As data science is a newly evolving field, many professionals have been caught unaware by the vast gap in what the industry demands and what the average data science professionals can deliver.
Unfortunately, the technology has evolved faster than the workforce skills to make sense of it and organizations across sectors must adapt to this new reality or perish, says Andreas Weigend, Ph.D Stanford, Head of the Social Data Lab at Stanford, former Chief Scientist at Amazon.com.
If you happen to be a data professional who broke into the field from a technical discipline other than data science or data analytics, then you may be interested in exploring online courses or tutorials which can effectively augment your existing knowledgebase quickly; without requiring much time commitments. A separate post discusses the academic degree courses available in data science, but this post focuses more on just-in-time training for working professionals in the field of big data, who may need to supplement their knowledge and training without entering the traditional classroom.
The big data educational sites mentioned here promise to expand your depth of knowledge and practical training in big data technologies. The basic objective of the listed courses is to provide opportunities for self-training while balancing a busy, professional schedule.
EMC Data Science and Big Data Analytics
Although many of the available online courses are high priced, the courses on data science and big data analytics include hands-on training and certification to add to a professionals existing credentials. IDC believes the courses available here are a positive step to help both the industry and businesses move forward and quickly take advantage of the benefits that the cloud and Big Data present.
CALTECH Learning from Data
Learning from Data is available at Caltechs educational site as one of the online courses on Machine Learning. Divided into eighteen 60-minute lectures, the course content attempts to balance theory and practice. Reinforced with mathematical modeling exercises and taught by a professor at Caltech, this course offers the convenience of self-paced learning without diluting the quality of instruction. The courses which were live broadcast from Caltech in Summer 2012 have been captured in a video library for the benefit of professional data scientists. It combines theory, practical analyses, and mathematical modeling for better understanding of the topic.
Big Data University Open Courseware
At Big Data University, both novice or seasoned Hadoop professionals can learn and contribute among the growing bunch of big data enthusiasts. This platform provides a perfect opportunity to network with other professionals! The big data community that has evolved around this online portal includes members of the academia, students, professionals, and even companies like IBM and Jaspersoft. This online university seeks to share big data education with the wide community of data scientists or professionals already engaged in the big data analytics industry.
The course content has been created by experienced teachers or professionals, and the bulk of the curriculum is available free! It has been designed with explorative discovery in mind; the students can use the practical lab sessions to simulate actual situations. The growing Facebook community associated with this site is a key indicator of the sites popularity and effectiveness as a teaching platform. The curriculum includes courses like Data Warehousing and Analytics for Everyone and Hadoop Fundamentals I and II.
Predictive Analytics World Introductory Course
A course called Predictive Analytics Applied An Online Introduction targets the technology leaders or managers for a high-level overview of predictive analytics. The registrants will enjoy three months access to the four training modules, so that busy managers can pace through the learning sessions according to personal convenience. Unlike other data mining or analytics courses, this workshop is geared towards solving actual business and marketing problems.