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Computer Science

The RFS computer science curriculum provides a solid base in computer science fundamentals that includes software design and development in collaboration with MIT, Stanford and Harvard computer science cirriculum.

BY SUBJECT:
Technology
Entrepreneurship
Computer Science
Chess
Math
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Nature
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Music
Capoiera
Sports
Spirituality
Fundamentals of HTML

1) Introduction to HTML
2) Structure Elements
3) Links, tables and list
4) Media in HTML
5) Semantic elements in HTML
6) Forms in HTML

Core   Elementary School   Middle School

Fundamentals of CSS

1) Introduction to CSS
2) Background Effect
3) Text Styling Properties
4) Pseudo Classes
5) Box Model
6) Positioning in CSS

Core   Elementary School   Middle School

Bootstrap 4

1) Introduction to Bootstrap
2) Typography
3) Containers in Bootstrap
4) Bootstrap utilities part 1
5) Bootstrap Utilities part 2
6) Bootstrap Carousel and Scrollspy

Core   Elementary School   Middle School

Introduction to JavaScript

1) Introduction to Javascript
2) Introduction to Functions in Javascript
3) Introduction to Methods, Loops and Switches in JavaScript
4) Introduction to Objects in JavaScript
5) Introduction to Array and call stack
6) Introduction to HTML DOM

Core   Elementary School   Middle School

Brief of JavaScript

1) Brief on JavaScript
2) Classes in JavaScript
3) Array sorting and mapping in JavaScript
4) JavaScript in Detail
5) Json and JS Asynchronous
6) Validation in JS

Core   Elementary School   Middle School

App Development using Js

1) Introduction to JS Apps
2) Palindrome app using JS
3) To-Do List App using JS
4) Digital Clock using JS
5) Stopwatch using JS
6) Rolling Dice app using JS

Core   Elementary School   Middle School

Capstone project on web development

1) Capstone Project
2) Slider in Website
3) Content Display in Website
4) Footer in Website
5) Website Part 1
6) Website Part 2

Core   Elementary School   Middle School

Python Basics

1) Welcome to Programming
2) Getting started with programming
3) Data types in python
4) Python Operators – I
5) Conditional Statements
6) Python Operator II

Core   Elementary School   Middle School

Let's Begin with Loops

1) Nested conditional statements
2) Loops
3) While loop
4) Nested loop
5) Pattern
6) Introduction to turtle

Core   Elementary School   Middle School

Python Functions and Modules

1) Function
2) Arguments
3) Keywords
4) Exception Handling
5) Random and math module
6) Date, time, and calendar module

Core   Elementary School   Middle School

Data Structures in Python

1) Getting Started with Lists
2) Tuples
3) All About Dictionary
4) Sets and Arrays
5) Advanced Python Functions
6) Python Challenges

Core   Elementary School   Middle School

Object Oriented Programming

1) Object-Oriented Programming
2) More on Object-Oriented Programming
3) Inheritance
4) Encapsulation and Special Functions
5) Abstraction and Polymorphism
6) Challenges on Object-Oriented Programming

Core   Elementary School   Middle School

Game Building with Pygame

1) Let’s Begin with Pygame
2) Basic Game Building Concepts
3) Let’s Add Sprites
4) Let’s Level Up The Game
5) Space Invader Project – Part 1
6) Space Invader Project – Part 2

Core   Elementary School   Middle School

GUI using Python Tkinter

1) Widgets for Starters
2) Tkinter Geometry Managers
3) Where’s the event
4) Let’s build a Text Editor
5) Denomination Calculator
6) Restaurant Management System

Core   Elementary School   Middle School

Welcome to Data Science

1) Welcome to Data Science
2) Introduction to Pandas
3) Introduction to Matplotlib
4) Seaborn Library in Python
5) Advance Visualizations in Python
6) Capstone Project

