Colaberry Alumni Success Story Roundup
Throughout 2019, we have brought you many different Alumni Success Stories. Since we are rounding out the year, we wanted to share five amazing Colaberry Alumni Success Stories in this roundup post.
Data Science & AI Consulting & Staffing Solutions
Throughout 2019, we have brought you many different Alumni Success Stories. Since we are rounding out the year, we wanted to share five amazing Colaberry Alumni Success Stories in this roundup post.
Learn how Fred accelerated his career in data analytics with Colaberry’s boot camp. Gain insights on his journey to success. Read now!
Continue reading “Fast-Tracking Career with Colaberry Data Analytics Bootcamp”
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”
Meet Colaberry’s exceptional leaders and mentors honored for their amazing contributions. Inspiring stories of impact and empowerment inside.
Since Colaberry’s inception, we have transformed the lives of thousands of people who had a dream to build a better future, career, and life for themselves and their families. That kind of change doesn’t happen easily and you can’t do it alone.Â
We are so proud of the hard work that our mentors, instructors, and teaching assistants have done to improve the lives of people around the world and for sharing their professional skills, talents, and passion with our community of students and alumni.
Learn more about Colaberry Training & Development Programs
Your dedication, commitment to student success, and hard work make magic happen!
We are pleased to honor the following outstanding Colaberry leaders:Â
Mika HopsonÂ
Abdullah MamunÂ
Addie WrightÂ
Josiane De Biyong OutlawHwk outlawÂ
Alex GibsonÂ
Chantal TA TogbeyÂ
Keba FrederickÂ
Balaram KasulaÂ
Ayad KashmoolaÂ
Alex SharifianÂ
Dozie UchegbulamÂ
Mohammed Alhaddad
Wajid Dawood
Colby OrrÂ
Ngiri YvetteÂ
Brandon SmithÂ
Pierre EheÂ
Moe KazemiÂ
Anthony ObidiakuÂ
Jonathan Bynder
Shruti Alladi,Â
Sowmya Attur
We invite you to check out our Facebook page where we’ve collected some great photos of our Colaberry leaders at this exciting event.Â
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”
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 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
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.