Data science is a field of study wherein data is analyzed using some specific parameters and decision is taken based on the pattern and results that are generated after the analysis. It is an interdisciplinary science that involves using scientific methods, algorithms and processes to study the available data and gain knowledge. Crampete Data Science Course shows how to become a Data Scientist from scratch. A data scientist is a person who uses a mixture of different concepts from mathematics, statistics, information science and business intelligence to write algorithms for analyzing data. The results of the analysis are used by organizations to make smarter business decisions. In general, a data scientist needs to know how to code so that they can write scripts used to process the data. http://www.crampete.com/

1. Data
Science

2. What is Data Science?
Data science is an interdisciplinary science wherein scientific methods,
algorithms and processes are used to study the available data and gain
knowledge. In this field, data is analyzed using some specific parameters
and decisions are made based on the patterns and results generated
from the analysis.

3. Career
in Data Science
in India
Data science and artificial intelligence have
slowly made their way into sectors like travel,
healthcare, education, stock market, and
e-commerce. In India, if you have a job
experience of working as a data scientist,
you can move onto other roles such as:
Data architect
Data engineer
Data analyst
Business intelligence analyst
Database administrator

4. Top Recruiters Hiring Data Scientists
Apple Google IBM
Amazon Accenture JP Morgan Chase
Microsoft

5. What Does a Data Scientist Do?
1. Discover and acquire
the right data
2. Process and clean
the data
3. Categorise and store
the data
4. Data investigation and
exploratory data analysis
5. Use one or more models
and algorithms
6. Use machine learning
tools
7. Measure results and
draw conclusions
8. Present
findings
9. Fine-tune the
methods

6. Who Can Be a Data Scientist?
There are two categories of people who can become a data scientist
1. IT students and professionals
These categories of students have
either studied computer science or
an IT course and have a bachelors or
masters in a related field.
These categories of students are from
completely different background. They tend
to choose data science because they want to
switch careers for both personal and
professional reasons.
2. Non-IT students and professionals

7. Data Science
Skills You Need
to Learn?
Probability
Artificial
intelligence
Data
analysis
Coding- In
Python and R
Computer
vision
Deep
learning
Machine
learning
Statistics

8. Steps to
Help You Become
a Data Scientist
A specialization in other areas like artificial
intelligence, machine learning, data analysis,
database management, etc. might be useful
in knowing more about a particular field.
Choose a specialization
You must be aware of the basic programming
languages like Python and R. Data visualization,
data munging and data reporting are other
areas where you need to focus on if you
want to be good at your work.
Know the trends
There are several long- and short-
term courses on data science. Check
out Crampete's data science course.
Get a degree or certificate
The best way to get hands-on
experience in data science projects is
to start working with an organization that
deals with analytics, machine learning, or
artificial intelligence. Internships are a great
way to begin your career too.
Start working

9. Popular
Data Science
Tools
1. SAS programming language
2. Apache Spark
3. BigML
4. D3.js
5. Tableau
6. Jupyter
7. Matplotlib
8. NLTK
9. Scikit-learn
10. TensorFlow

10. Salary of a Data
Scientist in India?
Data scientists are one of the best-paid
professionals. The salary of a data scientist
in India is around 7LPA. The salary could
vary based on the location, employer,
experience, and education. With more
years of experience, income opportunities
increase as well.

11. Books that Every
Aspiring Data Scientist
Should Read
Think Stats: probability and statistics for
programmers by Allen B Downey
Introduction to statistical learning by Gareth James, Dan-
iela Witten, Trevor Hastie and Robert Tibshirani
Introduction to probability by J. Laurie Snell and Charles
Miller Grinstead
Deep learning with python by Franchois Chollet
Programming computer vision with python by Jan
Erik Solem
Fluent Python: clear, concise, and effective
programming by Luciano Romalho
R for data science by Garrett Grolemund and Hadley
Wickham
The Master Algorithm by Pedro Domingos
Mastering python for data science by Samir Madhavan
Modeling With Data by Ben Klemens