Core   Elementary School   Middle School

Stanford University
Introduction to Computer Science
  1. WEEK 1 
    1. Introduction 
    2. Code Writing 
    3.  Code Variables 
    4. Digital Images 
    5. Image Code 
  2. WEEK 2 
    1. Image for Loop 
    2.  Image Expressions 
    3. Image Puzzles 
    4. Grayscale Images 
  3. WEEK 3 
    1. Image Logic 
    2. Image Bluescreen 
    3. Computer hardware 
    4. Optional Video: Moore’s Law Flashlight 
    5. Optional Video: How a Hard Drive Works 
    6. Bits and Bytes 
    7. Kilobytes Megabytes Gigabytes 
    8. Make your own Bluescreen 
  4. WEEK 4 
    1. Software 
    2. Computer Languages 
    3. Computer Networking 
    4. The Internet – TCP/IP 
    5. Table Data 
  5. WEEK 5 
    1. Table startsWith endsWith 
    2. Table Boolean Logic 
    3. Table Counting 
    4. Table Counting Multiple 
    5. Analog and Digital 
  6. WEEK 6 
    1. Analog and Digital Part 2 
    2. Digital Media 
    3. Spreadsheets 
    4. Computer Security 
    5. Conclusions 
  7. Course Resources 
    1. Course Syllabus and How-To 
    2. CS101 Browser Checker 
    3. RGB Explorer 
    4. Image Functions Reference 

Core   Elementary School   Middle School

Harvard University
Introduction to Programming with Python
  1. Section 1 
    1. Creating your first programs in Python 
    2. Functions 
    3. Bugs 
    4. Variables  
    5. Comments  
    6. Pseudocode  
    7. Strings  
    8. Parameters  
    9. Formatted Strings 
    10. Integers  
    11. Principles of readability  
    12. Floats  
    13. Creating your own functions 
    14. Return values 
  2. Section 2 
    1. Conditionals 
    2. If Statements 
    3. Control flow, elif, and else 
    4. Or 
    5. And 
    6. Modulo 
    7. Creating your own function 
    8. Pythonic coding 
    9. Match 
  3. Section 3 
    1. Loops 
    2. While 
    3. For 
    4. Len 
    5. List 
    6. Dict 
  4. Section 4 
    1. Exceptions 
    2. Value Errors 
    3. Runtime Errors 
    4. Try 
    5. Else 
    6. Pass 
  5. Section 5 
    1. Unit tests 
    2. Assert 
    3. Pytest 
  6. Section 6 
    1. Regular Expressions 
    2. Case Sensitivity 
    3. Cleaning Up User Input 
    4. Extracting User Input 
  7. Section 7 
    1. Object-oriented programming 
    2. Classes 
    3. Raise 
    4. Class Methods 
    5. Static Methods 
    6. Inheritance 
    7. Operator Overloading 

