https://www.regenesys.in/newsroom/news-details/data-science-education-in-the-present

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Data Science Education in the Present
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Outline

• Motivation
• What is Data Science?
• Skill-set for Data Science
• Data Science Education
• Mathematics
• Data Science Job Search Terms (2018)
• Programming Languages
• Domain Expertise
• End Notes

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Motivation

• We are living in an ocean of data
• Internet of Things (IoT)
• Social media booming
• Many online transactions
• What value this data has?
• How do we extract this value?
• How can one interpret the results?
• What benefit the results have?
• for organization/business
• for the consumer

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What is Data Science?

• Data Science is a field that gives an
  organization the muscle power to
• process
• analyze
• derive insight
• take effective decisions

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What is Data Science?

• Data Science became very popular after 2012.
• Harvard Business Review called Data Science the
  most sought-after job of 21st century.
• Jim Gray, an American computer scientist
• Data Science a new paradigm of science
• Data Science provides students an opportunity
• to learn
• meet the rising demands of the industry for this
  particular subject

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Skill-set for Data Science

• A successful Data Scientist needs a unique set of
• analytical skills
• technical understanding
• business understanding
• to effectively work on massive data sets
• for actionable business insights
• Data Science is an interdisciplinary field,
  primarily consists of
• Mathematics
• Computer Science
• Domain Expertise
• All these disciplines are important in Data
  Science work.
• Optimal use of each of these disciplines has its
  own contribution for
• an optimal
• evolved Data Science product

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Data Science Education

• Data Science education has three main components
• Mathematics
• Programming Languages
• Domain Expertise

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Mathematics

• Mathematics for Data Science mainly comprise of
• Probability
• Statistics
• Multivariate Calculus
• Linear Algebra
• Discrete Mathematics
• This knowledge of mathematics is the basis for
  Data Science stages.
• Analysis
• Statistical testing
• Visualization
• Machine Learning
• Various skills are used as job search terms at
  job portals in 2018.

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Data Science Job Search Terms (2018)
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Programming Languages

• Programming languages formal education (started
  in 1960s).
• Different computer programming languages
• R programming
• Python
• SAS
• JAVA
• MATLAB
• SQL
• NoSQL
• Julia
• Ruby
• Scala
• C
• F
• Most in demand programming languages for Data
  Scientists in 2018.

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Programming languages (2018)
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Domain Expertise

• Domain Expertise is also very important in Data
  Science.
• Experts claim that Domain Knowledge is more
  important than any best-sophisticated Machine
  Learning algorithm.
• Data Scientist must understand the information
  that they are processing.
• Domain Expertise plays a crucial part in
• a good Feature Engineering
• Model quality is a function of features that we
  use to train a Machine Learning algorithm.
• Building models without domain knowledge
• a risky task
• result in a sub-optimal output of limited
  applicability

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Acquiring Domain Knowledge

• Finance
• Education
• Telecom
• Healthcare
• Retail
• Bio-Informatics
• Manufacturing Engineering
• Acquiring Domain Knowledge
• Data Science skill-sets should be flexible and
  transferable among domains.
• To boost ones domain knowledge
• Reading literature
• attending presentation
• Talking and asking questions to the domain
  experts

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End Notes

• Many institutes all over the world
• started offering programmes in Data Science
• At Regenesys we focus on
• the quality of education
• a strong emphasis on
• the domain expertise
• Feature Engineering
• Programming skills
• mathematical background
• ample practice on the real-life data sets from
  various businesses
• We are also emphasizing on the advanced topics in
  the Data Science.