BS in Data Science with Social Technology Studies Concentration

Program Overview

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The BS in Data Science with Social Technology Studies Concentration at the University of Illinois Chicago combines data science expertise with a critical understanding of social technologies. Students master data analysis, machine learning, and social technology studies, preparing them for careers in data science, social media, communication, and other fields. The program emphasizes critical thinking, communication skills, and ethical considerations in data analysis and interpretation.

Program Outline

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BS in Data Science with Social Technology Studies Concentration at University of Illinois Chicago

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Degree Overview:

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Objectives:

• Master the fundamentals of data science: including data analysis, machine learning, and statistical modeling.
• Gain a deep understanding of social technologies: including their history, evolution, and impact on society.
• Develop critical thinking and communication skills: necessary for analyzing and interpreting complex data and communicating findings effectively.
• Graduate prepared for a variety of careers: in data science, social media, communication, and other fields.

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Outline:

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The program consists of 120 credit hours, divided into the following components:

• General and Basic Education Requirements: 37 hours of coursework in areas such as English, mathematics, social sciences, and humanities.
• Core Courses: 57 hours of data science fundamentals, including programming, algorithms, statistics, machine learning, database systems, and ethics.
• Social Technology Studies Concentration Requirements: 18 hours of coursework exploring the impact of social technologies on society, covering topics like digital media, social media marketing, data journalism, and privacy.
• Free Electives: 8 hours of additional coursework in any subject.

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Sample Course Schedule:

• First Year: Focuses on introductory data science courses, mathematics, and general education requirements.
• Second Year: Dives deeper into data science fundamentals, statistics, and social technology studies courses.
• Third Year: Includes advanced data science courses, electives, and the continuation of social technology studies courses.
• Fourth Year: Culminates with capstone projects, electives, and completion of social technology studies requirements.

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Individual Modules:

• Data Science Fundamentals: Covers programming, algorithms, databases, statistics, machine learning, and data visualization.
• Social Technology Studies: Explores the history, evolution, and impact of social technologies on society, covering topics like digital media, social media marketing, data journalism, and privacy.
• Communication and Ethics: Develops strong communication and ethical reasoning skills essential for responsible data analysis and interpretation.

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Assessment:

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Assessment methods vary depending on the course but may include:

• Exams: Assess students' understanding of key concepts and theories.
• Assignments: Apply data science skills and knowledge to real-world problems.
• Projects: Develop and implement data-driven solutions to address complex challenges.
• Presentations: Communicate findings effectively to a variety of audiences.

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Assessment criteria:

• Accuracy: Ensure that analyses and interpretations are based on sound data and methods.
• Clarity: Present findings in a clear, concise, and well-organized manner.
• Critical thinking: Demonstrate the ability to analyze complex data and draw meaningful conclusions.

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Teaching:

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Teaching methods include:

• Lectures: Provide foundational knowledge and theoretical frameworks.
• Discussions: Facilitate active learning and critical thinking.
• Hands-on labs: Apply data science skills to real-world datasets.
• Guest lectures: Industry experts share insights and practical experiences.

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Faculty:

• **Experienced and highly qualified professors with expertise in data science, social technologies, and related fields.

• **Actively engaged in research and bring real-world experience to the classroom.

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Careers:

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Graduates are prepared for a variety of careers in:

• Data science: Data analyst, data scientist, machine learning engineer.
• Social media: Social media manager, content strategist, digital marketing specialist.
• Communication: Public relations specialist, communication strategist, journalist.
• Other fields: Policy analyst, researcher, consultant.

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Opportunities:

• **Work for leading technology companies, government agencies, non-profit organizations, and research institutions.

• **Pursue further studies in data science, social technologies, or related fields.

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Other:

• **The program offers a unique opportunity to combine technical skills with a critical understanding of social technologies.

• **Students have the opportunity to work on real-world projects and gain practical experience.