Data Science - Training and Placement - Best Job Oriented IT Training Institutes and certification courses
Category Name : BigData / Hadoop
Certification Name : EMC Data Science Certification
Exam Id : E20-007
Number of Questions : 50
Passing Score : 70%
Time Limit : 60 minutes
Examination Format : MCQ
Count : 10
Duration: XX Classes | XX Hours | Weekdays: XX Days | Weekends: XX Days
Batch Timings: Mon-Fri: 30 Days | Sat-Sun (Weekend): 8 Weekends Mon-Fri: 9 AM to 11 AM | Sat-Sun (Weekend): 10 AM to 4 PM
Batch Schedule: Starts from 01-Sep-2017


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 from the sub domains of machine learning, classification, cluster analysis, data mining, databases, and visualization. The Data Science Certification Training enables you to gain knowledge of the entire Life Cycle of Data Science, analyzing and visualizing different data sets, different Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes.


This course is intended for Solutions Architects and Solution Design Engineers who wish to learn how to design and implement IT infrastructure solutions on Amazon Web Services platform.


There is no specific pr-requisite for the course.


  • Introduction to Data Sciences .
  • Statistical Inference
  • Data Extraction,Wrangling and Exploration
  • Introduction to Machine Learning
  • Classification
  • Unsupervised Learning
  • Recommender Engines.
  • Text Mining
  • Time Series
  • Deep Learning

Who can do this course

The course is suitable for upper-level undergraduate (or graduate) students in computer science,computer engineering, electrical engineering, applied mathematics, business, computational sciences, and related analytic fields.

Data Science or Big Data?

Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. Therefore persons working on this are mostly deal with processing and analyzing massive amounts of data.
On the other hand , Data scientists investigate complex problems through expertise in disciplines within the fields of mathematics, statistics, and computer science. These areas represent great breadth and diversity of knowledge, and a data scientist will most likely be expert in only one or at most two of these areas and merely proficient in the others.