Core   Elementary School   Middle School

Harvard University
Introduction to Computer Science
  1. Section 1 – SCRATCH 
    1. Welcome! 
    2. What’s Ahead 
    3. Community! 
    4. Computer Science 
    5. ASCII 
    6. Unicode 
    7. Representation 
    8. Algorithms 
    9. Pseudocode 
    10. Artificial Intelligence 
    11. Scratch 
    12. Hello World 
    13. Hello, You 
    14. Meow and Abstraction 
    15. Conditionals 
    16. Oscartime 
    17. Ivy’s Hardest Game
  2. Section 2 – C 
    1. Welcome! 
    2. Hello World 
    3. Functions
    4. Variables 
    5. Conditionals 
    6. Loops 
    7. Operators and Abstraction 
    8. Linux and the Command Line 
    9. Mario 
    10. Comments 
    11. Types
  3. Section 3 – Arrays 
    1. Welcome! 
    2. Compiling 
    3. Debugging 
    4. Arrays 
    5. Strings 
    6. String Length 
    7. Command-Line Arguments 
    8. Exit Status 
    9. Cryptography
  4. Section 4 – Algorithms  
    1. Welcome! 
    2. Linear Search 
    3. Binary Search 
    4. Running Time 
    5. search.c 
    6. Data Structures 
    7. Sorting 
    8. Bubble Sort 
    9. Recursion 
    10. Merge Sort
  5. Section 5 – Memory 
    1. Welcome! 
    2. Pixel Art 
    3. Hexadecimal 
    4. Memory 
    5. Pointers 
    6. Strings 
    7. Pointer Arithmetic 
    8. String Comparison 
    9. Copying 
    10. malloc and Valgrind 
    11. Garbage Values 
    12. Pointer Fun with Binky 
    13. Swap 
    14. Overflow 
    15. scanf 
    16. File I/O
  6. Section 6 – Data Structure 
    1. Welcome!
    2. Data Structures 
    3. Stacks and Queues 
    4. Jack Learns the Facts 
    5. Resizing Arrays 
    6. Linked Lists 
    7. Trees 
    8. Dictionaries 
    9. Hashing and Hash Tables 
    10. Tries
  7. Section 7 – Python 
    1. Welcome! 
    2. Python 
    3. Hello 
    4. Speller 
    5. Filter 
    6. CS50 Library 
    7. Strings 
    8. Variables 
    9. Types 
    10. Calculator 
    11. Conditionals 
    12. Object-Oriented Programming 
    13. Loops 
    14. Abstraction 
    15. Truncation and Floating Point Imprecision 
    16. Exceptions 
    17. Mario 
    18. Lists 
    19. Searching and Dictionaries 
    20. Command-Line Arguments 
    21. Exit Status 
    22. Third-Party Libraries
  8. Section 8 – Artificial Intelligence  
    1. Welcome! 
    2. Image Generation 
    3. ChatGPT 
    4. Prompt Generation 
    5. CS50.ai 
    6. Generative AI 
    7. Decision Trees 
    8. Minimax 
    9. Machine Learning 
    10. Deep Learning 
    11. Generative Artificial Intelligence
  9. Section 9 – SQL 
    1. Welcome! 
    2. Flat-File Database 
    3. Relational Databases 
    4. Shows 
    5. JOINs 
    6. Indexes 
    7. Using SQL in Python 
    8. Race Conditions 
    9. SQL Injection Attacks
  10. Section 10 – HTML, CSS, JavaScript 
    1. Welcome! 
    2. Routers 
    3. DNS 
    4. HTTP 
    5. HTML 
    6. Regular Expressions 
    7. CSS 
    8. Frameworks 
    9. JavaScript
  11. Section 11 – Flask 
    1. Welcome! 
    2. Static to Dynamic 
    3. Flask 
    4. Forms 
    5. Layout 
    6. POST 
    7. Frosh IMs 
    8. Flask and SQL 
    9. Session 
    10. Shopping Cart 
    11. Shows 
    12. AJAX and APIs 
    13. JSON
  12. Section 12 – Cybersecurity 
    1. Recap 
    2. Looking Ahead 
    3. Cybersecurity 
    4. Passwords 
    5. Phone Security 
    6. Password Managers 
    7. Two-factor Authentication 
    8. Hashing 
    9. Cryptography 
    10. Passkeys 
    11. Encryption 
    12. Deletion 

