SDEV 122 - Data Analytics Technologies

Credits: 5
A continuation of SDEV 121 . Students learn about emerging technologies and their applications through hands-on Python programming and case studies of artificial intelligence, big data, and cloud computing.

Prerequisite: SDEV 121  with a grade of 2.0 or higher.

Course Outcomes:
Students who successfully complete this class will be able to:

1. Recall the six stages of the data processing cycle.
2. Write a Python program that reads and processes large real-world data sets from files and/or databases.
3. Create and use a custom class in Python.
4. Use data science class libraries to support data analysis activities such as data acquisition, processing, visualization.
5. Define terms and concepts relating to contemporary data science technologies such as artificial intelligence, big data, and cloud computing.
6. Recognize broader impacts and issues relating to data analytics such as privacy, security, ethics, and transparency.

1. Solve data-related problems using a programming language.
2. Demonstrate the ability to acquire, clean, and prepare data for analysis.
3. Perform basic data analysis techniques such as filtering, aggregation, and joins.
4. Produce and interpret data visualizations to describe, explore, and communicate insights from data.

 

College-wide Outcomes

• Quantitative and Symbolic Reasoning - Quantitative Reasoning encompasses abilities necessary for a student to become literate in today’s technological world. Quantitative reasoning begins with basic skills and extends to problem solving.