Data Analytics Option, A.S.

Data Analytics and Artificial Intelligence are changing the face of the world where we live. Analytics is used in society to analyze and provide solutions for a wide scope of problems including customer churn, programming self-driving cars, facial recognition, natural language processing, and predicting crime. The Data Analytics AS degree is designed for students looking to pursue an entry-level job or internship in the field of Analytics. Students will learn the fundamentals of data science through the lens of the R and Python programming languages. Students will learn data gathering, combining, preparation, and presentation with a variety of open source and commercial tools. Students will learn the basic building blocks of analytical modeling and gain an understanding of the analytics life cycle.

* Milestone Courses should be taken in the order shown. This will help you stay on track and graduate on time.

Semester 1

CIT-113 Information Technology Problem Solving Credits: 3 *
MAT-181 Statistics I Credits: 3 *
MAT-197 Precalculus Credits: 4 *
ENG-111 College Writing I Credits: 3 *
GenEd -SR Scientific Reasoning Credits: 4

Total Credits: 17

Semester 1 Advising Note

Equivalent courses for CIT-113 are CIT-110 Applications/Concepts or CSC-120 Intro to Comp Sci & Object Oriented Prog .
There is a hidden prerequisite for MAT-197 (MAT-194 College Algebra for STEM ), but students can place into the course. Students who place into MAT-281 (Calculus I) must replace MAT-197 with an elective.
General Education requirement Quantitative Problem Solving satisfied by program.

Semester 2

CSC-236 SQL Programming Credits: 3 *
CIT-137 Intro to Big Data with R & R-Studio Credits: 4 *
CIT-234 Decision Support Using MS Excel Credits: 3
MAT-281 Calculus I Credits: 4 *
GenEd -CCC Community & Cultural Contexts Credits: 3

Total Credits: 17

Semester 3

CSC-125 Python Programming Credits: 3 *
MAT-291 Linear Algebra Credits: 4
CIT-187 Data Analytics and Predictive Analysis Credits: 3
ENG-112 College Writing II Credits: 3
Elective- Concentration Elective Credits: 3

Concentration Electives:

CSC-240 Database Programming , CIT-268 Operating Systems , CIT-299C Computer Technology Internship

Total Credits: 16

Semester 4

Elective- Concentration Elective Credits: 3

Concentration Electives:

CSC-240 Database Programming , CIT-268 Operating Systems , CIT-299C Computer Technology Internship

CIT-130 Data Visualization Credits: 3
CSC-225 Advanced Python Programming Credits: 3
GenEd -E General Education Elective Credits: 4
Choose one four credit Science/Lab course (see semester four advising note)
GenEd -CW Creative Work Credits: 3

Total Credits: 16

Semester 4 Advising Note

GenEd-E To satisfy MassTransfer STEM program requirements, students are required to earn seven credits in the Natural/Physical Sciences.

Upon Completion of This Concentration Graduates Will Be Able To:

Collect, clean and prepare data from various sources for analysis.
Utilize R and Python computer languages to generate insight from data.
Handle data with an ethically conscious approach and understanding.
Select the correct data visualization to communicate findings and recommendations.
Select appropriate data visualizations to clearly communicate insights to various stakeholders.

Career Outlook

Graduates of this option will be qualified to pursue internships or junior data practitioner jobs in the field of data analytics.

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Transfer Options

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