Algorithms Lecture 1: Introduction to Algorithms

Analysis and Design of Algorithms
Introduction to Algorithms

Algorithms
Time Complexity & Space Complexity
Algorithm vs Pseudocode
Some Algorithm Types
Programming Languages
Python
Anaconda

An algorithm is a set of steps of operations to solve a
problem performing calculation, data processing,
and automated reasoning tasks.
An algorithm is the best way to represent the
solution of a particular problem in a very simple and
efficient way.

Algorithms
Analysis Design

Analysis: predict the cost of an algorithm in terms of
resources and performance
Design: creating an efficient algorithm to solve a
problem in an efficient way using minimum time and
space.

Analysis
Time Space

Time Complexity is a function describing the amount of time
required to run an algorithm in terms of the size of the input.
Space Complexity is a function describing the amount of
memory an algorithm takes in terms of the size of input to the
algorithm.

Time Complexity
What make algorithm “fast”?
Space Complexity
How much memory is used?

 Input: sequence <a1, a2, …, an> of numbers.
 Output: permutation <a'1, a'2, …, a'n> such that
a'1  a'2  …  a'n .
Example:
Input
Output
8 12 5 9 2
2 5 8 9 12

 An algorithm is a formal definition with some specific characteristics
that describes a process. Generally, the word "algorithm" can be
used to describe any high level task in computer science.
 Pseudocode is an informal and human readable description of an
algorithm leaving many details of it. Writing a pseudocode has no
restriction of styles and its only objective is to describe the high level
steps of algorithm.

 Algorithm: Selection Sort
Input: A list L of integers of length n
Output: A sorted list L1 containing those integers present in L
Step1: Find the minimum value in the list L
Step2: Swap it with the value in the current position
Step3: Repeat this process for all the elements until the entire list is sorted
Step 4: Return the sorted list L1
Step 5: Stop

 Pseudocode : Selection Sort
for j ← 1 to n-1
smallest ← j
for i ← j + 1 to n
if A[ i ] < A[ smallest ]
smallest ← i
Exchange A[ j ] ↔ A[ smallest ]

Sorting
Algorithms
Searching
Algorithms
Graph
Algorithms
Patterns
Algorithms
Numerical
Algorithms

Sorting Algorithms are to rearrange the items of a given
list in non decreasing order.
Searching Algorithms deal with finding a given value,
called a search key, in a given set.

Pattern (String) Algorithms deal with string which comprise
letters, numbers, and special characters; bit strings, which
comprise zeros and ones; and gene sequences
Numerical Algorithms deal with mathematical problems that
solving equations and systems of equations, computing
definite integrals ,evaluating functions, and so on.

Graph Algorithms deal with graphs. Graph can be thought of
as a collection of points called vertices, some of which are
connected by line segments called edges. Graphs can be used
for modeling a wide variety of applications, including
transportation, communication, social and economic
networks, project scheduling, and games.

 All algorithms can be coded using any programming language
such as ( Pyhton, C++, Java, PHP, JavaScript, C#, …)
 The most used programming language in this course is Python
 Why Python???

1) Easy to Understand:
Python is very high level language, Python reads like English.
Python is incredibly easy to learn and use.
2) Python Has Amazing Libraries
When you’re working on bigger projects, libraries can really help
you save time and cut down on the initial development cycle.

NumPy
SciPy
Matplotlib Pandas
Scikit Learn
Statsmodels Seaborn
Scrapy
Keras

3) Supportive community
Python has documentation, guides, tutorials and more. Plus, the
developer community is incredibly active.
4) Great Corporate Sponsor
C# has Microsoft, Java has Sun and PHP is used by Facebook.
Google adopted Python heavily back in 2006, and they’ve used it
for many platforms and applications since.

5) Python can do:

6) Python distribution:
 The best Python distribution, we will used in our course is Anaconda

 Jupyter
notebook

 Spyder

Algorithms
Lab
C++
JavaPython

Algorithms
Lab
Solve Problems
Python
Notebook

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Algorithms Lecture 1: Introduction to Algorithms

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