Making a Successful Career in Data Science - PowerPoint PPT Presentation

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Making a Successful Career in Data Science

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Start a Successful Career in Data Science with the Leading IT Training Institute in Pune & Mumbai. Contact Now. – PowerPoint PPT presentation

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Date added: 1 June 2022
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Title: Making a Successful Career in Data Science


1
Making a Successful Career in Data Science
2
  • Data Science, Analytics, Artificial Intelligence,
    Machine Learning nowadays, we keep on hearing
    these terms quite often. There is a lot of
    glamour associated with them. Many are aspiring
    to make a career in Data Science. Why data
    science is gaining so much popularity?
  • It is said that todays world is of data and
    information. We produce and consume so much data.
    For example, we use social media. We cannot
    imagine a day without a mobile phone and without
    social media- Facebook, Twitter, YouTube,
    Snapchat, WhatsApp, Pinterest, and so on. People
    are using social media for sharing photos,
    videos, documents, communicating, commenting,
    etc., Almost every business creates a website.
    Data consumption is increased tremendously after
    the exponential growth of Mobile phones. And this
    will keep on growing further, thanks to more
    advanced technologies like the Internet of
    things(IoT).

3
  • Every day, roughly we create 2.5 quintillion
    bytes of data. With the growing popularity of
    IoT, this data creation rate will become even
    greater. seedscientific.com
  • Career in Data Science More and More Data
  • Here are some interesting numbers to give you an
    idea of the data we end up generating every day,
    every minute, and every second. Every minute,
    Google does 5,700,000 searches Every minute,
    Instagram users post 65,000 photos Every
    minute, YouTube 694000 Hours streaming video
    Every minute, Zoom hosts 856 Minutes of Webinar
    Every minute, Snapchats shared 2000000 chatsAnd
    the list continues

4
  • That is really mind-boggling! We are aware that
    now we use so much data daily. But why we are
    discussing all this? What can be done with this
    data? Is it really useful to study this large
    data to get something interesting for business?
  • And the answer is a big YES. Let us look at
    what it means by studying this data or the
    science of it.

5
  • Career in Data Science, understand what it is!
  • When you visit search on the internet or talk to
    people, you will hear the following terms very
    often. These terms which are in fashion right now
    are data science, data analytics, machine
    learning, deep learning, big data, etc. Without
    really understanding the meanings of these terms,
    it is not possible to understand data science.

6
  • Let me simplify this for you from the perspective
    of the job roles or tasks. To process a very
    large volume of data to discover new insights is
    the main function of Data Science. Data
    warehousing, Data mining were the terms used for
    this kind of computing. However, in recent years
    it got more glamourized in the name of data
    science or machine learning.
  • We can call Data science the big domain which
    encompasses everything. In this domain, at a very
    high level, there are two types of tasks one is
    to clean and prepare the data and the other is to
    analyze the data for insights.

7
  • Engineering the Data
  • An important step before analyzing the data is to
    clean it and prepare for the next step. It is
    called Data Engineering. Data from various
    sources is collected, processed, cleansed,
    transformed, and stored in different ways. This
    includes everything from the file system,
    databases, data warehouses, and NO-SQL databases.
    In addition, the big data processing mechanisms
    like Map Reduce, PIG, HIVE, etc., data wrangling
    also comes in this category.
  • To process data, you must have skills in
    Databases, SQL, and Programming languages like
    Python and/or a set of tools that are part of a
    big data system like Hadoop.

8
  • Data Analytics
  • This section contains tools and technologies
    which are used to process and view data in
    different ways. Statistical analysis is done
    using different statistical tools and algorithms.
    These generate insights or patterns. Using these
    insights, businesses can take vital decisions
    like how much to order, how to arrange goods on
    the shelf of a big store, and whether to give a
    loan or not to a particular applicant? This is
    what you learn in a data science certification
    course.

9
  • Learning Data Science Python/R Programming
  • Data engineering being more focused on data
    processing or programming may be of more interest
    to computer graduates. On the other hand, data
    analytics being statistically oriented may
    attract students from other science disciplines.
    But the bottom line is one has to have a fair
    knowledge of both to do well in a career.

10
  • Starting step could be learning Python and R
    Programming. Recently Python has become popular
    because of the availability of a large number of
    readymade libraries for data science algorithms.
    If you want to pursue a Data science course, make
    sure that it teaches you statistical concepts,
    Python/R Programming, and then various machine
    learning algorithms with a project.
  • Why wait, take a step and enroll in a Python
    Programming course at Texceed!

11
  • Conclusion
  • Start a Successful Career in Data Science with
    the Leading IT Training Institute in Pune
    Mumbai. Contact Now.

12
  • THANK YOU
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