Data Science is the most revolutionary technology of the era. It 's all about
deriving useful insights from data in order to solve real-world complex problems.
The first module is an reduction to data science that covers all the basic
fundamentals of data science followed by this. The next module is the supervised
learning algorithms module where we 'll start by understanding the most basic With
them or which is linear regression. We 'll discuss how Walmart is using insightful
patterns from their database to increase the potential of their business. After
that. We will see what exactly data science is, then we 'll move on and discuss who
are data scientist is where we will also discuss the various skill sets. After this
we will discuss how data is extracted processed and finally use as a solution.
We'll discuss a use case of the k-means clustering after which we can move on to
see the various data science job roles such as data analyst data architect data
engineer. We produce 2. 5 quintillion bytes of data each day. And this is only
accelerating with the growth of iot or Internet of Things. iot data is measured in
zettabytes and one zettabyte is equal to trillion gigabytes. According to a recent
survey by Cisco. It 's estimated that by the end of 2019 the iot will generate more
than five hundred zettbles of data per year. This number will only increase through
time.
Social media is generating a lot of data for us. Data science is a simple process
that will just extract the useful information from data. Walmart is the world 's
biggest retailer with over 20,000 stores in just 28 countries. We pay bills online.
We even buy homes online these days you can even sell your pets on oil excuses.
Walmart is currently building the world 's biggest. Good Cloud, which will be able
to process two point five petabytes of data every hour now. The reason behind
Walmart success is how the user customer data to get useful insights about
customers shopping patterns. Walmart found out that strawberry Pop-Tart sales
increased by seven times before a hurricane. Walmart uses data in a very effective
manner the analyzer very well. They process the data very well and they find out
the useful insights that they need in order to get more customers or improve their
business. Netflix analyzes the movie viewing patterns of users to understand what
drives user interest and to see what users want to watch.
There are actually many machine learning algorithms which are based on linear
algebra. So guys overall you need to have a good understanding of math and apart
from that data scientist. Eli 's technology. So data scientists have to be really
good with technology. It is also important for a data scientist to be a tactical
business consultant. Programming languages is a must at the minimum. You should
know our or python and a database query language now. Data extraction and
processing is all about getting data. From these different data sources and then
putting it in a format so that you can analyze it now next is data wrangling and
exploration. There are many job roles under data science. Data scientists have to
understand business and offer the best solution using data analysis and data
processing. Data visualization is one of the most important part of data analysis.
The challenge is over business and they have to offer best solution. Data is being
generated at an Unstoppable Pace.
A data analyst is responsible for a variety of tasks including visualization
processing of massive amount of data and among them. They have to also perform
queries on databases. A data architect creates the blueprints for a data management
so that the databases can be easily integrated centralized and protected. They also
ensure that the data Engineers have the best tools and systems. A business analyst
acts like a link between the data engineers and the management Executives. A data
deriving useful insights from data in order to solve real-world complex problems.
The first module is an reduction to data science that covers all the basic
fundamentals of data science followed by this. The next module is the supervised
learning algorithms module where we 'll start by understanding the most basic With
them or which is linear regression. We 'll discuss how Walmart is using insightful
patterns from their database to increase the potential of their business. After
that. We will see what exactly data science is, then we 'll move on and discuss who
are data scientist is where we will also discuss the various skill sets. After this
we will discuss how data is extracted processed and finally use as a solution.
We'll discuss a use case of the k-means clustering after which we can move on to
see the various data science job roles such as data analyst data architect data
engineer. We produce 2. 5 quintillion bytes of data each day. And this is only
accelerating with the growth of iot or Internet of Things. iot data is measured in
zettabytes and one zettabyte is equal to trillion gigabytes. According to a recent
survey by Cisco. It 's estimated that by the end of 2019 the iot will generate more
than five hundred zettbles of data per year. This number will only increase through
time.
Social media is generating a lot of data for us. Data science is a simple process
that will just extract the useful information from data. Walmart is the world 's
biggest retailer with over 20,000 stores in just 28 countries. We pay bills online.
We even buy homes online these days you can even sell your pets on oil excuses.
Walmart is currently building the world 's biggest. Good Cloud, which will be able
to process two point five petabytes of data every hour now. The reason behind
Walmart success is how the user customer data to get useful insights about
customers shopping patterns. Walmart found out that strawberry Pop-Tart sales
increased by seven times before a hurricane. Walmart uses data in a very effective
manner the analyzer very well. They process the data very well and they find out
the useful insights that they need in order to get more customers or improve their
business. Netflix analyzes the movie viewing patterns of users to understand what
drives user interest and to see what users want to watch.
There are actually many machine learning algorithms which are based on linear
algebra. So guys overall you need to have a good understanding of math and apart
from that data scientist. Eli 's technology. So data scientists have to be really
good with technology. It is also important for a data scientist to be a tactical
business consultant. Programming languages is a must at the minimum. You should
know our or python and a database query language now. Data extraction and
processing is all about getting data. From these different data sources and then
putting it in a format so that you can analyze it now next is data wrangling and
exploration. There are many job roles under data science. Data scientists have to
understand business and offer the best solution using data analysis and data
processing. Data visualization is one of the most important part of data analysis.
The challenge is over business and they have to offer best solution. Data is being
generated at an Unstoppable Pace.
A data analyst is responsible for a variety of tasks including visualization
processing of massive amount of data and among them. They have to also perform
queries on databases. A data architect creates the blueprints for a data management
so that the databases can be easily integrated centralized and protected. They also
ensure that the data Engineers have the best tools and systems. A business analyst
acts like a link between the data engineers and the management Executives. A data
