The FutureReadyNYC Technology pathway aspires to create robust technology-career-focused instructional tools and support to enable NYC high schools to meet the ambitions of their students, regardless of life experiences, identities, or perceptions of self. As technology continues to evolve rapidly, this pathway equips students not only with essential technical skills, but also with the professional skills needed to thrive in a dynamic workforce that is currently being augmented by Artificial Intelligence. Students will leave the technology pathway with the knowledge, confidence, and a portfolio of work they can showcase in college or job applications—positioning them for success in technology-related careers or higher education.
Each occupational title introduces students to a four-part course sequence:
Software Developer
The Software Developer occupational title begins with introducing students with how technology integrates itself across industries. Students then learn about programming languages such as JavaScript, HTML, CSS, and web-based application development tools. Over the course of this 4-year sequence, students will learn and develop their coding and foundational computer science knowledge to bridge the gap between technical skills and creative applications following an ethical approach to software development.
Course 1: Introduction to Computer Science
Introduction to Computer Science is a course intended to provide students with exposure to various technology occupations and pathways such as Cybersecurity, Data Science, and Software Development as well as initial experiences with learning foundational computer science concepts. Upon completion of this course, proficient students will be able to describe various technology occupations and professional organizations. Moreover, they will be able to demonstrate logical thought processes and discuss the social, legal, and ethical issues encountered in tech professions.
Course 2: Computer Programming I
Computer Programming is a course intended to continue building student understanding of foundational computer science concepts with a focus on programming. The course places emphasis on practicing and refining standard programming techniques and learning the logic tools and methods typically used by programmers to create simple computer applications. Upon completion of this course, proficient students will be able to solve problems by planning multi step procedures; write, analyze, review, and revise programs, converting detailed information from workflow charts and diagrams into coded instructions in a computer language; and will be able to troubleshoot/debug programs and software applications to correct malfunctions and ensure their proper execution.
Course 3: Computer Programming II <OR> AP Computer Science Principles
Computer Programming II challenges students to develop advanced skills in problem analysis, construction of algorithms, and computer implementation of algorithms as they work on programming projects of increased complexity. In so doing, they develop key skills of discernment and judgment as they must choose from among many languages, development environments, and strategies for the program life cycle. Course content is reinforced through numerous short- and long-term programming projects, accomplished both individually and in small groups. These projects are meant to hone the discipline and logical thinking skills necessary to craft error-free syntax for the writing and testing of programs.
AP Computer Science Principles is an introductory college-level computing course that introduces students to the breadth of the field of computer science. Students learn to design and evaluate solutions and to apply computer science to solve problems through the development of algorithms and programs.They incorporate abstraction into programs and use data to discover new knowledge. Students also explain how computing innovations and computing systems—including the internet—work, explore their potential impacts, and contribute to a computing culture that is collaborative and ethical. Curricula for this course will also prepare students to take the Advanced Placement CS Principles exam. This exam assesses student understanding of the computational thinking practices and learning objectives outlined in the course framework.
Course 4: Software Development Practicum <OR> AP Computer Science A
Software Development Practicum is a capstone course intended to provide students with the opportunity to apply the skills and knowledge learned in previous Software Development courses toward the completion of an in-depth project with fellow team members. Students who have progressed to this level take on more responsibilities for producing independent work and managing processes involved in the planning, designing, refinement, and production of original software applications. The course is designed to allow students to choose their specific application of interest, be it the development of a mobile application (app), an animation package, a game or other educational tool, or any other approved program that requires programming and development skills. Upon completion of the practicum, proficient students will be prepared for postsecondary study and career advancement in software development, and will be equipped to market their finished product should they choose.
AP Computer Science A is an introductory college-level course that introduces students to computer science through programming. Fundamental topics in this course include the design of solutions to problems, the use of data structures to organize large sets of data,the development and implementation of algorithms to process data and discover new information, the analysis of potential solutions, and the ethical and social implications of computing systems.The course emphasizes object-oriented programming and design using the Java programming language. The AP Computer Science A Exam assesses student understanding of the computational thinking practices and learning objectives outlined in the course framework.
Please review PL Catalog and Curriculum Recommendations for FRNYC Schools for SY 25-26.
Cybersecurity Analyst
The Cybersecurity Analyst occupational title introduces students to concepts of technology, and then builds into an intentional sequence focused on established, stackable credentials including CompTIA Network+ and Security+. Students will learn about the technical and social aspects of cybersecurity and conclude in a comprehensive practicum that provides students an opportunity to demonstrate their understanding of security methods and tools, architecture, and operations.
