AWS Fundamentals: Going Cloud-Native

Course Link: https://www.coursera.org/learn/aws-fundamentals-going-cloud-native

AWS Fundamentals: Going Cloud-Native
This course is designed to provide a basic overview of AWS services and the process of going cloud-native. We’ll cover topics such as AWS resources, virtual hosts, networking, security, HA, load balancing, networking fundamentals, and AWS orchestration. You’ll also get a very basic understanding of AWS virtual machine capabilities, such as virtual IP addresses and public interfaces.

At the end of this course, you will be able to:

*Check out Amazon.com for pricing and availability on AWS resources.
*List and query resources on AWS.
*Implement security and monitoring capabilities on AWS.
*Implement networking and security policies on AWS.
*Implement AWS orchestration strategies and policies.
*Organize AWS resources in AWS resources.
*Configure security and monitoring capabilities on AWS.
*Rethink security and monitoring capabilities on AWS.
*Go cloud native with security and monitoring.
*Configure security and monitoring on AWS.

This is the third course in the AWS Networking and Security Operations specialization. The course assumes prior knowledge of AWS. If you have no prior familiarity with AWS, proceed through the first course, Managing AWS Resources, which provided an in-depth, step-by-step overview of AWS.

Module 1: AWS Resource Abstraction
Module 2: AWS Virtual Hosts
Module 3: AWS Networking
Module 4: AWS Security
AWS Fundamentals: Transforming the Cloud
This course is designed to provide a basic overview of AWS services and the process of going cloud-native. We’ll cover topics such as AWS resource utilization, AWS networking, security, HA, load balancing, and network communication. You’ll also get a very basic understanding of AWS orchestration and security.

At the end of this course, you will be able to:

*Check out Amazon.com for pricing and availability on AWS resources.
*List and query resources on AWS.
*Implement security and monitoring capabilities on AWS.
*Rethink security and monitoring capabilities on AWS.
*Go cloud native with security and monitoring.
*Configure security and monitoring on AWS.

This is the second course in the AWS Networking and Security Operations specialization. The course assumes prior knowledge of AWS. If you have no prior experience with AWS, proceed through the first course Managing AWS Resource Utilization, which provided an in-depth, step-by-step overview of AWS.

Module 1: AWS Resource Utilization
Module 2: AWS Networking
Module 3: AWS Security
Algorithms on Strings
This course is the third course in the specialization that covers algorithms on strings. You’ll learn several of them from the perspective of algorithms and programming, and then you

Course Link: https://www.coursera.org/learn/aws-fundamentals-going-cloud-native

Achieving Advanced Insights with BigQuery

Course Link: https://www.coursera.org/learn/gcp-advanced-insights-bigquery

Achieving Advanced Insights with BigQuery
In this course, we will learn how to use BigQuery to do advanced analysis of our data. We will build a database schema and query plan for our BigQuery queries. We will use various tools within the SQL that we have learned in the previous courses to perform advanced SQL queries and to visualize the results we will see which indices we need to use to make our queries. This class will allow us to see the data in a whole data set, so we can make more advanced SQL queries and to visualize the data we will need to use the appropriate indices. We will use the SQLite3 Framework to build our schema and query plan.

This is the second course in the Data Analysis with SQL specialization. The first course was all about data warehousing and storing our data securely. This second course covers advanced SQL queries and how to prepare them in a secure manner. We will learn how to use password protection to ensure that only the authorized user can run queries and how to use SQLite3 for this security. We will also learn how to use SQLite3 for data warehousing and storage. By the end of this course, you should be able to write more complex SQL statements and write them in a secure manner. We will start by writing some basic queries for our queries to ensure that we are working on a master database (which will allow us to run all our queries). We will then learn how to use SQLite3 for data warehousing and storage and use it for our master database. We will then apply various SQL commands to our queries and use it for our master database. Finally, we will use SQLite3 for our queries to make sure that they are safe. We will then apply various SQL commands to our queries to make sure that they are safe. We will then apply various SQL commands to our queries to make sure that they are safe.

