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Computer Science

Sign up for a session at schoolhouse.world, a free peer tutoring platform founded by Sal Khan of Khan Academy. We offer virtual small-group sessions with volunteer tutors from around the world. Join Schoolhouse to learn with a community that’ll support you!

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Join a series to learn, practice, and study Computer Science regularly with other learners like you.

Introduction to Data Science w/ Python 🖥️📊

Starts Wed May 1, 5:00 AM

Welcome to "Introduction to Data Science with Python" course! This is my second time hosting this course, and I have made adjustments and improvements from my first time. In this course, you'll learn how to use Python for data analysis and gain insights from large datasets. Python is a versatile language widely used in the data science community. You'll explore Python's fundamentals, including syntax and data structures. We'll also cover essential libraries such as NumPy, Pandas, and Matplotlib for efficient data manipulation and visualization. Through hands-on activities and projects, you'll develop the skills to analyze and present data effectively. By the end of this 17 session course, you will be an expert on the basics of data science, and you would have completed your very first data science case study project. Please note that there will be assignments after every session to best learn data science. Get ready for an exciting journey into the world of data science! :)

Jacob H

1 spot left!

Intro to Java

Starts Mon Jun 10, 4:30 PM

No installation is needed. We will use online compilers. No prior coding experience required.
Session 1: Primitive Data Types
Session 2: Conditionals
Session 3:Control Flow
Session 4: Loops
Session 5: Capstone project

Anish G

Registration full.

Deep Dive into Convolution Nueral Networks (CNN)!

Starts Wed Jun 12, 8:00 PM

Hello Everyone!
Welcome to Deep Dive into Convolution Neural Networks. In this series, I will teach you how to program your own convolution neural network (CNN) through Python and I will explain how convolution neural networks work, by providing a full outline on how the layers of the model function and a introduction into backpropagation. I want everyone to think of a image recognition problem that they want to solve before joining this series, as this series will be tailored to each individual's needs, based on the project they choose. Please keep in mind that we are strictly only working with CNNs, so do not choose a project that would involve a different type of model. Finally, at the end of this series I will provide a through explanation of how to choose and prepare a project that will get you to the International Science and Engineering Fair (ISEF), as I was given the oppourtunity to compete this year! Hope to see you soon!
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NOTE: we will be using Replit and GitHub through this process. I recommend having a laptop where you can save and quickly access files, if you want to be able to deploy your CNN as a website (which we may cover this this series as well). 

Diya R

1/10

AP Computer Science A Exam Only (2024-25)

Starts Fri Jun 21, 12:00 AM

This series is still appropriate for students taking an actual AP Computer Science A course, but will assume you are not taking an actual course
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Thinking of taking the AP exam next year and don't want to/can't take the course? You've found the perfect series!
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This series will be treated as close to a formal class as possible; the only difference being that it follows a mastery learning method (meaning that it allows ALL students to be caught up with everyone else at once) as opposed to taditional learning (where everyone must follow the same pace as everyone else). This means that several quizzes and tests will be assigned throughout the series. And in order to execute this idea of a formal yet mastery learning class, I will only allow us to advance to next concepts if everyone scores a 90% or higher on these assessments to make the series as easy sailing as possible.
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Self-studying for an AP exam requires a lot discipline, and so you are expected to be prepared to attend the 5 sessions a week (45 minutes each session), although it's fully expected that you'll miss a few sessions here and there.
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Because of this mastery learning method, you will be withdrawn if you still cannot score over a 90% on an assessment assigned over a week ago. If this does happen, i might make another series dedicated to those who've been withdrawn from the series so that you can catchup on your own pace without the guilt of slowing everyone else down.
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I can always schedule a Catchup/Office hours session by request if you were absent for a session/need extra help with a topic.

Jeremy L

12/30

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Computer Science · session

APCSA MCQ Full Practice

Sat May 4, 4:30 PM

(APCSA 5 scorer) We'll simulate taking the full APCSA Multiple Choice section. We'll go over the explanations for any MCQ you have questions on afterwards.
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Agenda:
40 MCQ - 90 minutes
Review - 30 minutes
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The session will likely go overtime, but you can leave after the 2 hour mark. Feel free to stay if you have any questions you want more in-depth explanations on or want general tips on the exam.

Helena H

1/10

Computer Science · session

APCSA FRQ Full Practice

Sun May 5, 4:30 PM

(APCSA 5 scorer) We'll simulate taking the full APCSA Free Response section. I'll answer any questions about scoring and provide example code for how to answer each problem. We'll be using the FRQ from 2021.
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Agenda:
4 FRQ (2021) - 90 minutes
Scoring + Questions - 30 minutes
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The session will likely go overtime, but you can leave after the 2 hour mark. Feel free to stay if you have any questions you want more in-depth explanations on or want general tips on the exam.

Helena H

1/10

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Computer Science

Computer Science

Topics

Format

All Courses Series

Introduction to Data Science w/ Python 🖥️📊

Intro to Java

Deep Dive into Convolution Nueral Networks (CNN)!

AP Computer Science A Exam Only (2024-25)

All Courses Sessions

APCSA MCQ Full Practice

APCSA FRQ Full Practice

That's it for now!