Online and On Campus
Data Analytics | BS
Bachelor of Science in Data Science/Analytics (online and on ground)
The major in Data Science/Analytics (BSDS) is a four-year learning experience leading to a Bachelor of Science in Data Science/Analytics. This major is designed to prepare students with the information and skills needed to excel in the rapidly expanding field of data analytics and to enter the data analytics field upon graduation.
Through a combination of theoretical coursework and firsthand practical experience, students will develop proficiency in collecting, organizing, analyzing, and visualizing large datasets. They will learn various statistical and computational techniques to uncover patterns, trends, and insights that can drive data-informed decision-making in various industries and sectors.
The curriculum also emphasizes the ethical and legal considerations associated with data analytics, including privacy, security, and data governance. Students will learn to apply ethical principles and best practices in their data analytics projects and adhere to relevant legal and regulatory frameworks. Anna Maria College students will be encouraged and mentored to seek out internships to gain further practical experience.
The skills gained will be useful to help organizations effectively leverage data and make strategic decisions. This major has an interdisciplinary focus on principles from computer science, statistics, mathematics, as well as business to provide a comprehensive education in data analysis and the interpretation of data. Thus, this program offers students the opportunity to pursue a wide range of careers in business, education, finance, and healthcare.
Anna Maria College students currently enrolled in other existing majors such as sports management, business, health and human services, health administration, health science, criminal justice, and those within the liberal studies, social science, and psychology majors, might look to the minor in data analytics to enhance their competitive edge in the job market.
The coursework in a BS in Data Analytics program typically covers a wide range of topics, including:
- Statistics and Probability
- Data Mining and Machine Learning
- Database Management
- Data Visualization
- Business Intelligence and Analytics
- Ethical and Legal Aspects
CSC 1 – Internet History, Technology, and Security
To thrive in today’s digital world, you need to understand the system that powers it. This course, built in collaboration with Google, will explore the internet and show you how it works.
CSC II – Programming for Everyone I
This course, built in collaboration with Google, provides a gentle, but thorough, introduction to programming using Python.
CSC III – Programming for Everyone II
This course, built in collaboration with Google, follows on from Programming for Everyone I. In the first half of the course, you will learn how to leverage your Python skills to treat the internet as a source of data.
CSM 1II – Programming for Everyone II
This course, built in collaboration with Google, will teach you how to understand and use data structures.
CSM IV – Algorithms
This course explores algorithms from a coding-focused perspective, using Python. Students will learn about the issues that arise in the design of algorithms for solving computational problems and will explore a number of standard algorithm design paradigms and their applicability.
DAM – Foundations of Data Analytics I
In an increasingly data-driven world, everyone should be able to understand the numbers that govern our lives.
DAM II – Foundations of Data Analytics II
This course is intended as a continuation of Foundations of Data Analytics I. In this course, you’ll learn how Data Analytics is applied within the workforce.
DAM III – Principles and Techniques of Data Analytics I
This course is based heavily on UC Berkeley’s Data 100 class. Data Analytics combines data, computation and inferential thinking to solve challenging problems and understand their intricacies.
DAM IV – Principles and Techniques of Data Analytics I
This course builds on Principles and Techniques of Data Analytics I to provide students with a more robust understanding of the tools of a Data Scientist.
DAM V – Data Analytics Practicum
This course is a capstone project in which students are asked to work through a full data science workflow on a set of real data drawn from sports, politics, business or public health.
Course Of Study
- Operations Research Analyst
- Data Scientist
- IT/Computer Programmer
- Data collection/Data mining
- Predictive analytics
- Customer loyalty and selection programs
- Marketing strategy development
- Fraud detection
- Applied statistics
- Quality assurance
- Supply chain management
- Collect, clean/process, and transform data
- Analyze and interpret it in a way that is morally responsible
- Apply the right models of analysis, evaluate the quality of the input, draw conclusions from the findings, and look into any potential problems.
- Use the ideas of optimization, mathematical and statistical models, programming languages, and computing theory to properly create and use data analysis.
- Create and apply relevant models for data analysis to find hidden solutions to problems in the corporate world.
- Work well in a team – Effectively communicate data findings to any audience in written, oral, and graphic forms