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Big Data,
                  Analytics, and the
                  Data Scientist Role (5%) : 3
                    Quuestions 
•
                Define and describe the characteristics of Big Data 
•
                Describe the business drivers for Big Data analytics and data
                science 
•
                Describe the Data Scientist role and related skills 
•
                Describe the data analytics lifecycle purpose and sequence of
                phases 
•
                Discovery - Describe details of this phase, including activities
                and associated roles 
•
                Data preparation - Describe details of this phase, including
                activities and associated roles 
•
                Model planning - Describe details of this phase, including
                activities and associated roles 
•
                Model building - Describe details of this phase, including
                activities and associated roles 
•
                Explain how basic R commands are used to initially explore and
                analyze the data 
•
                Describe and provide examples of the most important statistical
                measures and effective visualizations of data 
• Describe the theory, process, and analysis of results for hypothesis testing and its use in evaluating a model
Advanced
Analytics
                  - Theory, Application, and Interpretation of Results for
                  Eight
                  Methods (40%) : 24
                    Questions 
•
                K-means clustering (3 Questions) 
•
                Association rules (3
                Questions)
                
•
                Linear regression (3
                Questions)
                
•
                Logistic Regression (3
                Questions)
                
•
                Naïve Bayesian classifiers (3
                Questions)
                
•
                Decision trees (3
                Questions)
                
•
                Time Series Analysis (3
                Questions)
                
•
                Text Analytics (3
                Questions)
                
•
                Describe the technological challenges posed by Big Data 
•
                Describe the nature and use of MapReduce and Apache Hadoop 
•
                Describe the Hadoop ecosystem and related product use cases 
•
                Describe in-database analytics and SQL essentials 
•
                Describe advanced SQL methods: window functions, ordered
                aggregates, and MADlib 
•
                Describe best practices for communicating findings and
                operationalizing an analytics project 
•
                Describe best practices for building project presentations for
                specific audiences 
• Describe best practices for planning and creating effective data visualizations
                
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