Introduction to Data Analytics
This course is a survey of processes and tools commonly used in applications that rely heavily on data analysis. The course will describe data pipelines deployed by data engineers and data scientists to ingest data for use in an application and to manipulate that data for use by analysts. Hands-on activities will include a combination […]
Practical Machine Learning With Apache Spark
This intensive hands-on training introduces the audience to the core aspects of scalable data processing using Python on the Apache Spark platform. The students will learn the essentials of Python with the primary focus being on the capabilities of the Apache Spark platform and its Machine Learning module. The students will be introduced to the […]
Data Science and Data Engineering for Architects
This course covers the theoretical and practical aspects of applying the principles and methods of Data Science and Data Engineering. Students are introduced to the relevant concepts, terminology, theory, and tools used in the field. This training course is complemented by a variety of hands-on exercises to help the attendees reinforce their theoretical knowledge of […]
Data Engineering with PySpark
Data Engineering has become an important role in the Data Science space. For Data Analysts to do productive work, they need to have consistent datasets to analyze. A Data Engineer provides this consistency for analysts by accessing data in a variety of formats, using a variety of tools. This class will introduce programmers to tools […]
Applied Data Science with Python
This course provides theoretical and practical aspects of using Python applied to Data Science, Business Analytics, and Data Logistics. Emphasis is on a survey of core concepts, terminology, and theory. This course is supplemented by a variety of hands-on labs that help participants reinforce their theoretical knowledge of the learned material.
Advanced Data Analytics with PySpark
This class introduces participants to the Apache Spark platform, the Spark Shell and Spark SQL for big data processing applications. In addition to the Spark platform, participants will learn fundamental tools in the pandas library and gain experience with data visualization using seaborn.
Planning and Designing Databases on AWS
In this course, you will learn about the process of planning and designing both relational and nonrelational databases. You will learn the design considerations for hosting databases on Amazon Elastic Compute Cloud (Amazon EC2). You will learn about our relational database services including Amazon Relational Database Service (Amazon RDS), Amazon Aurora, and Amazon Redshift. You […]
Data Analysis with Excel
The objective of this course is to fully explore the uses of Microsoft Excel as a data analysis tool. Most business professionals are familiar with the core functionality of Excel. This course explores some of the additional capabilities and advanced features of Excel for analyzing, manipulating and visualizing data.
AWS – Practical Data Science with Amazon SageMaker
In this intermediate-level course, individuals learn how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also […]