The document discusses programming languages, with a focus on Python, its features, and applications in data science. It highlights Python's high-level nature, open-source status, and frameworks like Django and Bootstrap for web development. Additionally, it covers data science as a field, its growth, key algorithms, and varied applications, including artificial intelligence and machine learning.

1. by
Younus S B S
M.Phil., Computer Science
Sadakathullah Appa College
Under the Guidance of
Dr.S.Shajun Nisha, MCA, M.Phil, MBA, M.Tech,
Ph.D, MISTE,
Assistant Professor & Head
PG & Research Department of Computer
Science
Sadakathullah Appa College

2. Language
Programming language
Python
Data Science

3. Language
 Communication-Sharing of Information
 Language-a way or a method to make communication

4. Programming Language
 A programming language is a set of commands,
instructions, and other syntax use to create a software
program
 Command: a word that makes system to do something
 Instruction: sequence of commands
 Syntax: Structure of program
 Why we need programming language…?

5. Python
 Python is a high-level programming language
designed to be easy to read and simple to implement.
It is open source

6. High Level Language
 A high-level language (HLL) is a programming
language that enables a programmer to write programs
that are more or less independent of a particular type
of computer. Such languages are considered high-level
because they are closer to human languages and
further from machine languages.

7. Open Source
 Program’s source code is freely available to the public
unlike Commercial Software
 3-Types of Software:
 Freeware : Free to use
 Shareware: Free but limited resource(pay for additional
resource)
 Commercial Software: pay amount before use

8. Python

9. Django
 Django is a high-level Python Web framework that
encourages rapid development and clean, pragmatic
design
 Follows MVT model
 Terminologies:
 Bootstrap
 Jinja
 Pycharm

10. Bootstrap
 Bootstrap is a CSS framework that makes it easier to
create website and web application user interfaces.
 Bootstrap 4 is the newest version of Bootstrap.
 Bootstrap 4 supports all major browsers except
Internet Explorer 9.
 If you require support for IE9 or IE8, you must use
Bootstrap 3.

11. Jinja- Template Engine

12. Pycharm
There are 2-types of Software,
 System Software
 Application Software
Pycharm-Editor (System
Software)

13. Data Science
 Sexiest job of 21st century
 Data science is an interdisciplinary field that uses
scientific methods, processes, algorithms and systems
to extract knowledge and insights from data in various
forms, both structured and unstructured (?)
 Data Mining is just obtain useful information from
massive amount of data
 What is a difference between data & information

14. Massive Data
 According to a paper from IBM, about 2.5 billion
gigabytes of data had been generated on a daily basis
in the year 2012. Another article from Forbes informs
us that data is growing at a pace which is faster than
ever. The same article suggests that by the year 2020,
about 1.7 billion of new information will be developed
per second for all the human inhabitants on this
planet

15. Data Science Algorithms
 Linear Regression
 Logistic Regression
 Linear Discriminant Analysis
 Classification and Regression Trees
 Naive Bayes

16. Algorithms (contd….)
 K-Nearest Neighbors
 Learning Vector Quantization
 Support Vector Machines
 Bagging and Random Forest
 Boosting and AdaBoost

17. Data Science-Main Applications
 Artificial Intelligence
 Machine Learning-Learn from data by algorithms
 Deep Learning- improved ML by Artificial Neural
Ntworks

18. Data Science & ML in Python
 Data Science
 Numpy and Pandas
 ML
 Scikit-Learn
 Typically, these packages developed by Scientists and
implemented by Engineers

19. Applications Internet Search
 Digital Advertisements (Targeted Advertising and re-
targeting)
 Recommender Systems
 Image Recognition
 Speech Recognition
 Gaming
 Price Comparison Websites
 Fraud and Risk Detection
 Delivery logistics