2021 – 2022
Florida Department of Education
Curriculum Framework 

Program Title:	Data Science Technology
Career Cluster:	Information Technology

AS	
CIP Number	1530700100	
Program Type	College Credit	
Standard Length	60 credit hours	
CTSO	Business Professionals of America (BPA)	
SOC Codes (all applicable) 	15-1199 – Computer Occupations, All Others	
CTE Program Resources 	http://www.fldoe.org/academics/career-adult-edu/career-tech-edu/program-resources.stml	

Purpose

This program offers a sequence of courses that provides coherent and rigorous content aligned with challenging academic standards and relevant technical knowledge and skills needed to prepare for further education and careers in the Information Technology career cluster; provides technical skill proficiency, and includes competency-based applied learning that contributes to the academic knowledge, higher-order reasoning and problem-solving skills, work attitudes, general employability skills, technical skills, and occupation-specific skills, and knowledge of all aspects of the Information Technology career cluster.

The content includes but is not limited to in-depth instruction on activities performed in the acquisition of data in structured and unstructured formats, cleaning, modeling, and analysis of acquired data, and extraction of knowledge or insights using statistical processes and systems. Additional content includes identification of data sources, retrieval issues and methodologies, data security, and the use of other informational tools.

Additional Information relevant to this Career and Technical Education (CTE) program is provided at the end of this document.

Program Structure

This program is a planned sequence of instruction consisting of 60 credit hours.

Standards

After successfully completing this program, the student will be able to perform the following:

01.0	Describe the data life cycle.
02.0	Describe basic statistical concepts and apply statistical methods used in data science problems.
03.0	Describe selection, preprocessing, and transformation processes used with data sources.
04.0	Describe modelling, analysis, and visualization techniques applied to acquired data.
05.0	Describe security best practices for each phase of acquisition, analysis, and retention of data.
06.0	

2021 – 2022
Florida Department of Education
Student Performance Standards

Program Title:	Data Science Technology
CIP Number:		1530700100
Program Length:	60 credit hours
SOC Code(s):		15-1199

