Data science is the study of data. It involves
developing methods of recording, storing,
and analyzing data to effectively extract
useful information. The goal of data science
is to gain insights and knowledge from any
type of data — both structured and unstructured.
There are 3 important sciences which are form
Data Science. These are:
Computer Science
Mathematical Statistics
Applications
There are four main components of data science:
Machine learning,deep,learning,data visualization
and statistics.
Machine learning is an application of (AI)
artificial intelligence that provides systems
the ability to automatically learn and improve
from experience without being explicitly programmed
Deep learning is a subset of machine learning
where artificial neural networks, algorithms
inspired by the human brain, learn from large
amounts of data
the next comes data visualization
Data visualization is the graphical representation
of information and data. By using visual elements
like charts, graphs, and maps, data visualization
tools provide an accessible way to see and
understand trends, outliers, and patterns
in data.
Statistics is a branch of applied mathematics
dealing with data collection, organization,
analysis, interpretation and presentation.
... ,In addition to being the name of a field
of study, the word "statistics" also refers
to, numbers, that are used to describe data
or ,relationships.
There is always a question in students mind
about which programming language to learn
for ,data science!!
Python is the programming language ,with simple
syntax, which is commonly used for data science!!
R !!!is the programming language which was
designed for statistians and data mining ,and
is optimised for, computing.
There are various frameworks like tensorflow
pandas pytorch and many more which are used
for turning data ,into actions.
So!!!!! where to practice data science problems?
You can either use anaconda navigator ,or
jupyter notebook,or we can use google colab
,that is much more faster for machine learning
problems.
Tableau and Power B I ,are generally used
in companies for data visualization purpose.
Apache Hadoop and spark are open-source software
frameworks for storing data and running applications
on clusters of commodity hardware.
The next comes Applications of Data science
in, human life.
first application is financial markets. Wherever
there is an immediate and ,tangible payoff
for, analytics, there you will find the most
cutting edge data analytics.
A close second is, gambling and betting!!!
The industry can be characterised by probability
and payoffs, at scale.
Retail banking!! Financial institutions deploy
a large spectrum of data Science ,whose footprint
is only increasing with time.
Healthcare and pharmaceutical!!Data Science
works across the value chain, from drug discovery
to clinical trials ,to manufacturing to sales
and marketing.
Recommendation systems !!! data science is
also use for recommending movies or shows
,or the topics in which one is interested.
There are many more applications which we
would discuss in detail in further lectures.
Then we move towards most interesting topic
that is salary.
According to ZipRecruiter, the median salary
for an experienced data scientist is $162,800—while
the median salary for an experienced manager-level
,data scientist is considerably higher ,at
$184,000.
According to Naukri.com one of the top Indian
job-seeking site, more than 50,000 data scientist
jobs are available in India.
According to PayScale, the average salary
of a Data Scientist in India is ₹708,012.
According to Indeed, the average salary of
a Data Scientist in Canada is $80,394 per
year.
Data is the omnipresent force ruling our lives
now and will be for the ,foreseeable future,
and data science jobs are booming like never
before. From the finance industry to the healthcare
and education sector, to banking, every sector
is opening up doors for data science professionals
,who can draw actionable insights ,from such
vast amounts of data!!!!!!Data Scientist and
Data science is always improving, and change
to a vast extent ,over the next ten years.
So Happy learning!!!!
and see you in the next video.
