This course introduces the Participants to concepts of Data Analytics, Data mining techniques and the underlying statistics that support Big Data Analytics.
The course is vast and each topic of training is divided into modules so that participants can learn, understand and practice each module and develop mastery of the same.
Learning Outcomes By the end of the course:
Students will be able to:
1. Deploy a structured lifecycle approach to Data Analytics projects
2. Select visualization techniques and tools to analyze big data and create statistical models
3. Use tools such as R, Python and Knime to develop analytical applications and generate meaningful insights thereby generating value for themselves and their organization.
Evaluation: Assignments (40 Marks) Presentation (10 Marks) + Project Work (60 Marks)
All Training Material and Script Access will be provided to the participants
Analytics Domain has trained more than 1500 professionals from over 100+ companies around the world through a variety of workshops and boot camps. Our training is online, hands-on, and feedback oriented. We take personal interest in each student’s learning needs.
Our students are exposed to real world scenarios for solving real world problems right from week one.
This course covers foundation techniques and tools required for data science and big data analytics.
The course focuses on concepts, principles, and techniques applicable to any technology environment and industry and establishes confidence in the student to tackle many types of situations related to Data Analytics.
(Technical Skills normally picked up by trainees during the Training)
Python and its libraries like - Numpy, Pandas, Matplotlib, Scipy, Plotly, Bokeh etc.,
R and its Packages
Data Visualization Tools and Reporting tools such as Qlikview and Google Data Studio
Knime Analytic platform
Predictive Analytics tools & Text Analytics Tools
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