Exam E20-065: Advanced Analytics Specialist Exam for Data Scientists - Version 1.0

Data scientists who have successfully attained the certification for Associate Level in Data Science, can take the Advanced Analytics Specialist Exam, of code E20-065. To attain the Specialist Certification via this E20-065 Exam, the candidates will have to sit through 60 questions for a total of 90 minutes. They will need to manage a score of 63 to pass.

It would not be difficult for the candidates to manage a score like that, for there several resources available online to facilitate their preparation. The candidates can purchase the E20-065 Training Guides and study kits which contain extensive material on every exam topic. Additionally, brain dumps can also be bought online, for they contain E20-065 Real Exam Questions and detailed answer explanations to ensure a competitive score.

Following are the Sections of the Exam:

Section 1- MapReduce:

This section will constitute 15% of the E20-065 Exam PDF. It will test the candidates’ prowess in areas of outlining the framework and implementing MapReduce in Hadoop, usage of Hadoop Distributed File System (HDFS), and employment of Yet Another Resource Negotiator (YARN).

Section 2 - Environment of Hadoop, and NoSQL:

The candidates need to be familiar with Hive, Pig, NoSQL, HBase and Spark in order to secure the 15% of the aggregate marks allocated to this section of the exam.

Section 3 - Natural Language Processing:

The test takers need to be well acquainted with the basics of the four categories of ambiguity, using Natural Language Processing, processing of text, and modelling of language. Having an in-depth understanding of the aforementioned topics will award the candidates with 20% of the exam total.

Section 4 - Scrutiny of Social Networking:

The candidates need to familiar with the concept of social networking, implications of Graph Theory, and the interconnection of communities. They also need to have a understanding of the rudimentary problems and issues with networking, and the uses of the SNA (Social Networking Analysis) tools, to pocket the 23% of the total marks weighted to this section.

Section 5 - Theory and Methodology of Data Science:

For the attainment of the 15% of the exam aggregated allotted to this portion, the candidates need to be well versed in the simulation of data, the analysis of random forests, and the use of multinomial logistic regression in order to maximize the transfer and exchange of information.

Section 6 – Conception of Data:

The Big Data is all numbers; hence, the candidates need to be able to comprehend and perceive the data in ways that allow them to visualize it and make sense out of it. Being able to understand and decipher the multivariate data will award the candidates with the remaining 12% of the aggregate.

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