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Overview
Course Outline
Schedule & Fees
Methodology
This course will be highly interactive with group discussions, case studies, hands-on practical exercises, and group activities being the core focus.
Course Objectives
By the end of the course, participants will be able to:
Design big data implementation plans and create strategies for data-driven solutions
Explain the challenges of big data and traditional technologies like Excel
Discuss the main challenges and advantages of Hadoop ecosystem and other big data distributed architectures
Demonstrate and discuss key technologies for big data storage and compute, such as PostgreSQL and MongoDB
Discuss popular machine learning algorithms and the importance of ethics in data analytics and artificial intelligence
Deliver an architectural diagram for analytics focused use cases
Target Audience
This course is ideal for data analysts, data engineers, data scientists, as well as technically-inclined management and administrative professionals seeking to understand big data strategies, technologies and use cases. Recommended pre-knowledge includes basic programming experience and analyzing data in python, knowledge of basic database technologies, and awareness of analytics driven business initiatives.
Target Competencies
Big data hands-on labs
Big data analytics structures and technologies
Ethics and integrity for big data analytics
Big data storage and computer system implementation
Architecture diagram design
Larimar will help you find what you are looking for