Data Science For Beginners [2023]
Introduction to Data Science
Data science is a fascinating field with a high demand for skilled
professionals. In this full course on data science, we will cover
everything about data science from end to end. Before we get
started, make sure to hit the like button and subscribe to our
channel for regular updates. We also offer training programs and
certification courses, so check out the links in the description if
you're interested. Let's take a look at the topics we'll be covering
in this video:
What is Data Science?
Who is a Data Scientist?
Roadmap to Becoming a Data Scientist
Data Science Core Concepts (Total Life Cycle, Statistics
and Probability, Machine Learning, Core Algorithms, Deep
Learning)
Data Science for Non-Programmers
Bonus Sections (Creating a Data Scientist Resume, Data
Science Interview Questions and Answers)
Now, let's dive into what data science is all about.
What is Data Science?
With the development of new technologies, there has been a
rapid increase in the amount of data. This has created an
opportunity to analyze and derive meaningful information from all
this data. Technically, data science is defined as the process of
extracting knowledge and insights from complex and large sets of
data by using processes like data cleaning and data visualization.
For example, Google Maps collects data every day from a
multitude of reliable sources, primarily smartphones. It
continuously combines the data from drivers, passengers, and
pedestrians and then uses machine learning algorithms to send
real traffic updates by way of colored lines on the graphic layers.
This helps you find your optimal route and even determine which
areas should be avoided due to road work or accidents.
, As data science continues to evolve, the demand for skilled
professionals in this domain is also increasing drastically. In order
to uncover useful intelligence for their organizations, data
scientists must master all the aspects of data science.
How Data Science is Used
Data science is all about extracting useful insights from data and
using it to grow your business. Walmart, for example, is building
the world's biggest private cloud, which will be able to process
2.5 petabytes of data every hour. The reason behind Walmart's
success is how they use customer data to get useful insights
about customers' shopping patterns. The data analysts and data
scientists at Walmart know every detail about their customers.
They use the data that they get from their customers and analyze
it to see what a particular customer is looking for. For instance,
during Halloween sales, an analyst at Walmart found out that a
specific cookie was popular across all Walmart stores, but two
stores were not selling them at all. The situation was immediately
investigated, and it was found that there was a simple stocking
oversight because of which the cookies were not put on the
shelves for sale. Another example is that through association rule
mining, Walmart found out that strawberry poptart sales
increased by seven times before a hurricane.
With the emergence of the internet and the increasing amount of
data generated, we need more complex algorithms and a better
process to process this data. This is where data science comes in.
It helps us extract useful insights from data and use them to grow
our businesses.
How Walmart Uses Data Science to Improve
Their Business
Walmart is known for its successful business strategies, and one
of the main reasons for their success is the huge amount of data
they collect and analyze. They use social media data to find out
the trending products and customer preferences. Walmart invests
a lot of time, effort, and money in analyzing data to find any
hidden patterns or associations between products. Once they find
Introduction to Data Science
Data science is a fascinating field with a high demand for skilled
professionals. In this full course on data science, we will cover
everything about data science from end to end. Before we get
started, make sure to hit the like button and subscribe to our
channel for regular updates. We also offer training programs and
certification courses, so check out the links in the description if
you're interested. Let's take a look at the topics we'll be covering
in this video:
What is Data Science?
Who is a Data Scientist?
Roadmap to Becoming a Data Scientist
Data Science Core Concepts (Total Life Cycle, Statistics
and Probability, Machine Learning, Core Algorithms, Deep
Learning)
Data Science for Non-Programmers
Bonus Sections (Creating a Data Scientist Resume, Data
Science Interview Questions and Answers)
Now, let's dive into what data science is all about.
What is Data Science?
With the development of new technologies, there has been a
rapid increase in the amount of data. This has created an
opportunity to analyze and derive meaningful information from all
this data. Technically, data science is defined as the process of
extracting knowledge and insights from complex and large sets of
data by using processes like data cleaning and data visualization.
For example, Google Maps collects data every day from a
multitude of reliable sources, primarily smartphones. It
continuously combines the data from drivers, passengers, and
pedestrians and then uses machine learning algorithms to send
real traffic updates by way of colored lines on the graphic layers.
This helps you find your optimal route and even determine which
areas should be avoided due to road work or accidents.
, As data science continues to evolve, the demand for skilled
professionals in this domain is also increasing drastically. In order
to uncover useful intelligence for their organizations, data
scientists must master all the aspects of data science.
How Data Science is Used
Data science is all about extracting useful insights from data and
using it to grow your business. Walmart, for example, is building
the world's biggest private cloud, which will be able to process
2.5 petabytes of data every hour. The reason behind Walmart's
success is how they use customer data to get useful insights
about customers' shopping patterns. The data analysts and data
scientists at Walmart know every detail about their customers.
They use the data that they get from their customers and analyze
it to see what a particular customer is looking for. For instance,
during Halloween sales, an analyst at Walmart found out that a
specific cookie was popular across all Walmart stores, but two
stores were not selling them at all. The situation was immediately
investigated, and it was found that there was a simple stocking
oversight because of which the cookies were not put on the
shelves for sale. Another example is that through association rule
mining, Walmart found out that strawberry poptart sales
increased by seven times before a hurricane.
With the emergence of the internet and the increasing amount of
data generated, we need more complex algorithms and a better
process to process this data. This is where data science comes in.
It helps us extract useful insights from data and use them to grow
our businesses.
How Walmart Uses Data Science to Improve
Their Business
Walmart is known for its successful business strategies, and one
of the main reasons for their success is the huge amount of data
they collect and analyze. They use social media data to find out
the trending products and customer preferences. Walmart invests
a lot of time, effort, and money in analyzing data to find any
hidden patterns or associations between products. Once they find
