Defining Data Science • What Does a Data Science Professional Do? • Data Science in Business • Use Cases for Data Science • application advantages

1. Applications & Advantages Of Python
Applications/Projects that are currently hot in python
Wine Quality Prediction
This is one of the most demanded datasets for data science beginners. It is divided into 2
datasets. Users have the liberty to perform both regression and classification on this data. It will
test your understanding of basic machine learning, such as outlier detection and feature
selection. There are 4898 rows and 12 columns in this dataset.
Loan Prediction
The insurance domain has one of the largest uses of analytics and data science methods in
their field. This dataset will provide you with a basic understanding of working on data sets from
insurance companies – what challenges these companies are currently facing, what game-
changing strategies are been implemented, which outcome variables are suitable for their
operation etc. It is a pure classification problem. The data has 615 rows and 13 columns.
Time Series Analysis
Time Series is one of the most commonly used phenomena in data science. It has a wide
variety of applications ranging from weather forecasting, predicting sales to analyzing year on
year trends, etc. This dataset is specific to the time series and the challenge here is to forecast
traffic on a mode of transportation.
Twitter Classification
Scrapping and working with the Twitter data has become a mandatory part of sentiment
analysis problems. If you want to understand the working of this kind of unstructured data,
definitely you will have fun working on the challenge this dataset poses. The dataset is 3MB in
size and has 31,962 tweets.
Recommendation Engine
In this practice problem, the users are introduced with the data of programmers and questions
that they previously solved, along with the time that they took to solve those questions. As a
data scientist, the model you build will help online judges to decide the next level of questions to
recommend to a user.
Handwritten Recognition using MNIST dataset
This is used for natural language processing. Dataset consists of total 60,000 in training model
and 10.000 in the test model. The algorithm recognizes the human language and demonstrated
the same with the use of SVM and Tensorflow.
All the projects can be easily found on Kaggle and can be extensively understood by
practicing them.
Advantages Over Other Languages
COST EFFECTIVE, TIME-EFFICIENT AND EASY TO GRASP

2. As Python’s syntax has less code to execute in real-time, it enables time-saving and cost-saving
for the users. Also, the client is happy because it means less money going from his pocket.
Many full-time programmers have discussed the ups and downs of Python in Quora and many
blogs, where it’s pointed out that the main benefit of Python is the little effort required for writing
and executing lines of codes compared to other languages, such as C++ or Java.
For example, printing a simple statement like “Hi guys!” in C++ requires.
#include <iostream>
int main() { std::cout << “Hi guys! “; return 0; }
In Python, it is represented as
print(“Hi guys!”)
Sealed approval by renowned and experienced data scientists from over the globe
The rate at which the data is booming is the reason why python is the primetime language of
this era. It has everything going in its way, be it data mining, data wrangling, data cleaning, data
manipulation, or data handling. It is being called the “gold” of this digital era thanks to its
robustness and clever engineering.
Data scientist have been fiddling with the skulls and bones of python to understand its core idea
and make it futile for machine learning and deep learning algorithms. This is the reason Python
is increasingly being used in both industry and academic applications.
Used by big organizations
Big companies are increasingly choosing Python over Java and C++ as their preferred
language. The vast majority of IT giants including Google, Dropbox, Spotify, and Instagram are
using it to add new and ground-breaking features to their applications and products. Meanwhile,
this trend has entered into industries such as science, gaming and 3D rendering meaning
companies such as NASA, Electronic Arts and NVidia have made it as a crucial backbone to
their systems!