon completion of both modules, participants will:
1. Gain proficiency in Python: Learn to use Python for data analysis and visualization tasks relevant to various industries.
2. Understand data wrangling techniques: Acquire skills in handling, cleaning, and preparing datasets for analysis.
3. Use of Generative AI: Leverage Generative AI to enhance learning, assist in coding and perform data analytics tasks.
4. Visualize and communicate data insights: Learn to effectively present data insights through visualization techniques, supporting data-driven decision-making.
5. Perform analysis with data: Apply various analytics techniques to real-world data to solve practical challenges
What You'll Learn
Day 4: Introduction to Text Analytics and Statistical Modelling
• Introduction to Text Analytics
o Overview of text analytics – Word Cloud, Sentiment Analysis
o Enhancing text analytics with Generative AI – Text Summary, Translation
• Statistical Modelling
o Apply statistical tests (A/B testing, t-tests)
o Apply Multivariate Linear Regression for predictive analysis
• Hands-on Session: Text Analytics and Statistical Modelling
Day 5: Time Series Analysis and Clustering
• Time Series Analysis
o Data Preparation for Time Series Data
o Perform Time Series decomposition, Exponential Smoothing and fit ARIMA models
• Hands-on Session: Times Series Analysis
o Apply time series analysis to a practical dataset.
• Clustering
o Data Preparation for K-Means Clustering
o Perform K-Means clustering and post-clustering analysis
• Assignment
Day 6: Assignment Presentation, AI Governance
• Assignment Presentation
• Data and AI Governance
o Overview of PDPA regulations, MAS FEAT Principles and IMDA frameworks for AI Governance
Entry Requirements
This course is suitable for:
• Analysts in marketing and finance, underwriters, risk managers and professionals who want to leverage data analytics and AI in their roles.
• Managers from various sectors who want a better understanding of how data analytics and Generative AI can transform their business practices.
While prior knowledge of Python is not required, some basic understanding of programming and/or data analytics will be a strong advantage.