Linkedin Learning – AWS Infrastructure as Code for Software Developers

Linkedin Learning – AWS Infrastructure as Code for Software Developers-ZH
English | Size: 130.53 MB
Category: Tutorial

Traditionally, working with infrastructure in the cloud requires knowledge of domain-specific languages such as Terraform, network infrastructure, operating systems, and more. AWS Cloud Development Kit (CDK) simplifies this process for developers, allowing them to leverage their existing programming skills to deploy infrastructure. In this course, join Carlos Rivas as he explores a real-world architecture and shows how to write the code to deploy it using AWS CDK and Python. Carlos helps to familiarize you with the basics of working with CDK, as well as how to set it up and create your first CDK project. He then covers how to implement networking, validate your deployed subnets, use the CDK packages for load balancing verify that everything is up and running in your deployment, and more

Colin Dijs – September Mastermind

Colin Dijs – September Mastermind
English | Size: 3.77 GB
Category: Tutorial

Experience..
One of the greatest parts of being part of a mastermind is the guidance you receive from others that are already where you want to be. They have been through the highs and lows and can help you from experiencing the same pitfall that they did.

Technics Publications – What is Data Science and Data Analytics

Technics Publications – What is Data Science and Data Analytics-ZH
English | Size: 56.78 MB
Category: Tutorial

Follow along with data science expert Rohit Kumar and become equipped to explain the fields of data science and data analysis. Learn why data analysis is so important and become familiar with data analysis tools. Know why Python is ideal for data analytics. Become comfortable with the various types of analyses: Text Analysis, Statistical Analysis, Diagnostic Analysis, Predictive Analysis, and Prescriptive Analysis. Become aware of the steps in the data analytics process: Data Requirements Gathering, Data Collection, Data Analysis, Data Interpretation, and Data Visualization.