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Answer to all the above questions is the word “DATA SCIENTIST”, which is also termed differently as Data Analytics or Business Analytics. All it takes to become a successful data scientist is working knowledge of 5 core concepts –Statistical Analysis, Forecasting, Data Mining, Data Visualisation & Text Mining. Excelr provides hands-on training using live case studies being implemented in industry for 50 hours. In addition participants are provided with assignments, mini-projects, quizzes, case studies & a final capstone project to ensure that you are ready to crack any interview immediately after the last day of training.<br>
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Business Analytics/Data Analytics/Data Scientist Certifications
Business Analytics/Data Analytics/Data Scientist Certifications Answer to all the above questions is the word “DATA SCIENTIST”, which is also termed differently as Data Analytics or Business Analytics. All it takes to become a successful data scientist is working knowledge of 5 core concepts –Statistical Analysis, Forecasting, Data Mining, Data Visualisation & Text Mining. Excelr provides hands-on training using live case studies being implemented in industry for 50 hours. In addition participants are provided with assignments, mini-projects, quizzes, case studies & a final capstone project to ensure that you are ready to crack any interview immediately after the last day of training.
Big Data Hadoop Certification Training Introduction to Hadoop• What is Big Data• Need and significance of innovative technologies• What is Hadoop• 3 Vs (Characteristics)• History of Hadoop and its Uses• Different Components of Hadoop MapReduce• Introduction to MapReduce•MapReduce Architecture•MapReduce Programming Model•MapReduce Algorithm and Phases• Data Types• Input Splits and Records
Optimization Optimization techniques not only provides the best optimal solution but also provides feedback on how changing the objective function coefficient will change the optimal solution. Every industry faces optimization problem and different optimization techniques are used to solve different problems. Different optimization problems include linear optimization problem, combinatorial optimization problem, constrained optimization problem, multi objective optimization problem, nonlinear optimization problem etc.
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