Data Analytics

Certificate Degree
Associate Degree

Certificate Program
Division of Arts, Sciences and Professional Studies

Trocaire’s Fundamentals of Data Analytics Certificate program students are given a foundation of data science curriculum to prepare them for roles that allow them to identify, analyze, and interpret of volumes of data that are collected from a wide variety of sources. Graduates of the program are prepared to resolve business questions and make data-driven decisions, and effectively communicate informed tactical and strategic business objectives. Careers include data analyst, database administrators, and statistical assistants.

Location:
Most courses and labs are offered at the college’s Extension Center at Transit Road, Lancaster, NY. Students must take the GS100 (College Seminar) course at the college’s main campus in Buffalo, NY

The Fundamentals of Data Analytics Certificate provides students with a basis of course work to analyze data in multiple settings with courses in data mining, statistics and SQL.

Program Format
Time of Program: Evening / Weekends
Mode of Delivery: On-site, seated
Normal Time to Completion: 12 months (one academic year)

AAS Associate Program
Division of Arts, Sciences and Professional Studies

Trocaire’s Data Analytics A.A.S. degree program prepares graduates to assume entry and midlevel management roles that oversee the identification, analysis, and interpretation of volumes of data that are collected from a wide variety of sources. Graduates of the program are prepared to identify patterns and relationships in large data sets, to resolve business questions and make data-driven decisions, and effectively communicate informed tactical and strategic business objectives. Careers include data analyst, data scientist, database administrators, and statistical assistants.

Location
Most courses and labs are offered at the college’s Extension Center at Transit Road, Lancaster, NY. Students must take the GS100 (College Seminar) course at the college’s main campus in Buffalo, NY

The AAS in Data Analytics provides students with the tools to understand big data and to enter into the rapidly growing industry of Big Data Analytics. While in the program, students will be given the foundational tools to help and organizations use the power of analytics to become more innovative and profitable. Coursework in this program focuses on the manipulation of large data sets to uncover hidden patterns, data visualization to problem solve and statistical and research methods for strategic business intelligence.

Program Format
Time of Program: Evening / Weekends
Mode of Delivery: On-site, seated
Normal Time to Completion: 24 months (two academic years)

Resources

Data Analytics-AAS Program Learning Outcomes
Applied Analytics – Certificate Program Learning Outcomes
Data Analytics-Certificate- Program Learning Outcomes

Program Requirements

Admission Requirements

High school diploma (minimum 75% average) or GED Diploma with a minimum score of 2500

Minimum Degree Requirements:

A total of at least 61 semester credit hours with a Quality Point Average of 2.0

General Education

Basic Communications: EN101(3) – English Composition GS100* (1)** – College Seminar Humanities: PH107 (3) – Logical Reasoning and Decision Making PH215 (3) – Logic PH2XX (3) – Ethics in Data Science Natural Sciences: Biology Elective (3) Quantitative Analysis: MA120 (3) – Statistics I Social Sciences: PSY101 (3) – General Psychology PSY320 (3) – Research Methods: Techniques and Designs

Program Specific*

BU300 (3) Project Management
DA101 (3) Introduction to Data Science
DA102 (3) Data Analysis
DA103 (3) SQL for Data Analysis
DA104 (3) Data Mining
DA105 (3) Big Data Architecture
DA106 (3) Problem-Solving, Decision-Making and Computer Applications In Business
DA200 (3) Statistical Methods in Data Science
DA201 (3) Data Analysis with R
DA202 (3) Data Visualization and Business Intelligence
DA203 (3) Advanced Data Visualization
DA204 (3) Capstone Experience in Data Science

Graduation Requirements:

Mercy Action Project

Other

* A minimum grade of “C” (2.0) is required. ** GS100 (College Seminar) must be taken at the main campus only.

