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Main
UQU Programs
Data Science

Advanced Programming for Data Science

DS1103
3 hours English

Advanced Programming for Data Science

Advanced Programming for DS
1 Python Language Basics, IPython, and Jupyter Notebooks
2 Built-In Data Structures, Functions, and Files
3 NumPy Basics
4 Getting Started with Pandas
5 Data Loading, Storage, and File Formats in Python
6 Data Cleaning and Preparation in Python
7 Basics of Data Wrangling in Python
8 Data Aggregation and Group Operations in Python
9 Course Review and Project Development
10 Final Porject Presentations
11 Review, quizzes and midterm
1.1 Mapped to: K2

Understand the fundamentals of Python programming for data science applications.

Teaching Strategy Lectures, Lab
Assessment Methods Exams, Project, Lab
1.2 Mapped to: K3

Identify and apply libraries for data analysis (e.g., Pandas and NumPy).

Teaching Strategy Lectures, Lab
Assessment Methods Exams, Project, Lab
1.3 Mapped to: K1

Understand the process of handling datasets, including loading, cleaning, and preprocessing data.

Teaching Strategy Lectures, Lab
Assessment Methods Exams, Project, Lab
2.1 Mapped to: S2

Write Python programs to solve data-driven problems.

Teaching Strategy Lectures, Lab
Assessment Methods Exams, Project, Lab
2.2 Mapped to: S4

Utlilize data science libraries for manipulating large datasets.

Teaching Strategy Lectures, Lab
Assessment Methods Exams, Project, Lab
3.1 Mapped to: V2

Demonstrating integrity and accountability when working with data.

Teaching Strategy Lab, Project
Assessment Methods Lab, Project
3.2 Mapped to: V3

Collaborating with peers to solve programming challenges.

Teaching Strategy Lab, Project
Assessment Methods Lab, Project
Assessment
Weight
Quizzes
20%
Midterm Exam
20%
Lab Participation
5%
Final Lab Project
15%
Final Exam
40%
Total
100%