Franklin High School Computer Science

Teacher Information

 Mr. Dagler

 mrdagler@csfhs.net

 (916) 714-8150 x 41912

Welcome to the Computer Science Pathway at Franklin High School. In this website, you will find a description for all of the classes in the pathway and how I connect my students to industry partners: guest speakers, field trips, coding camps, and competitions. All of the classes and activities in our Computer Science program are based around our CS Pathway Outcomes.

The three year sequence for the programming pathway is Exploring Computer Science, AP Computer Science Principles and AP Computer Science A. We also offer two elective classes: Web-Development and Machine Learning. You will earn a graduation cord when you take a total of four coures in the pathway..

Exploring Computer Science

Learn the command line interface • Develop problem-solving skills and techniques • Program using the C language • Solve problems using control flow, arrays and iteration • Create code for modular robotics • Compete at a statewide programming/robotics competition.

AP Computer Science Principles

Explore how computing and technology is impacting us today through a project-based approach • Address real-world problems involving Big Data and Cybersecurity • Learn the history of the internet and how it works • Earn a 5.0 GPA bump and college credit by taking the AP test.

AP Computer Science A

Learn content equivalent to a first-semester college-level course in CS • Learn object-oriented programming using the Java language • Solve problems by developing algorithms and using data structures • Compete at HP CodeWars • Earn a 5.0 GPA bump and college credit by taking the AP test.

Web Design and Development

Develop web sites with HTML5 and CSS • Validating HTML code using W3C • Using images including Image Maps and SVG • Responsive design with BootStrap and FlaxBox • Use JavaScript to communicate with users and modify DOMTranscompilers including SASS and TypeScript.

Machine Learning

Gain understanding of every ML model covered • Use regression to model continuous data • Predect descrete resutls using classification models • Discover unkown patters with clustering models • Additional topics include association rule learning, reinforcement learing, and natural langue processing

Pathway Outcomes

We developed these outcomes in partnership with industry partners and administration. All of the classes, field trips, guest speakers, field trips, and competitions are align with these outcomes. Students who complete our pathway will have a mastery of these outcomes.