Courses

Semester 1

16/18

DA 101

Introduction to Data Science

3

DA 102

Data Analysis

3

DA 103

SQL for Data Analysis

3

GS 100

College Seminar*

1

The College Seminar is a course designed to provide students strategies for successful learning in college and beyond. Topics in the course include: learning styles, learning and study strategies, cognitive strategies, time management, goal-setting, note-taking, test-taking strategies, overcoming test anxiety, cultural diversity, and other issues that focus on enabling students to become better achievers.

The course is one credit with a one hour laboratory. Students are requires to take this course in their first semester at Trocaire College. (Fall, Spring and Summer Semester)

*Students must receive a grade of “C” (2.0) or higher to pass this course.

OR

GS 102

College Success*

3

The College Success is a course designed to provide students strategies for successful learning in college and beyond. It is part of the Transitional Studies curriculum. Central to the course is students’ intensive work in learning strategies and the use of the diagnostic tool, Learning and Study Strategies Inventory (LASSI). Topics in the course include: learning styles, learning and study strategies, cognitive strategies, time management, goal-setting, note-taking, test-taking strategies, overcoming test anxiety, cultural diversity, and other issues that focus on enabling students to become better achievers.

This course is three credits and is open only to new Trocaire students who participate in Transitional Studies. They are required to take this course their first semester at Trocaire College. (Fall and Spring Semesters)

*Placement is based on participation in Transitional Studies
*Students must receive a grade of “C” (2.0) or higher to pass this course.

MA 120

Statistics I

3

An introduction to Statistics with modern applications to Sociology, Business, Economics, Ecology, Health Science and Psychology. Topics include: descriptive statistics, central tendency, percentile rank, Z-Scores, probability, probability distribution, correlation and regression analysis. (Fall and Spring Semesters)

MA 107

Logical Reasoning and Decision Making

3

This course introduces students to both informal and formal logic; and students will use the developed logic to evaluate decisions for given situations. Topics include: informal logical games, logical fallacies, truth tables, logical equivalence, sentential logic with proofs, categorical logic, probability, expected value, and decision making. (This course is cross listed in Philosophy PH107-credit will not be granted for both PH107 and MA107)
Semester 2

15

DA 105

Big Data Architecture

3

DA 106

Problem Solving, Decision Making and Computer Applications in Business

3

DA 200

Statistical Methods in Data Science

3

PH 215

Logic

3

An introductory course to the science of logic and the principles of deductive reasoning, correct thinking and valid argumentation. Special emphasis will be placed on the traditional Aristotelian syllogism.

PSY 101

General Psychology

3

An introduction to the basic concepts, research methods and applications of psychology. The major theoretical perspectives are presented through such areas as sensation, perception, intelligence, cognition, personality, and abnormal behavior. The course requires a research paper. (Fall, Spring and Summer Semesters)
Semester 3

15

BU 300

Project Management

3

This course covers essential concepts and framework of project management. The tools and methodologies will be introduced to help with the project execution and achievement of strategic organizational goals.

DA 104

Data Mining

3

DA 202

Data Visualization and Business Intelligence

3

PH 206

Ethics in Data Science

3

BIOEL

Biology Elective

3
Semester 4

15

GS 320

Research Methods and Designs

3

This course provides students with an introduction to research methodologies from an interdisciplinary approach. Students will learn how to develop productive research questions while introducing them to the practical and ethical issues involved in a variety of research methodologies. The course also introduces students to useful strategies for searching for and evaluating relevant primary and secondary source materials in the library and online. Students develop a well-informed, rigorous, and realistic interdisciplinary research plan grounded in knowledge from their individual disciples.

DA 201

Data Analysis with R

3

DA 203

Advanced Data Visualization

3

DA 204

Capstone Experience in Data Science

3

EN 101

English Composition

3

The course seeks to aid the communication process by developing the ability to write clear, concise, expository prose, with emphasis on pre-writing and revision. It assists the student in finding a voice and an audience. A research paper is required, thus techniques of writing a formal research paper are reviewed. (Fall, Spring and Summer Semesters)