Core   Elementary School   Middle School

Harvard University
Web Programming with Python and JavaScript
  1. Section 1 – HTML, CSS
    1. Introduction 
    2. Web Programming 
    3. HTML (Hypertext Markup Language) 
      1. Document Object Model (DOM) 
      2. More HTML Elements 
      3. Forms 
    4. CSS (Cascading Style Sheets) 
    5. Responsive Design 
    6. Bootstrap 
    7. Sass (Syntactically Awesome Style Sheets)
  2. Section 2 – Git
    1. Introduction 
    2. Git 
    3. GitHub 
    4. Commits 
    5. Merge Conflicts 
    6. Branching 
      1. More GitHub Features
  3. Section 3 – Python
    1. Introduction 
    2. Python 
    3. Variables 
    4. Formatting Strings 
    5. Conditions 
    6. Sequences 
      1. Strings 
      2. Lists 
      3. Tuples 
      4. Sets 
      5. Dictionaries 
      6. Loops 
    7. Functions 
    8. Modules 
    9. Object-Oriented Programming 
    10. Functional Programming 
      1. Decorators 
      2. Lambda Functions 
    11. Exceptions
  4. Section 4 – Django
    1. Introduction 
    2. Web Applications 
    3. HTTP 
    4. Django 
    5. Routes 
    6. Templates 
      1. Conditionals: 
      2. Styling 
    7. Tasks 
    8. Forms 
      1. Django Forms 
    9. Sessions
  5. Section 5 – SQL, Models, and Migrations
    1. Introduction 
    2. SQL 
      1. Databases 
      2. Column Types 
    3. Tables 
    4. SELECT 
      1. Working with SQL in the Terminal 
      2. Functions 
      3. UPDATE 
      4. DELETE 
      5. Other Clauses 
    5. Joining Tables 
      1. JOIN Query 
      2. Indexing 
      3. SQL Vulnerabilities 
    6. Django Models 
    7. Migrations 
    8. Shell 
      1. Starting our application 
    9. Django Admin 
    10. Many-to-Many Relationships 
    11. Users
  6. Section 6 – JavaScript
    1. Introduction 
    2. JavaScript
    3. Events 
    4. Variables 
    5. querySelector 
    6. DOM Manipulation 
      1. JavaScript Console 
      2. Arrow Functions 
      3. TODO List 
    7. Intervals 
    8. Local Storage 
    9. APIs 
      1. JavaScript Objects 
      2. Currency Exchange
  7. Section 7 – User Interface
    1. Introduction 
    2. User Interfaces 
    3. Single Page Applications 
    4. Scroll 
      1. Infinite Scroll 
    5. Animation 
    6. React 
      1. Addition
  8. Section 8 – Testing, CI/CD
    1. Introduction 
    2. Testing 
    3. Assert 
      1. Test-Driven Development
    4. Unit Testing 
    5. Django Testing 
      1. Client Testing 
    6. Selenium 
    7. CI/CD 
    8. GitHub Actions 
    9. Docker
  9. Section 9 – Scalability and Security
    1. Introduction
    2. Scalability 
    3. Scaling 
    4. Load Balancing 
    5. Autoscaling 
      1. Server Failure 
    6. Scaling Databases 
      1. Database Replication 
    7. Caching 
    8. Security 
      1. Git and GitHub 
    9. HTML 
    10. HTTPS 
      1. Secret-Key Cryptography 
      2. Public-Key Cryptography 
    11. Databases 
      1. APIs 
      2. Environment Variables 
    12. JavaScript 
      1. Cross-Site Request Forgery 
    13. What’s next? 

Core   Elementary School   Middle School

MIT
Introduction to Computational Thinking and Data Science
  1. Section 1 – Overview
    1. Introduction
  2. Section 2 – Entrance Survey
    1. Preliminary Survey
  3. Section 3 – Python
    1. Python 
    2. Hello 
    3. Speller 
    4. Filter 
    5. CS50 Library 
    6. Strings 
    7. Variables 
    8. Types 
    9. Calculator 
    10. Conditionals 
    11. Object-Oriented Programming 
    12. Loops 
    13. Abstraction 
    14. Truncation and Floating Point Imprecision 
    15. Exceptions 
    16. Mario 
    17. Lists 
    18. Searching and Dictionaries 
    19. Command-Line Arguments
  4. Section 4 – Unit 1
    1. Optimization and the Knapsack Problems
    2. Decision Trees and Dynamic Programming
    3. Graph Problems 
    4. Problem Set 1
  5. Section 5 – Sandbox
    1. Hands on 

Core   Elementary School   Middle School

MIT
Introduction to Computer Science and Programming Using Python
  1. Section 1 – Why should you learn to write programs?
    1. Creativity and motivation
    2. Computer hardware architecture
    3. Understanding programming
    4. Words and sentences
    5. Conversing with Python
    6. Terminology: Interpreter and compiler
    7. Writing a program
    8. What is a program?
    9. The building blocks of programs
    10. What could possibly go wrong?
    11. Debugging
    12. The learning journey
  2. Section 2 – Variables, expressions, and statements
    1. Values and types
    2. Variables
    3. Variable names and keywords
    4. Statements
    5. Operators and operands
    6. Expressions
    7. Order of operations
    8. Modulus operator
    9. String operations
    10. Asking the user for input
    11. Comments
    12. Choosing mnemonic variable names
    13. Debugging
  3. Section 3 – Conditional execution
    1. Boolean expressions
    2. Logical operators
    3. Conditional execution
    4. Alternative execution
    5. Chained conditionals
    6. Nested conditionals
    7. Catching exceptions using try and except
    8. Short-circuit evaluation of logical expressions
    9. Debugging
  4. Section 4 – Functions
    1. Function calls
    2. Built-in functions
    3. Type conversion functions
    4. Math functions
    5. Random numbers
    6. Adding new functions
    7. Definitions and uses
    8. Flow of execution
    9. Parameters and arguments
    10. Fruitful functions and void functions
    11. Why functions?
    12. Debugging
  5. Section 5 – Iteration 
    1. Updating variables
    2. The while statement
    3. Infinite loops
    4. Finishing iterations with continue
    5. Definite loops using for
    6. Loop pattern
    7. Debugging 

