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Become an Expert in Big Data Technologies and Analysis.

Data Engineer with Python

Please contact us for best rates.

Cost

5 Days

Duration

Participants will gain proficiency in handling raw data, data warehousing, Big Data processing, and security. You'll learn how to use various tools and platforms to analyze data, design databases, and create data models, enabling you to offer valuable insights and solutions for business optimization.

Learning Objectives

No prerequisites are required for this bootcamp. However, prior knowledge of Linux and basic Python programming will be beneficial. A logical thinking approach and a drive for curiosity are essential to make the most of this course.

Prerequisites

This bootcamp is ideal for IT professionals in traditional ETL or database domains, software engineers, business analysts, data professionals interested in data engineering, and banking or finance professionals looking to harness data for insightful decision-making.

Who Should Attend

Dive into the realm of data engineering with NEOEDX's Data Engineer Bootcamp. This comprehensive course is designed for professionals aiming to harness the power of Big Data technologies. You'll become proficient in a range of critical topics, including Data Warehousing, Linux, Python, SQL, Hadoop, MongoDB, Big Data processing, security, AWS, and more. By learning to design databases, capture and analyze data, and prepare data models, you'll be equipped to tackle complex business challenges and optimize performance with data-driven insights.

Course Description

  1. Essentials of Python for Data Analysis: Mastering Python for Data Science.

  2. Relational Databases and SQL: Extracting and analyzing data with Excel.

  3. SQL for Data Analysis: Using SQL for data extraction and analysis.

  4. NoSQL – MongoDB: Complete knowledge from CRUD operations to cloud applications.

  5. Data Warehousing: Integrating and understanding data warehousing applications.

  6. Big Data Processing using Hadoop: Ingesting data in Hadoop using Sqoop and Flume.

  7. Streaming Big Data with Spark: Foundation of Spark programming and APIs.

  8. Apache Kafka: Understanding Kafka Cluster and configuration.

  9. AWS in Big Data: Services stack for Big Data Analytics on AWS.

  10. Big Data Security: Navigating data protection regulations and challenges.

Course Outline

Lets scale your business

Karl-Gruneklee Strasse 22,

37077, Gottingen

Germany

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