Introduction to Data Science
Introduction to Data Science
Course Information
Institution: Regis University, Denver, CO
Department: Marketing and Data Science
Level: Graduate
Prerequisites: None
Course Description
This course is designed to give students a comprehensive understanding of the data science field, its various applications, and its ethical implications. Students will acquire foundational statistical analysis and machine learning skills through engaging practical exercises and projects, ensuring that the knowledge gained is directly applicable. By the end of this course, learners will be proficient in data science tools to create recommender systems and tackle data science challenges effectively.
Learning Outcomes
Upon successful completion of this course, students will be able to:
- Articulate the scope and applications of data science as an emerging field
- Understand the data science project lifecycle and roles of data scientists
- Characterize Big Data using volume, variety, and velocity principles
- Address ethical concerns in data collection and analysis
- Apply statistical and machine learning techniques for data modeling
- Implement recommender systems using modern data science frameworks
- Create data-driven solutions for real-world challenges
Course Outline
| Week | Topic |
|---|---|
| 1 | Introduction to Data Science and EDA |
| 2 | Cleaning and Preparing Data |
| 3 | Machine Learning (ML) |
| 4 | Decision Tree Machine Learning (ML) and Feature Selection |
| 5 | Data Science Automation |
| 6 | Recommender Systems, Big Data, and Graph Analysis |
| 7 | Collecting Social Media Data |
| 8 | Analyzing Social Media Data |