How to make confident decisions using Data Science – IQ Online Training - PowerPoint PPT Presentation

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How to make confident decisions using Data Science – IQ Online Training

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Data Science has been a Buzzword and it is going to stay with us for a much longer time in different forms. Get Data Science Training with the much-updated curriculum at IQ Online Training. – PowerPoint PPT presentation

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Title: How to make confident decisions using Data Science – IQ Online Training


1
How To Make Confident Decisions Using Data
Science?
Call Us 1 732-593-8450, 91-9989527180 Email
info_at_iqtrainings.com
IQ ONLINE TRAINING
2
Quality of Data is always important than Quantity
  • If the quality of the input is of low quality,
    even the best predictive model could show the
    worst results, which are not reliable. So first,
    we need to understand, the quality of data is
    more important than gathering more data. To
    evaluate the data whether it is accurate,
    complete and consistent, we need to know from
    where and how it came together.

3
Learn Skills For Tomorrow
  • Data literacy is one of those skills, which is
    necessary for almost everyone in the digital age.
    The employees of an organization should be
    prepared for tomorrow by improving their skills
    of understanding, analyzing, and most importantly
    questioning data.
  • Some employees may fear for change of a cultural
    shift but they need to be educated about the
    importance of learning data literacy. The
    importance of including Artificial Intelligence
    (AI) in the workplace to support their role has
    to be made clear. Once implemented and we start
    seeing changes, organizations need to take
    feedback and be ready for the open challenges.

4
Learn And Upgrade By Doing
  • Although organizations train their employees to
    hone skills, they need to participate in other
    ways of learning as well such as blogs, webinars,
    video playlists, etc. These fill them with
    confidence in the new technology.
  • The technology should be learned to use as a part
    of their work culture but should not feel like an
    extra burden by the employees. The aim should not
    be to turn a companys marketing team or
    accountants into Data Scientists but enhance
    their skill set with the technology in their
    particular role.

5
  • With the knowledge of Data Science or Artificial
    Intelligence, an employee can analyze and
    interpret enterprise data avoiding any ambiguity.
    Natural language processing helps users in
    finding answers through a search-engine like an
    experience.
  • The new technology might be of use in little
    things but very useful things that reduce the
    work. It could be a small machine-generated
    alert, but once the user gets the correct
    forecast and benefits from the insights, his
    confidence in the technology grows and curiosity
    to learn increases.

6
Start Small Go Big
  • Small things matter a lot. Even a small feature
    in AI can give greater insight. A small and
    innovative project in AI could turn into success
    and can then scale it up across the entire
    enterprise. For this to happen, the right
    employees in the team are much necessary. A
    person with the right mindset to identify
    problems and test hypothesis are better than with
    a good understanding of the algorithm.
  • A curious, self-motivated who like to try and
    fail frequently can do the work better in data
    science technology. Such employees would decipher
    the mystery of data science and help enhance the
    projects in the organization.

7
Go With The Right Approach
  • Data Science techniques are complex and most
    time-consuming. Therefore, buying pre-trained AI
    models that suit your needs and could automate
    complex processes could be a better idea.
    Choosing the right solution will help users about
    the data science process and the factors
    considered during the model creation. It creates
    transparency about the reliability and accuracy
    to the users and helps them in understanding the
    steps in the process that fail and how to rectify
    them. In such a process of corrections, users
    will adopt the best practices for the
    implementation.

8
  • Even though Data Science is based on logical
    thinking and mathematics, there is never a single
    right answer, since there are many approaches to
    a single problem or a question. The key is to
    find a solution that fits everyone by conducting
    various experiments and improving continuously.
    The entire process is to create a trust between
    machine learning models and the users by
    delivering valuable information to the business.

9
Thank You
IQ Online Training
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