The AS degree requires the inclusion of a minimum of 15 credits of general education coursework according to SACS, and it must be transferable according to Rule 6A-14.030 (2), F.A.C.  At the completion of this program, the student will be able to:	
01.0	Describe the data life cycle.  The student will be able to:	
01.01	Describe ways in which data can be acquired:	
01.01.1	Describe data sources and methods for acquiring data. 	
01.01.2	Describe how data is captured (i.e., from control systems devices or Internet of things devices, etc.).	
01.01.3	Describe how acquired data is cleansed and enriched.	
01.02	Describe techniques for analyzing data: 	
01.02.1	Describe data models.	
01.02.2	Describe techniques used for data visualization.	
01.02.3	Describe statistical methods which are applied to data to extract useful information.	
01.03	Describe how data analysis results can be reported.	
01.03.1	Describe dashboards and how they can be used to make business decisions.	
01.03.2	Determine appropriate reporting formats.	
02.0	
Describe basic statistical concepts and apply statistical methods used in data science problems.  The student will be able to:	
02.01	Describe the difference between population and sample data.	
02.02	Construct frequency distributions.	
02.03	Use descriptive statistical methods to analyze sets of data.	
02.04	Use probability rules to solve probability problems.	
02.05	Solve problems involving discrete probability distributions including the binomial probability distribution.	
02.06	Construct confidence intervals from sample data.	
02.07	Conduct tests of hypotheses with one and two samples.	
02.08	Use correlation and linear regression methods to analyze data.	
03.0	Describe selection, collection, preprocessing, and transformation processes used with data sources.  The student will be able to:	
03.01	Describe criteria and procedures used for data selection.	
03.02	Compare attributes and benefits of data sources and associated collection strategies including:	
03.02.1	Structured and unstructured data.	
03.02.2	RDBMS (Relational Database Management Systems).	
03.02.3	Data warehouses and OLAP (Online Analytical Processing) Cubes.	
03.02.4	Spreadsheets.	
03.02.5	XML (eXtensible Markup Language) data.	
03.02.6	CSV (Comma Separated Values) data.	
03.02.7	Web data.	
03.02.8	GIS (Geographical Information Systems) data.	
03.02.9	Raw data.	
03.03	Describe and utilize data preprocessing and normalization:	
03.03.1	Describe and apply common techniques for cleaning textual, numeric, and categorical data.	
03.03.2	Describe the use of probabilistic methods and decision trees for classification.	
03.03.3	Describe the use and applicability of transformations used to normalize data distributions.	
03.04	Describe OLTP (Online Transaction Processing) design concepts and principals.	
03.05	Use data processing tools (e.g. SAS, PowerBI, Tableau, etc.) or programming languages (e.g. Python, R, Java, etc. and associated libraries) to collect and clean data from various sources.	
03.06	Create a data warehouse:	
03.06.1	Design an OLAP database using dimensional modeling techniques.	
03.06.2	Create a data warehouse based on OLAP design.	
03.06.3	Create an ETL (Extract/Transfer/Load) process to populate and update the data warehouse from OLTP database utilizing SQL Server Integration (SSIS).	
04.0	Describe modelling, analysis, and visualization techniques applied to acquired data.  The student will be able to:	
04.01	Describe and apply the use of linear regression and decision trees in data modeling.	
04.02	Develop data cubes utilizing SQL Server Reporting Services (SSRS).	
04.03	Use statistical tools (e.g.: SAS, SPSS, etc.) or programming languages (e.g.: R, Python, etc. with associated libraries ) to solve various statistical problems:	
04.03.1	Calculate summary statistics.	
04.03.2	Calculate correlation values.	
04.03.3	Construct confidence intervals from sample data.	
04.03.4	Construct confidence intervals from sample data.	
04.03.5	Conduct tests of hypotheses with one and two samples.	
04.03.6	Use correlation and linear regression methods to analyze data.	
04.04	Describe the advantages of large-scale data analysis tools (e.g., Apache Hadoop, Apache Spark, Google BigQuery, Data Torrent RTS, etc.) for solving data science problems.	
04.05	Use data visualization tools (e.g.Tableau, PowerBI, SAS, etc.) or programming languages (e.g., R, JavaScript, Python, Java, etc. with associated libraries) to create graphical representations of data models and analysis results.	
04.06	Develop dashboards utilizing reporting tools (e.g., SharePoint, Tableau, PowerBI, etc.).	
05.0	Describe security best practices for each phase of acquisition, analysis, and retention of data.  The student will be able to:	
05.01	Demonstrate understanding of basic security principles including general security concepts, communication security, confidentiality, authentication and other cryptography concepts, and operational and organizational security.	
05.02	Describe risks associated with data privacy and integrity.	
05.03	Describe basic web security.	
05.04	Describe security methodologies as they relate to data protection and availability.	

Additional Information

Laboratory Activities

Laboratory investigations that include scientific inquiry, research, measurement, problem solving, emerging technologies, tools and equipment, as well as, experimental, quality, and safety procedures are an integral part of this career and technical program/course. Laboratory investigations benefit all students by developing an understanding of the complexity and ambiguity of empirical work, as well as the skills required to manage, operate, calibrate and troubleshoot equipment/tools used to make observations. Students understand measurement error; and have the skills to aggregate, interpret, and present the resulting data. Equipment and supplies should be provided to enhance hands-on experiences for students.

Career and Technical Student Organization (CTSO)

Business Professionals of America (BPA) is an intercurricular career and technical student organization providing leadership training and reinforcing specific career and technical skills.  Career and Technical Student Organizations provide activities for students as an integral part of the instruction offered.  

Accommodations

Federal and state legislation requires the provision of accommodations for students with disabilities to meet individual needs and ensure equal access. Postsecondary students with disabilities must self-identify, present documentation, request accommodations if needed, and develop a plan with their counselor and/or instructors. Accommodations received in postsecondary education may differ from those received in secondary education. Accommodations change the way the student is instructed. Students with disabilities may need accommodations in such areas as instructional methods and materials, assignments and assessments, time demands and schedules, learning environment, assistive technology and special communication systems. Documentation of the accommodations requested and provided should be maintained in a confidential file.

Certificate Programs

A College Credit Certificate consists of a program of instruction of less than sixty (60) credits of college-level courses, which is part of an AS or AAS degree program and prepares students for entry into employment (Rule 6A-14.030, F.A.C.).  This AS degree program includes the following College Credit Certificates:

No certificates included.

Standards for the above certificate programs are contained in separate curriculum frameworks.

Additional Resources

For additional information regarding articulation agreements, Bright Futures Scholarships, Fine Arts/Practical Arts Credit and Equivalent Mathematics and Equally Rigorous Science Courses please refer to:
http://www.fldoe.org/academics/career-adult-edu/career-tech-edu/program-resources.stml