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Leading transformation through learning.

Big Data holds the key to effectively address business challenges that result in competitive advantage. Develop skills that will unlock valuable insights from data using analytic tools, tips, and techniques learned.

Leverage Dell Technologies Education Services framework to enable a continuous learning process.

Home » Courses » DELL-EMC » DELL Data Science and Big Data

Leading transformation through learning.

Big Data holds the key to effectively address business challenges that result in competitive advantage. Develop skills that will unlock valuable insights from data using analytic tools, tips, and techniques learned.

Leverage Dell Technologies Education Services framework to enable a continuous learning process.

Leading transformation through learning.

Big Data holds the key to effectively address business challenges that result in competitive advantage. Develop skills that will unlock valuable insights from data using analytic tools, tips, and techniques learned.

Leverage Dell Technologies Education Services framework to enable a continuous learning process.

  • 5 Days ILT, VILT

    This instructor-led workshop covers the content and hands-on lab exercises provided in the following courses: Data Warehousing with SQL and NoSQL, ETL Offload with Hadoop and Spark, Data Governance, Security and Privacy for Big Data, Processing Streaming and IoT Data, Building Data Pipelines with Python.

    This training prepares the learner for a major portion of the Dell Technologies Proven Professional data engineering specialist-level certification exam (DES-7DE1). Review the exam description document to understand all the related data engineering training and consumption options.

  • 5 Days ILT, VILT

    This ES722OCMDSBDA: Data Science and Big Data Analytics v2 course provides practical foundation level training that enables immediate and effective participation in Big Data and other analytics projects. It includes an introduction to Big Data and the data analytics lifecycle to address business challenges that leverage Big Data.

    The course provides grounding in basic and advanced analytic methods and an introduction to Big Data analytics technology and tools, including MapReduce and Hadoop. Labs offer opportunities for students to understand how these methods and tools may be applied to real world business challenges by a practicing data scientist.

    The course takes an “open”, or technology-neutral approach and includes a final lab which addresses a big data analytics challenge by applying the concepts taught in the course in the context of the data analytics lifecycle. The course prepares the student for the Dell EMC Proven™ Professional Data Scientist Associate (EMCDSA) certification exam.

  • 1 Day ILT, VILT

    The ESOCMS02326: Artificial Intelligence and Machine Learning training course provides a detailed description about the technical and operational aspect of AI and ML and helps the learners to understand the concepts of AI, ML, neural network, reinforcement learning, NLP and artificial ecosystem. It also provides a detailed description about the need of AI ready infrastructure, AI and ML frameworks, implemented machine learning models, and use cases across the industry.

    The offering is an engaging mix of key technologies, case examples, and business insights. The course includes recorded lab exercise demonstrations explaining the techniques of machine learning, neural network, reinforcement learning, and infrastructure in detail.

  • 1 Day ILT, VILT

    This course gives business leaders the skills and knowledge to better manage such analytical efforts. It describes how to get started and what is required to effectively run projects which leverage Big Data analytics. Specifically, it addresses: deriving business value from Big Data, leading Data Science projects using a data analytics lifecycle, developing Data Science teams, and driving innovation using analytics.

  • 5 Days ILT, VILT

    This course builds on skills developed in the Data Science and Big Data Analytics course. The main focus areas cover Hadoop (including Pig, Hive, and HBase), Natural Language Processing, Social Network Analysis, Simulation, Random Forests, Multinomial Logistic Regression, and Data Visualization. Taking an “Open” or technology-neutral approach, this course utilizes several open-source tools to address big data challenges.

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