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          "data": "**Algorithm **is a process or set of steps to accomplish a certain task.\n\n| **Algorithms** | **Programs** |\n|:---:|:---:|\n| It is a step\\-by\\-step procedure for solving the problem | It is the implementation in “code” that instructs the computer how to execute the algorithm. |\n"
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          "data": "**Big O notation** is used to describe the **performance** or** complexity **of an algorithm. Big O specifically describes the worst\\-case scenario, and can be used to describe the execution time required or the space used \\(e.g. in memory or on disk\\) by an algorithm.\n\n**Common notations**_:_\n1. Omega\\(Ω\\)\n1. Theta \\(θ\\)\n1. Omicron\\(O\\) or Big O\n\n\n\n\n### Big\\-O notation :\n\n* **O\\(1\\)**  \\- **Constant** \\- no loops\n* **O\\(log N\\)** \\- **Logarithmic** \\- usually searching algorithms have log n if they are sorted \\(Binary Search\\)\n* **O\\(n\\)** \\- _Linear_ \\- for loops, while loops through n items\n* **O\\(n log\\(n\\)\\)** \\- **Log Linear** \\- usually sorting operations\n* **O\\(n^2\\)** \\- **Quadratic** \\- every element in a collection needs to be compared to ever other element. Two nested loops\n* **O\\(2^n\\)** \\- **Exponential** \\- recursive algorithms that solves a problem of size N\n* **O\\(n\\!\\)** \\- **Factorial** \\- you are adding a loop for every element\n\n"
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          "data": "## Understand the problem\n\n* Can I restate the problem in my own words ?\n* What are the inputs that go into the problem ?\n* What are the outputs that should come from the solution to the problem ?\n* Can the outputs be determined from the inputs ? Do I have enough info to solve the problem ?\n* How should I label the important pieces of data that are a part of the problem ?\n\n"
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