Experfy
No Result
View All Result
  • Home
  • Future of Work
  • AI & Machine Learning
  • Big Data & Cloud
  • IoT & Automation
  • Software
  • ConsumerTech
  • HealthTech
  • FinTech
  • Home
  • Future of Work
  • AI & Machine Learning
  • Big Data & Cloud
  • IoT & Automation
  • Software
  • ConsumerTech
  • HealthTech
  • FinTech
No Result
View All Result
Experfy Insights
No Result
View All Result
Home Big Data & Cloud

Data Science Curricula Become Mainstream in Academia

Cameron Turner by Cameron Turner
August 28, 2015
in Big Data & Cloud
3 min read
0
Data Science Curricula Become Mainstream in Academia
Share on FacebookShare on Twitter

In the coming years, data scientists will be in high demand throughout the globe. Venture Beat reconfirmed FICO’s claim that job openings in data science took a giant leap by 15,000 percent between 2011 and 2012. During this data science market boom, fresh students with undergraduate and graduate degrees in disciplines intersecting with Data Science have a golden opportunity to land high paying jobs. The growing salaries and challenging job prospects are likely to attract a lot of bright students to this burgeoning field of study. As universities and the industry collaborate to design and develop coursework—appropriate for nurturing the students of data science or data analytics, a few marked trends have been noticed in the design of curricula.

The demand for skilled data scientists will continue to grow in the next five years, but the demand-supply gap will also continue to grow. To face this unique challenge, universities, in partnership with specific segments of the industry, have designed several types of courses that are equipped to fulfill both short-range and long-range demands.

Refer to this insightful infographic by Domo. According to the infographic provided below by 2016 the big data industry is expected to be a 53.4 billion industry.  By 2020, data scientist jobs are projected to increase by 18.7 percent.

Future Demand for Data Scientists

 

Future Demand for Data Scientists

 

Highly acclaimed academic programs

MIT, Stanford University, and the University of Southern California have all come up with their own versions of academic courses or programs in data science to prepare the future generation of data scientists. Industry leaders like Cloudera have tabled more realistic solutions by offering certificate programs in data science and machine learning. The certificate programs provide ample opportunity to students to leverage their knowledge in actual, real-world business problems such as creating big data strategies for the financial services sector. The following link provides a comprehensive list of degree or certificate programs in Data Science for an individual seeking more information: Degree or Certificate Programs in Data Science Offered by American Universities.

Academic coursework in data science: The types and formats

A review of the current program offerings reveals four types of coursework:

  1. Certification programs in big data (lasting between 6 to 12 weeks with exposure to real-world projects) for immediate fulfillment of demand in the industry
  2. Graduate level courses in data science, machine learning, algorithm modeling and so on for short-term fulfillment of demand in the industry
  3. Post-graduate level courses in Data Science integrated with full MBA programs for long-term fulfillment of demand in the industry
  4. Post-graduate degree courses in data science or analytics (MSA) for long-term fulfillment of demand in the industry

While most graduate-level courses are focused on providing skills in individual topic areas like statistical modeling, programming algorithms, big data analytics; these are often full-fledged degree courses in data science or analytics. The certification programs are the best substitute for internship work, as they expose the students to real-world projects. The certification programs or the graduate-level courses are more geared towards confronting the immediate demand for data science experts, whereas the post-graduate degree courses are probably aimed at fulfilling the future demand for data scientists. In another three to four years, the industry should receive a steady supply of fresh degree-holders from the data science discipline.

Tags: Big Data
Previous Post

Big Data Funding Rounds (July 14, 2014): Databricks, RetailNext, Luminoso, Amplitude

Next Post

Big Data Goes To The Movies

Cameron Turner

Cameron Turner

Next Post
Big Data Goes To The Movies

Big Data Goes To The Movies

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

POPULAR POST

  • A Comparison of Tableau and Power BI, the Two Top Leaders in the BI Market

    A Comparison of Tableau and Power BI, the Two Top Leaders in the BI Market

    11938 shares
    Share 4781 Tweet 2982
  • Insights to Agile Methodologies for Software Development

    3024 shares
    Share 1210 Tweet 756
  • Why You Should Forget Loops and Embrace Vectorization for Data Science

    2704 shares
    Share 1082 Tweet 676
  • Greedy Algorithm And Dynamic Programming

    2088 shares
    Share 835 Tweet 522
  • Cloudera vs Hortonworks vs MapR: Comparing Hadoop Distributions

    2080 shares
    Share 832 Tweet 520
Experfy Insights

Experfy Insights provides cutting-edge perspectives on Big Data and analytics. Our unique ability to focus on business problems enables us to provide insights that are highly relevant to each industry.

Join Us At

About Us

Contact Us


1700 West Park Drive, Suite 190
Westborough, MA 01581

Email: [email protected]

Toll Free: (844) EXPERFY or
(844) 397-3739

© 2020, Experfy Inc. All rights reserved.

No Result
View All Result
  • Home
  • Future of Work
  • AI & Machine Learning
  • Big Data & Cloud
  • IoT & Automation
  • Software
  • ConsumerTech
  • HealthTech
  • FinTech

© 2020, Experfy Inc. All rights reserved.