Course Outline
Part 1: Python Foundations for Analytics (3.5 Hours)
· Module 1: The Analytics Landscape (45 min)
o Why Python? A comparison of Python, Excel, and SQL in academic research contexts.
o Preparing for success: An introduction to Jupyter Notebooks and Google Colab.
Google Colab offers the advantage of requiring no installation but demands a robust internet connection.
If possible, participants may install Jupyter Notebooks for a smoother user experience.
· Module 2: The Building Blocks of Data (60 min)
o Variables, Data Types (Strings, Integers, Floats), and fundamental logic.
o Exploring Lists and Dictionaries—understanding how Python structures and stores information.
· Module 3: Python for Data Analysis Demo & Lab (75 min)
o Introduction to Pandas: The industry-standard tool for data manipulation.
o Practical application: Loading a CSV file, applying filters, and computing basic statistics.
Part 2: Introductory Business Analytics (2.0 Hours)
· Module 4: The Analytics Mindset: Grasping the "Ask-Analyze-Act" framework to define business questions that data can effectively answer.
· Module 5: Descriptive vs. Predictive: A high-level overview of interpreting trends and identifying anomalies within a financial context.
· Module 6: Communicating Insights: Core principles of data storytelling—transforming technical outputs into actionable executive recommendations.
Requirements
- A foundational understanding of data analytics
- Prior experience in data processing
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
