Coding Resources
Why Learn To Code?
In today's technology-driven era, coding stands out as a foundational skill. For high school and college students, acquiring coding expertise opens doors to prestigious STEM careers and opportunities to be at the forefront of innovation. As technology continues to shape our future, becoming proficient in coding will become as indispensable as traditional literacy. At Illuminating Minds, we recognize this importance and provide resources to prepare our students for the digital age.
Coding Tutorials
Beginner
1. Introduction to Python: Basics & Setup
Embark on your coding journey by grasping the foundational concepts of Python, a language celebrated for its accessibility to beginners.
⏱️ Est. time: 45 mins | 🌟🌟
2. Basic Data Types & Variables
Familiarize yourself with Python's core elements, such as numbers and strings, forming the basis of more complex structures.
⏱️ Est. time: 30 mins | 🌟
3. Control Structures: Loops and Conditionals
Command your code effortlessly using loops and conditional directives, paving the way for intricate operations.
⏱️ Est. time: 40 mins | 🌟🌟
Dive into the realm of reusability with Python's functions, understanding how to segment and streamline your code.
⏱️ Est. time: 50 mins | 🌟🌟🌟
Intermediate
5. Object-Oriented Programming Concepts
Delve into the heart of Python's structure, learning how classes and objects are integral to scalable and modular code development.
⏱️ Est. time: 1 hour | 🌟🌟🌟
6. Data Structures: Lists, Dictionaries, Sets, Tuples
Discover the diverse data structures that Python offers and understand their respective applications in various programming scenarios.
⏱️ Est. time: 1 hour 15 mins | 🌟🌟🌟🌟
Equip yourself to gracefully handle unforeseen errors in your code, ensuring robust applications that can address and recover from anomalies.
⏱️ Est. time: 40 mins | 🌟🌟🌟
Advanced
8. Advanced Python Libraries (e.g., NumPy, Pandas, Matplotlib)
Dive deep into Python's rich ecosystem of libraries tailored for data analysis, scientific computing, and visualization.
⏱️ Est. time: 2 hours | 🌟🌟🌟🌟🌟
9. Introduction to AI & Machine Learning with Python
Embark on a journey into the realm of artificial intelligence, leveraging Python's vast array of machine learning tools and libraries.
⏱️ Est. time: 2 hours 30 mins | 🌟🌟🌟🌟🌟
10. Data Visualization Techniques
Unveil the power of data by learning to represent it visually, using graphs, charts, and plots to convey complex information intuitively.
⏱️ Est. time: 1 hour 30 mins | 🌟🌟🌟🌟
Coding Challenges
Easy
Buzzing Elements
Description: Using the periodic table elements, write a program that prints 'Buzz' for elements with atomic number multiples of 3, 'Fizz' for multiples of 5, and 'BuzzFizz' for multiples of both.
Expected Outcome: The first 15 elements' atomic numbers should result in 1, 2, Buzz, 4, Fizz, Buzz, 7, 8, Buzz, Fizz, 11, Buzz, 13, 14, BuzzFizz
Difficulty: 1/5 | 🌟
Units Converter
Description: Develop a tool where users can convert units like kilograms to pounds, meters to feet, Celsius to Fahrenheit, and vice versa.
Expected Outcome: Converting 100 Celsius should give 212 Fahrenheit.
Difficulty: 2/5 | 🌟🌟
Medium
DNA Sequence Reverse-Complement
Description: Given a DNA sequence (e.g., ACGT), produce its reverse-complement (e.g., TGCAs).
Expected Outcome: For the input "AGTC", the output should be "GACT".
Difficulty: 3/5 | 🌟🌟🌟
Solar System Simulator
Description: Simulate a solar system where you can add planets with their orbits and visualize their movements around the sun.
Expected Outcome: After adding Earth and Mars, the visualization should show Earth completing one orbit faster.
Difficulty: 3/5 | 🌟🌟🌟
Hard
Automated Plant Watering System
Description: Design a simulation where users can schedule waterings for different plants based on their water needs and monitor soil moisture.
Expected Outcome: If "Cactus" is set to be watered every 7 days, the soil moisture should decrease over time and spike on the 7th day.
Difficulty: 4/5 | 🌟🌟🌟🌟
Facial Recognition with Filters
Description: Implement a basic facial recognition system that can detect faces in an image and apply fun filters like glasses or mustaches.
Expected Outcome: Given a selfie, the system should recognize the face and apply the chosen filter appropriately.
Dificulty: 4/5 | 🌟🌟🌟🌟
Expert
Mini Neural Network
Description: Construct a mini neural network that can recognize handwritten digits. Train it using a basic dataset and evaluate its accuracy.
Expected Outcome: After training, the system should recognize a handwritten '5' correctly more often than not.
Difficulty: 5/5 | 🌟🌟🌟🌟🌟