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School of Health Sciences

Data Analytics

Data Analytics

Data Analytics

The Data Analytics major at Lasell has a professional focus, rooted in Connected Learning, that prepares students to understand data and create actionable insights. Organizations across industries have the increasing need for skilled analysts who can collect, analyze, and produce actionable insights for their teams to generate more revenue, increase customer base, and develop products.


Program Features

The program features many extracurricular opportunities to give students leadership/team experience and portfolio material. These experiences include:

  • The Data Analytics concentration allows students to earn certifications and badges in: Google Analytics and SAS Visual Analytics.
  • Students learn techniques and tools to set-up, retrieve, aggregate, and process large data sets - from a traditional data store to Big Data insights.
  • Learn methods of data analysis and visualization using software to create charts, dashboards and reports.
  • Students will complete a minimum of one industry-relevant internship and will come out of the program ready to create actionable insights.

What You'll Learn

From your first day, you’ll take courses in your major and advance towards graduation with a yearly plan. Not sure what classes to take? We’ll help you create the perfect plan. 

For a complete list of courses and learning outcomes, view the Academic Catalog >>


Accelerated Master's Program

Save time and money — earn your graduate degree in just 1 year with the Accelerated Master's program. Learn more and how to apply >>

Career Success in the Data Analytics Industry

Data Analytics majors learn a broad range of transferable skills and gain strong competence in critical thinking and hands-on experience. There is a wide variety of Connected Learning opportunities for Data Analytics students.

Our students have gone on to have careers as:

  • Citizen Data Scientist
  • Data Analyst
  • Business Analyst
  • Big Data Engineer
  • Data Scientist

 

 

 

 

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DSCI102 - Introduction to Computer Science

This introduction to computer science, emphasizes problem solving and data analysis skills along with computer programming skills. Using Python, students learn design, implementation, testing, and analysis of algorithms and programs. And within the context of programming, they will learn to formulate problems, think creatively about solutions, and express those solutions clearly and accurately. Problems will be chosen from real-world examples such as graphics, image processing, cryptography, data analysis, astronomy, video games, and environmental simulation. Students get instruction from a world-class computer science professor, delivered remotely through video and interactive media and attend class for collaborative team projects to solve real-life problems. Prior programming experience is not a requirement for this course. Formerly: INTC102

DSCI103 - Fundamentals of Information Technology

This course provides students with the fundamental skills and concepts required to maintain, support, and work efficiently with personal computers. It will assist students in preparing for the Digital Transformation. The course is organized around the five important uses of technology in business – IT concepts, Infrastructure, Applications and Software Development, Database fundamentals, and Security and Cloud Computing

DSCI409 - Project & Program Management

This course allows students to develop the competencies and skills for planning and controlling projects and understanding interpersonal issues that drive successful project outcomes. Focusing on the introduction of new products and processes, students will examine the project management life cycle, define project parameters, matrix management challenges, effective project management tools and techniques, and take on the role of a project manager. This course is designed to guide students through the fundamental project management tools and behavioral skills necessary to successfully launch, lead, and realize benefits from projects in both for-profit and non-profit organizations. Prerequisites: Senior Standing and internship.

DSCI499 - Internship Data Science

This is a hand-on experience in a data science work or research setting that offers students an opportunity to apply concepts, theories, and practices learned in the classroom in a supervised setting. Students must successfully complete a minimum of 150 hours of field experience in addition to course assignments. Prerequisite: Permission of Program Chair. Requirement for Cybersecurity and Data Analytics Majors

MATH208 - Statistics

This is an introductory course in descriptive and inferential statistics. Topics include: data analysis, and graphical methods of describing data, measures of central tendency and variability, probability, the normal distribution, sampling distributions, confidence intervals, hypothesis testing, correlation, and regression analysis. Prerequisites: MATH 106 with a grade of C or better or demonstrated competency through placement testing and ENG 102.

MATH215 - Discrete Math

Topics will include elementary logic and set theory, equivalence relations, functions, counting arguments, inductively defined sets, recursion, graphs and trees, Boolean algebra and combinatorial circuits, and countability arguments. Prerequisite: MATH203 with a C or better.

MATH305 - Advanced Statistics

Quantitative statistical tools for modern data analysis are used across a range of disciplines and industries to guide organizational, societal and scientific advances. Using data sets from across a variety of fields, the focus will be on applications and analysis. Topics include two sample confidence intervals, Chi Square tests, multiple regression analysis, ANOVA, non- parametric tests, sampling, and simulation. Prerequisite: Math 208 or Math 209