Florida Department of Education
Curriculum Framework 

Program Title:	FinTech Technician 
Career Cluster:	Information Technology

CCC	
CIP Number	0530710400	
Program Type	College Credit Certificate (CCC)	
Program Length	33 credit hours 	
CTSO	BPA	
SOC Codes (all applicable) 	Please see the CIP to SOC Crosswalk at the link below.	
CTE Program Resources 	http://www.fldoe.org/academics/career-adult-edu/career-tech-edu/program-resources.stml	

Purpose

This certificate program is part of the Data Science Technology AS degree program (1530700100).  

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 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 foundational instruction on activities performed in the development of applications and acquisition and analysis of data related to finance and banking technology. The program is designed to meet industry demand for students with students with advanced technical skills required by emerging FinTech-related occupations. This program is designed to emphasize the use of application programming interfaces (APIs) for accessing, manipulating, and analyzing financial data.

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

Standards

After successfully completing this program, the student will have demonstrated mastery the following student learning outcomes:

01.0	Describe the data life cycle.
02.0	Describe selection, preprocessing, and transformation processes used with data sources.
03.0	Describe modeling, analysis, and visualization techniques applied to acquired data.
04.0	Describe security best practices for each phase of acquisition, analysis, and retention of data.

Florida Department of Education
Student Performance Standards
Program Title:	FinTech Technician
CIP Number:		0530710400
Program Length:	33 credit hours
		
This certificate program is part of the Data Science Technology AS degree program (1530700100).  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:	
•	Describe data sources and methods for acquiring data. 	
•	Describe how data is captured (e.g., from control systems devices or Internet of things devices, etc.).	
•	Describe how acquired data is cleansed and enriched.	
01.02	Describe techniques for analyzing data: 	
•	Describe data models.	
•	Describe techniques used for data visualization.	
•	Describe statistical methods which are applied to data to extract useful information.	
01.03	Describe how data analysis results can be reported.	
•	Describe dashboards and how they can be used to make business decisions.	
•	Determine appropriate reporting formats	
02.0	Describe selection, collection, preprocessing, and transformation processes used with data sources.  The student will be able to:	
02.01	Describe criteria and procedures used for data selection.	
02.02	Compare attributes and benefits of data sources and associated collection strategies including:	
•	Structured and unstructured data.	
•	RDBMS (Relational Database Management Systems).	
•	Data warehouses and OLAP (Online Analytical Processing) Cubes.	
•	Spreadsheets.	
•	XML (eXtensible Markup Language) data.	
•	CSV (Comma Separated Values) data.	
•	Web data.	
•	GIS (Geographical Information Systems) data.	
•	Raw data.	
02.03	Describe and utilize data preprocessing and normalization.	
•	Describe and apply common techniques for cleaning textual, numeric, and categorical data.	
•	Describe the use and applicability of transformations used to normalize data distributions.	
02.04	Describe OLTP (Online Transaction Processing) design concepts and principals.	
02.05	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.	
02.06	Collect and transform financial data from the web using a Restful API.	
03.0	Describe modelling, analysis, and visualization techniques applied to acquired data. The student will be able to:	
03.01	Use statistical tools (e.g., SAS, SPSS, etc.) or programming languages (e.g., R, Python, etc. with associated libraries) to solve various statistical problems:	
•	Calculate summary statistics.	
•	Calculate correlation values.	
•	Construct confidence intervals from sample data.	
•	Construct confidence intervals from sample data.	
•	Conduct tests of hypotheses with one and two samples.	
•	Use correlation and linear regression methods to analyze data.	
03.02	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.	
04.0	Describe security best practices for each phase of acquisition, analysis, and retention of data.  The student will be able to:	
04.01	Demonstrate understanding of basic security principles including general security concepts, communication security, confidentiality, authentication and other cryptography concepts, and operational and organizational security.	
04.02	Describe risks associated with data privacy and integrity.	
04.03	Describe basic web security.	
04.04	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 the co-curricular 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.