CMSC 178DA · Syllabus
Data Analytics
Principles and techniques of data analytics with Philippine context
This syllabus is not final. It is a working outline and will change
before the term settles — the topic sequence below is indicative, and grading,
deadlines and course policies are still being finalised. Anything here may be revised
and announced in class. Do not treat it as the official course document.
Topics by week
| Week | Topic | |
|---|---|---|
| 1 | Introduction to Data Analytics | slides |
| 2 | Probability & Statistical Foundations | slides |
| 3 | Data Wrangling & Cleaning | slides |
| 4 | Exploratory Data Analysis | slides |
| 5 | Data Visualization Principles | slides |
| 6 | Data Storytelling & Dashboards | slides |
| 7 | Regression Analytics | slides |
| 8 | Tree-Based Methods & Ensembles | slides |
| 9 | Clustering & Segmentation | slides |
| 10 | Time Series Analytics | slides |
| 11 | Text Analytics & Ethics | slides |
| 12 | Capstone Presentations | slides |
Labs
| Week | Lab | |
|---|---|---|
| 1 | Python Basics & Data Structures | Colab |
| 2 | Probability & Statistical Testing | Colab |
| 3 | Data Wrangling with Pandas | Colab |
| 4 | Exploratory Data Analysis | Colab |
| 5 | Data Visualization Techniques | Colab |
| 6 | Building Interactive Dashboards | Colab |
| 7 | Regression Analytics | Colab |
| 8 | Tree-Based Models | Colab |
| 9 | Clustering & Segmentation | Colab |
| 10 | Time Series Analysis | Colab |
| 11 | Text Analytics | Colab |
Assessment
Not finalised. The weighting of labs, project and any exams will be confirmed and announced before it affects any submitted work.
Course policies
Attendance, late work, academic integrity and use of AI tools are still being finalised for this term.
Where things live
| Slides & materials | This portal — they stay up all term |
| Lab notebooks | njpinton/cmsc178da-labs |