Data science is the study of the generalizable extraction of knowledge from data, yet the key word is science. It incorporates varying elements and builds on techniques and theories from many fields, including signal processing, mathematics, probability models, machine learning, statistical learning, computer programming, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. Data Science is not restricted to only big data, although the fact that data is scaling up makes big data an important aspect of data science.
The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data.
1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts wanting to understand Machine Learning (ML) Techniques
5. Information Architects wanting to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies
9. Statisticians looking to implement the statistics techniques on Big data
Contact us: To customize this class with your own dates, times and location. You can also call
"I've been to a different training facilities for other technologies, and this is one of the few where I've left feeling like I've learned more than I expected.
Eduardo Moreno, USA