Course 1: Introduction to Computer Science
Introduction to Computer Science is a course intended to provide students with exposure to various technology occupations and pathways such as Cybersecurity, Data Science, and Software Development. Upon completion of this course, proficient students will be able to describe various technology occupations and professional organizations. Moreover, they will be able to demonstrate logical thought processes and discuss the social, legal, and ethical issues encountered in tech professions.
Course 2: CompTIA Network+
CompTIA Network+ is a course intended to teach students the basic concepts of cybersecurity. The course places an emphasis on security integration, application of cybersecurity practices and devices, ethics, and best practices management. The fundamental skills in this course cover both in-house and external threats to network security and design, how to enforce network level security policies, and how to safeguard an organization’s information. Upon completion of this course, students will be able to demonstrate an understanding of cybersecurity concepts, identify fundamental principles of networking systems, understand network infrastructure and network security, and be able to demonstrate how to implement various aspects of security within a networking system.
Course 3: CompTIA Security+
CompTIA Security+ is a course that challenges students to develop advanced skills in concepts and terminology of cybersecurity. This course builds on previous concepts introduced in CompTIA Network+ while expanding the content to include malware threats, cryptography, wireless technologies and organizational security. Upon completion of this course, students will be able to demonstrate an understanding of cybersecurity ethical decisions, malware threats, how to detect vulnerabilities, principles of cryptology, security techniques, contingency plan techniques, security analysis, risk management techniques, and advanced methods of cybersecurity.
Course 4: Cybersecurity Practicum
Cybersecurity Practicum is a capstone course intended to provide students with the opportunity to apply the skills and knowledge learned in previous Cybersecurity courses toward the completion of an in-depth project with fellow team members. Students who have progressed to this level in the Cybersecurity pathway take on more responsibilities for producing independent work and managing processes involved in the planning, designing, refinement, and production of cybersecurity applications. Upon completion of the practicum, students will be prepared for postsecondary study and career advancement in cybersecurity.
Please review PL Catalog and Curriculum Recommendations for FRNYC Schools for SY 25-26.
Data Scientist
The Data Science occupational title introduces students to key concepts in computer science and data analysis while building essential technical and critical thinking skills. Students explore technology career pathways, learn programming with Python, and develop practical skills in collecting, analyzing, and visualizing data. Throughout the sequence, they examine the connections between technology, ethics, and data-driven decision-making. The final courses challenge students to apply their knowledge and tools to real-world scenarios, preparing them for further study and future opportunities in data science and related fields.
Course 1: Introduction to Computer Science
Introduction to Computer Science is a course intended to provide students with exposure to various technology occupations and pathways such as Cybersecurity, Data Science, and Software Development. Upon completion of this course, proficient students will be able to describe various technology occupations and professional organizations. Moreover, they will be able to demonstrate logical thought processes and discuss the social, legal, and ethical issues encountered in tech professions.
Course 2: Computer Programming I (Python)
Computer Programming is a course intended to continue building student understanding of foundational computer science concepts with a focus on programming in Python . The course places emphasis on practicing standard programming techniques and learning the logic tools and methods typically used by programmers to create simple computer applications. Upon completion of this course, proficient students will be able to solve problems by planning multi step procedures; write, analyze, review, and revise programs, converting detailed information from workflow charts and diagrams into coded instructions in a computer language; and will be able to troubleshoot/debug programs and software applications to correct malfunctions and ensure their proper execution.
Course 3: Data Science with Python
Data Science with Python builds on the programming skills students developed in Computer Programming I. In this course, students expand their knowledge of Python by learning how to apply it to real-world data science tasks. They practice collecting, cleaning, and preparing data, and use Python libraries to analyze datasets and create clear, informative visualizations. By applying programming techniques to data-focused problems, students gain hands-on experience with the core tools and methods used by data scientists today.
Course 4: Data Analytics and Visualization
Data Analytics and Visualization builds on the programming and data science skills developed in earlier courses by introducing students to industry-standard database tools and data modeling techniques. Students learn to use SQL to create, manage, and query relational databases and practice organizing data into clear, efficient structures. They also strengthen their ability to analyze and visualize data using Excel and other software, developing more advanced skills in uncovering patterns and telling compelling data stories. By the end of this course, students will be able to integrate their Python knowledge with database and spreadsheet tools to manage larger datasets and communicate findings clearly to diverse audiences.
Please review PL Catalog and Curriculum Recommendations for FRNYC Schools for SY 25-26.
