Course Outline
Introduction to Data Science for Government
The course will begin by defining data science and its significance for government operations. We will explore the data science workflow and how it can be applied to address real-world challenges in public sector governance. The chapter will conclude with strategies for structuring a data team to meet the specific needs of your organization.
Analysis and Visualization for Government
In this chapter, we will discuss methods for exploring and visualizing data through dashboards. We will cover the essential elements of an effective dashboard and how to make targeted requests for dashboard creation. Additionally, we will delve into making ad hoc data requests and A/B testing, which are powerful tools for enhancing decision-making in government.
Data Collection and Storage for Government
With a foundational understanding of the data science workflow, we will now focus on the initial step: data collection. We will explore various data sources available to government agencies and the best practices for storing collected data securely and efficiently.
Prediction for Government
In this final chapter, we will delve into one of the most exciting areas of data science: machine learning. We will cover supervised and unsupervised machine learning techniques, as well as clustering methods. The chapter will also explore specialized topics in machine learning, including time series prediction, natural language processing, deep learning, and explainable AI, all tailored to enhance government operations.
Testimonials (5)
Trainer was accommodative. And actually quite encouraging for me to take up the course.
Grace Goh - DBS Bank Ltd
Course - Python in Data Science
Subject presentation knowledge timing
Aly Saleh - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.
Winnie Chan - Statistics Canada
Course - Jupyter for Data Science Teams
It is showing many methods with pre prepared scripts- very nicely prepared materials & easy to traceback
Kamila Begej - GE Medical Systems Polska Sp. Zoo
Course - Machine Learning – Data science
The example and training material were sufficient and made it easy to understand what you are doing.