Course Outline
Part 1: Core Python Competencies for Government Analytics (3.5 Hours)
· Module 1: The Public Sector Analytics Environment (45 min)
o Rationale for Python: A comparative analysis of Python against Excel and SQL within federal research and operations contexts.
o Operational Setup: Orientation to Jupyter Notebooks and Google Colab platforms.
Google Colab offers a zero-installation environment, requiring only a stable internet connection.
Where feasible, local installation of Jupyter Notebooks is recommended to ensure optimal workflow continuity.
· Module 2: Fundamental Data Structures (60 min)
o Core concepts including variables, data types (strings, integers, floats), and logical operators.
o Mechanisms for information storage: Examination of lists and dictionaries in Python.
· Module 3: Applied Data Analysis Demonstration & Exercise (75 min)
o Overview of Pandas: The dominant library for data manipulation in the public sector.
o Practical Application: Ingesting CSV files, applying data filters, and computing baseline statistical metrics.
Part 2: Introductory Business Analytics for Public Administration (2.0 Hours)
· Module 4: The Analytics Approach: Application of the "Inquire-Process-Execute" framework. Methods for defining policy and operational questions addressable through data.
· Module 5: Descriptive vs. Predictive Models: Strategic overview of trend interpretation and anomaly detection in fiscal contexts.
· Module 6: Communicating Insights: Standards for data storytelling—transforming technical results into actionable executive recommendations.
Requirements
- Foundational knowledge of data analytics principles
- Prior experience with data processing workflows
Testimonials (3)
Practice in using python is really helpful to understand the basics.
Wildana Ramadhani - OJK
Course - Foundations of Data & Business Analytics
Good presentation and expert trainers
Khairunnisa Andira - OJK
Course - Foundations of Data & Business Analytics
The technical details
