Welcome
IPN-Dharma AI Lab
This is an IPN CIC - DHARMA initiative to provide an Artificial Intelligence Laboratory to motivate researchers, professors and students to take advantage of the courses, resources and tools of the main technology platforms of the industry in the areas of Machine Learning, Data Science, Cloud Computing, Artificial Intelligence and Internet of Things with the purpose of generating a practical experience through a learning model between peers and by objectives.
Level 1: Literacy and Foundations
Data Analytics Part I
This program is designed to help Developers, Data Analysts, and Data Engineers design, build, secure, and maintain analytics solutions. The digital training included in this program will expose you to the fastest way to get answers from all your data to all your users. This program can also help prepare you for the AWS Certified Data Analytics - Specialty certification exam.
This is the first part of the program, the second part is in Data Analytics Part II. If you are interested in additional resources you can explore the Ramp-Up Guide: Data Analytics.
This is the first part of the program, the second part is in Data Analytics Part II. If you are interested in additional resources you can explore the Ramp-Up Guide: Data Analytics.
Courses in this program
1) AWS Analytics Services Overview
This course introduces AWS Analytics tools - a category of services that are tightly integrated to enable the ingestion, storage, analysis, and visualization of data.
Estimated effort 1 hour
English language
2) Introduction to Amazon Kinesis Streams
In this course, we cover how Amazon Kinesis Streams is used to collect, process and analyze real-time streaming data to create valuable insights. An overview of the components of this service and a brief demonstration are also covered in this course.
3) Introduction to Amazon Kinesis Firehose
Amazon Kinesis Firehose is the AWS service that helps you load streaming data into AWS. In this introductory course on Amazon Kinesis Firehose, we will provide an overview on how the service captures, transforms and loads streaming data into AWS by detailing the data transformation process. We will look at the benefits of the service and how it integrates with Amazon CloudWatch to enable stream monitoring. The course will wrap up with a demonstration on how to configure a Kinesis Firehose delivery stream and how to generate source stream content.
4) Introduction to Amazon Kinesis Analytics
This is an introductory course on Amazon Kinesis Analytics, which helps you query streaming data or build entire streaming applications using SQL. In this course, we discuss how the service collects, processes and analyzes streaming data in real-time. We also discuss how to use and monitor Amazon Kinesis Analytics and explore use cases.
5) Getting Started with Amazon EMR
Amazon EMR is a service for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. You can use Amazon EMR to set up, operate, and scale your big data environments and automate time-consuming tasks like provisioning capacity and tuning clusters. In this course, you will learn the benefits, typical use cases, and technical concepts of Amazon EMR. You will have an opportunity to try the service through a demonstration using the AWS Management Console.
In this course, you will learn to:
In this course, you will learn to:
- Understand how Amazon EMR works.
- Understand the technical concepts of Amazon EMR.
- List typical use cases for Amazon EMR.
- Specify what it would take to implement Amazon EMR in a real-world scenario.
- Recognize the benefits of Amazon EMR.
- Explain the cost structure of Amazon EMR.
- Show how to use Amazon EMR from the AWS Management Console.
6) Getting Started with AWS Glue
AWS Glue is a serverless data integration service that you can use to discover, prepare, and combine data for analytics, machine learning (ML), and application development. In this course, you will learn the benefits, typical use cases, and technical concepts of AWS Glue. You will have an opportunity to try the service through a demonstration using the AWS Management Console.
In this course, you will learn to:
In this course, you will learn to:
- Understand how AWS Glue works.
- Familiarize yourself with the technical concepts of AWS Glue.
- List typical use cases for AWS Glue.
- Specify what it would take to implement AWS Glue in a real-world scenario.
- Recognize the benefits of AWS Glue.
- Explain the cost structure of AWS Glue.
- Show how to use AWS Glue from the AWS Management Console.
7) Introduction to Amazon Athena
This course introduces the Amazon Athena service along with an overview of its operating environment. The basic steps in implementing Amazon Athena are also covered. Using the AWS Management Console, a brief demonstration of creating a database to run SQL queries for validation is performed.
8) Introduction to Amazon Quicksight
This is an introductory video on Amazon QuickSight – the cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. In this course, we will discuss the benefits of using Amazon QuickSight and how the service works.
The course will also include a demonstration so you can see what Amazon QuickSight looks like in action.
The course will also include a demonstration so you can see what Amazon QuickSight looks like in action.
9) Visualizing with QuickSight
In this course, you will be introduced to the technical side of business intelligence (BI) and data visualization with Amazon Web Services (AWS). You will focus on using Amazon QuickSight to build and share interactive dashboards and analyses. You will learn how to embed dashboards into applications and websites, and securely manage access and permissions. You will also see how to connect to and prepare data from services such as Amazon Simple Storage Service (Amazon S3), Amazon Relational Database Service (Amazon RDS), Amazon Redshift, Amazon Athena, and AWS Glue, as well as on-premises data sources through virtual private clouds (VPCs) and application connectors.
In this course, you will learn how to:
In this course, you will learn how to:
- Provide a technical overview of data visualization via QuickSight.
- Connect to and prepare data for visualization and analysis from AWS sources, third-party applications, and on-premises databases.
- Create and share visual analyses and dashboards.
- Set up secure authentication for users and groups, including Active Directory, Security Assertion Markup Language (SAML), and software development kits (SDKs).
- Embed interactive dashboards and analytics into your applications, websites, and portals.
- Leverage automated machine learning insights for anomaly detection, forecasting, and natural language narratives.
10) Introduction to AWS IoT Analytics
This course is an introduction to AWS IoT Analytics, a fully-managed service which allows you to run sophisticated analytics on massive volumes of IoT data. In this course, we look at the key components of AWS IoT analytics, an overview of the deployment architecture, and some use cases. We also have a demo for you to see AWS IoT Analytics in action.