Core   Elementary School   Middle School

Harvard University
Introduction to Artificial Intelligence with Python
  1. Introduction to AI
  2. Graph search algorithms
    1. Solving Search Problems
    2. Depth First Search
    3. Breadth First Search
  3. Adversarial search
    1. Minimax Problem
    2. Alpha-Beta Pruning
    3. Depth Limited Minimax
  4. Knowledge representation
    1. Propositional Logic
    2. Knowledge Engineering
    3. De Morgan’s Law
    4. Resolution
  5. Logical inference
    1. Inference Introduction
    2. Inference Rule
    3. Modus Ponens
    4. Double Negative Elimination
    5. Implication Elimination
  6. Probability theory
    1. Axioms in probability
    2. Conditional probability
    3. Bayes’ Rule
    4. Joint Probability
    5. Probability Rules
    6. Bayesian networks
    7. Markov models
  7.  Optimization
    1. Local Search
    2. Hill Climbing
    3. Simulated Annealing
    4. Linear Programming
    5. Constraint satisfaction
    6. Arc Consistancy
    7. Backtracking Search
  8. Machine learning
    1. Supervised Learning
    2. Perceptron Learning
    3. Support Vector Machine
    4. Regression
    5. Overfitting
    6. Regularization
    7. Scikit-learn
    8. Reinforcement learning
    9. Markov Decision Processes
    10. Q-Learning
    11. Unsupervised Learning
    12. K-mean Clusture
  9. Neural networks
    1. Activation Functions
    2. Neural Network Structure
    3. Gradient Descen
    4. Multilayer Neural Network
    5.  Backpropogation
    6.  Overfitting
    7.  TensorFlow
    8. Computer Vision
    9. Image Convolution
    10. Convolutional Neural Network
    11. Recurrent Neural Network
  10. Natural language processing
    1. Syntax & Semantics
    2. Nltk
    3. N-grams
    4. Naive bayes
    5. Information Retrival
    6. Information Extraction
    7. Word Representation
    8. Word2vec

Core   Elementary School   Middle School

MIT
Machine Learning with Python: from Linear Models to Deep Learning
  1. Lectures :
    1. Introduction
    2. Linear classifiers, separability, perceptron algorithm
    3. Maximum margin hyperplane, loss, regularization
    4. Stochastic gradient descent, over-fitting, generalization
    5. Linear regression
    6. Recommender problems, collaborative filtering
    7. Non-linear classification, kernels
    8. Learning features, Neural networks
    9. Deep learning, back propagation
    10. Recurrent neural networks
    11. Generalization, complexity, VC-dimension
    12. Unsupervised learning: clustering
    13. Generative models, mixtures
    14. Mixtures and the EM algorithm
    15. Learning to control: Reinforcement learning
    16. Reinforcement learning continued
    17. Applications: Natural Language Processing
  2. Projects :
    1. Automatic Review Analyzer
    2. Digit Recognition with Neural Networks
    3. Reinforcement Learning

Core   Elementary School   Middle School

Harvard University
Introduction to Data Science and AI with Python
  1. Introduction
  2. Linear Regression
    1. Introduction to Regression
    2. Error Evalution and model comparison
    3. Linear Regression
  3. Multiple and Ploynomial Regression
    1. Multiple Regression
    2. Techniques of Multilinear Modeling
    3. Polynomial Regression
  4. Model Section and Cross Validation
    1. Model Section
    2. Cross Validation
  5. Bias, Variance, and Hyperparameters
    1. Bias and Variance
    2. Ridge and LASSO
  6. Classification and Logistic Regression
    1. Classification and KNN
    2. Logistic Regression
  7. Multi-logstic Regression and Missingness
    1. Multinomial Logistic Regression
    2. Missingness
  8. Bootstrap, Confidence Intervals, and Hypothesis Testing
    1. Inference in Linear Regression
    2. Bootstrap and Confidence Intervals
    3. Prediction Intervals
    4. Evaluating Predictor Significance

Core   Elementary School   Middle School

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