Data Science Course Eligibility

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Data Science Course Eligibility
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Introduction

• This course made for anyone who wants to learn
  it, whether they are new or professional. One can
  go for a bachelors degree in Data Science after
  class 12. They should have a background in
  science, and it can be an additional benefit to
  having computer programmes in high school. The
  percentage needed to accept admission, however,
  depends on the institution. A new graduate from a
  recognised university may also opt for either a
  masters degree in Data Science in the relevant
  discipline. A PG Diploma in Data Science may be
  carried out by working professionals with a
  similar background. Data Science also has several
  online certification programmes.

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Data Science Course Eligibility

• Data scientists are highly educational. 88 have
  at least a Masters degree and 46 have PhDs. And
  although there are notable exceptions, it
  requires a very strong educational background to
  develop the level of knowledge necessary to be a
  data scientist. You could obtain a Bachelors
  degree in Computer Science, Social Sciences,
  Physical Sciences, and Statistics to become a
  data scientist. Mathematics and Statistics (32
  per cent), followed by computer science (19 per
  cent) and engineering (16 per cent), are the most
  common fields of study. A degree in each of these
  courses will provide you with the skills to
  process and analyse big data that you need. The
  fact is that most data scientists have a Masters
  or Ph. D degree and often undergo online training
  to learn a special ability such as how to use
  Hadoop or Big Data querying. You may then apply
  for a masters degree in Data Science,
  Mathematics, Astrophysics or any other related
  area. During your degree programme, the skills
  you have gained will help you to easily
  transition to data science. You can practise what
  you learned in the classroom, apart from
  classroom learning, by creating an app, starting
  a blog or exploring data analysis to enable you
  to learn more.

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Course Pre-requisites

• Data Analytics stakeholders should have some
  previous experience in (or be prepared to work
  with) Mathematics Basic
• Statistics (working with statistical methods and
  numbers)
• For anyone with a degree in social and natural
  sciences, engineering, mathematics, art and
  others, this course is well adapted.

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Skills required

• For data analytics, as a programming language, as
  an environment for statistical analysis, data
  visualisation, in-depth information in R R is
  used. Other skills that are required are
• Python coding 
• mathematical models and concepts are primarily
  preferred to Python since Python has rich
  libraries/packages to construct and deploy
  models.
• MS Excel
• For all data entry work, Microsoft Excel is
  considered a basic requirement. In data
  processing, applying formulae, equations,
  diagrams from a messy tonne of data is of great
  benefit.

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• Hadoop Platform
• It is a distributed computing system that is open
  source. It is used for the management of big data
  applications for processing and storage.
• SQL database/coding
• It is primarily used for dataset preparation and
  extraction. It can also be used for issues such
  as graphics and network analysis, search
  activity, detection of fraud, etc.
• Technology
• Because there is so much unstructured knowledge
  out there, one should know how to access the
  information as well. This can be done through AP
  in a variety of ways

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• Techniques required
• Along with the skills, students require some
  techniques as well. Mathematical Expertise
• Data scientists often work on machine learning
  algorithms that require a very large amount of
  mathematical knowledge, such as regression,
  clustering, time series, etc., since they
  themselves are based on mathematical algorithms.
• Working with unstructured data
• Since most of the data created each day is
  unstructured in the form of photos, comments,
  tweets, search history, etc., knowing how to turn
  this unstructured into a structured form and then
  work with them is a very useful ability in
  todays market.

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About Data Science Course

• This course intends for learners who do not have
  prior data analytics experience. It targets to
  gain these skills in a short period of time.
  These students will learn how to evaluate broad
  data sets and find trends that will enhance the
  decision-making process of any business or
  organisation. After completing the course, they
  will be able to Capturing, classifying,
  simplifying, normalising and preparing data for
  processing.
• Working with and evaluating huge sets of data.
• Reflect the findings of the study visually to
  professional and non-technical audiences.
• Use the most common algorithms to make sense of
  vast quantities of information. They are
  important to most business and management issues.
• You will have a professional portfolio of
  projects at the end of the programme. Alongside
  you will have real experience with data
  analytics. This will give you the confidence
  required to be successful as a data analyst.