Image of city at night with blue lazor lights

Posted on December 6, 2019 by Yash .

Discover how AI is transforming various industries in the future of work and how Colaberry is paving the way with its innovative solutions. Read our blog for insights.

Rapid technological innovations have been disrupting job markets since the First Industrial Revolution. The Fourth Industrial Revolution has accelerated the pace to unprecedented speed. Anticipating the trajectory of the changes and preparing for the workplace of tomorrow in the age of AI has become one of the most pressing global issues of our time. In 2016, the National Science Foundation (NSF) unveiled ten “Big Ideas” — ten distinct areas that would guide their research and investment strategy to position the United States as the global leader in science and engineering. The Future of Work at the Human-Technology Frontier was pronounced as one of them.

Continue reading “How To Thrive In The Future of Work With AI”

colaberry badges

Posted on December 3, 2019 by Yash .

Colaberry, an in-demand skills training and career transition provider, announced the launch of a new initiative to offer their learners a secure, portable, and trusted means to share and communicate their validated skills online through professional and social networks. Partnering with Credly, the digital credentials leader, Colaberry graduates will earn digital credentials that represent a range of technical and human skills gained by completing their data analytics and data science programs.

“Colaberry’s digital credentials give our graduates an effective tool to signify to prospective employers that they are prepared to begin delivering immediately on in-demand skills,” said Ram Katamaraja, Founder and CEO of Colaberry. “Together, we are bringing transparency to candidates’ capabilities that make it easier for employers to discover technology talent with the skills they need in today’s tight labor market.”

Through this new partnership, Colaberry graduates will receive digital credentials hosted on Credly’s Acclaim platform. Credential holders can use this verified record of their specific skills and knowledge to differentiate themselves from other professionals in their fields. Employers can, in turn, identify holders of in-demand credentials who have verified skills and expertise. This additional layer of recognition allows employers to better understand what applicants know and can do.

“The tech skills Colaberry develops— from data analysis to machine learning — are among the most in-demand skills today,” said Jonathan Finkelstein, CEO of Credly. “By providing digital credentials to its graduates, Colaberry is demonstrating to employers the skills their student has learned, in a way that can be quickly validated.”

About Colaberry

Colaberry has been providing one-of-a-kind, career-oriented training in data analytics and data science since 2012. Our training offerings include self-paced, instructor-led onsite, and instructor-led online classes. We have helped over 5,000 people to transform their lives with our immersive boot camp-style programs.

About Credly 

Credly is helping the world speak a common language about people’s knowledge, skills, and abilities. Thousands of employers, training organizations, associations, certification programs, and workforce development initiatives use Credly to help individuals translate their learning experiences into professional opportunities using trusted, portable, digital credentials. Credly empowers organizations to attract, engage, develop, and retain talent with enterprise-class tools that generate data-driven insights to address skills gaps and highlight opportunities through an unmatched global network of credential issuers.

For more information contact: 

Ram Katamaraja

CEO and Co-founder of Colaberry

(617) 444-9689

or

[email protected].

Colaberry Attends The Women in Data Science Conference

Posted on November 19, 2019 by Yash .

This weekend, Vivian Rebrin was able to attend the second annual Women in Data Science Conference in St. Louis. The event took place in Washington University’s Emerson Auditorium. My colleague David Freni and I met some data scientists who work with our client Bayer Crop Science. We were able to listen to several women working in the industry, as well as Washington University’s Professor Liberty, describe the dangers of manipulating data for self-interest and the importance of asking the right questions. The main subject that stuck out to me was the manipulation of data. The two main brands that were affected by this in her examples were Starbucks and Uber. Each of these had their data distorted to sabotage their reputations. Her conclusion for the women in data science and entering it was to always ask these four questions when looking for results. Who was asked? What was asked? How was it interpreted? Why do we care? In the world of science, it is important to maintain humanism.

Continue reading “Colaberry Attends The Women in Data Science Conference”

Colaberry Alumni Event Celebrates Achievements of Graduates

Posted on October 29, 2019 by Yash .

If you have read any of our past Alumni Success Stories (homelessness survivor Mika Hopson, military veteran Adrian Lujo, or teacher turned data rockstar Addie Mack), you’ll know that this alumni event would be well-attended and feature some of the most amazing life transitions you could ever hear.

Continue reading “Colaberry Alumni Event Celebrates Achievements of Graduates”

Posted on September 20, 2018 by Yash .

Refactored AI: Innovative Solution from Colaberry Labs Emerges as Finalist in SOLVE @ MIT Global Competition

Voting for the MIT SOLVE competition has ended, please visit http://training.colaberry.com for more exciting information about Colaberry Labs.

 

 Refactored.ai: Innovative Solution from Colaberry Labs Emerges as Finalist in SOLVE @ MIT Global Competition

Continue reading “Refactored A Finalist in SOLVE MIT Global Competition”

Posted on June 29, 2017 by Yash .

Data Science

Data Science, also known as data-driven science, is an interdisciplinary field of scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.

Data Science is a “concept to unify statistics, data analysis, and their related methods” to “understand and analyze actual phenomena” with data. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, in particular from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization.

data science

An Explosion of Data

Data is increasingly cheap and ubiquitous. We are now digitizing analog content that was created over centuries and collecting myriad new types of data from web logs, mobile devices, sensors, instruments, and transactions. IBM estimates that 90 percent of the data in the world today has been created in the past two years.

At the same time, new technologies are emerging to organize and make sense of this avalanche of data. We can now identify patterns and regularities in data of all sorts that allow us to advance scholarship, improve the human condition, and create commercial and social value. The rise of “big data” has the potential to deepen our understanding of phenomena ranging from physical and biological systems to human social and economic behavior

A Challenge Identified

Virtually every sector of the economy now has access to more data than would have been imaginable even a decade ago. Businesses today are accumulating new data at a rate that exceeds their capacity to extract value from it. The question facing every organization that wants to attract a community is how to use data effectively — not just their data, but all of the data that are available and relevant.

Our ability to derive social and economic value from the newly available data is limited by the lack of expertise. Working with this data requires distinctive new skills and tools. The corpora are often too voluminous to fit on a single computer, to manipulate with traditional databases or statistical tools, or to represent using standard graphics software. The data is also more heterogeneous than the highly curated data of the past. Digitized text, audio, and visual content, like sensor and blog data, is typically messy, incomplete, and unstructured; it is often of uncertain provenance and quality; and frequently must be combined with other data to be useful. Working with user-generated data sets also raises challenging issues of privacy, security, and ethics.