This is an intermediate course. To pass this course, you should have at least one (or two) years of SQL experience. You should be familiar with the SQL syntax, the basic query and the possible side effects. You should also have at least one year of programming experience. The code in this course is largely written in Python 3. If you have experience using other programming languages, you may be more at ease using Python.Module 1 – SQL Basics
Module 2 – Preparing Queries and Preparing Queries with Side Effects
Module 3 – SQLite3 Integration
Module 4 – The UT Table and Using it in Production
Alpha, Omega, and a Supernova: The Evolution of the Sun
Are we alone in the Universe?

This course will take you on a journey to learn more about our Sun, the origin of our solar system, and the evolution of our Galaxy. The course will cover the topics of stars, planets, and galaxies, expanding and contracting, black holes, supernovae, black holes

Course Link: https://www.coursera.org/learn/gcp-advanced-insights-bigquery

Applying Machine Learning to your Data with GCP

Course Link: https://www.coursera.org/learn/data-insights-gcp-apply-ml

Applying Machine Learning to your Data with GCP
In the Machine Learning course of this specialization, you will go in-depth about applying a basic approach to your data, namely, machine learning. In particular, we will cover the following topics:  

Applying a basic approach to your data, namely, regression
Applying linear models to your data, namely, regression
The use of deep learning on models, namely, neural networks
Deep learning on models, namely, neural networks
Applying Machine Learning for Retrieving Helpful Knowledge
In this course, you will learn how to use machine learning techniques to extract useful knowledge from your data. In particular, you will learn about:

* The use of parameters in models to predict outcomes
* The use of features in models to retain some of the originality and uniqueness that can help predict outcomes

To get the most out of this course, you should first take a look at the basic concepts and terminology we’ve introduced throughout the specialization. We have also played around with a few everyday examples in R and have come up with some interesting results.

In this class, you will get lots of practice doing simple machine learning tasks in R. We have also introduced lots of machine learning examples from many different disciplines, so you will understand what is going on inside a neural network.

Please note that this is an advanced course, and we recommend that you check with a professional, academic, or business level background about certain topics and tasks. You should be able to understand and perform basic machine learning tasks using these concepts and tools.

Note that this is an advanced class, and we expect you to check with a professional, academic, or business level background about certain topics and tasks. You should be able to understand and perform basic machine learning tasks using these concepts and tools.Week 1: Read and Preprocess your Data
Week 2: Load and Preprocess your Data
Week 3: Load and Preprocess your Data Part 1: Understanding the Machine
Week 4: Load and Preprocess your Data Part 2: Modeling and Compute the Model
Week 5: Load and Preprocess your Data Part 3: Predicting the Model
Applying Machine Learning to your Data with Google Cloud’s Big Data team
In the Machine Learning and Data Analytics course offered by Coursera, you will learn the ins and outs of using machine learning methods to extract useful data from big data. You will learn about:

* Compression, Encoding, and Background Intelligent Transfer (CITT)
* Linear models
* Recurrent and Distributed Forecasting (RFF)
* Neural Networks
* Machine Learning
* Optimization

If you are interested in leading a team of data scientists and engineers in data quality and quality management, this course is for you!

Pre-requisites

Course Link: https://www.coursera.org/learn/data-insights-gcp-apply-ml

Art and Science of Machine Learning

Course Link: https://www.coursera.org/learn/art-science-ml

Art and Science of Machine Learning
This course will cover the art and science of machine learning in high school science. We will learn about the computational methods used to design and train models for supervised learning and unsupervised learning in Python. We will also cover the basic techniques for modeling and exploring the data, as well as the types of models that are used. We will also cover the “meat” of the course, modeling and exploring the data. We will cover modeling problems in Python, introducing conditional and unconditional rules, as well as an introduction to supervised learning. We will learn about the state-of-the-art in Python models and how to use them in the real world. We will cover modeling, unsupervised learning, and exploration of the data, with an emphasis on modeling problems that arise from the data itself. We will cover modeling problems in Python, introduction to supervised learning, and an introduction to unsupervised learning. We will cover the state-of-the-art in Python models and how to use them in the real world. We will cover modeling, unsupervised learning, and exploration of the data, with an emphasis on modeling problems that arise from the data itself.

Prerequisites

Learners should be comfortable writing machine learning models using Python, having some basic knowledge of Python programming and statistics, and have previous experience with Python programming (including working with NumPy and Pandas). We will assume that learners are comfortable working with the typical “programming the same thing over and over” routine that is common in machine learning. This means you should be comfortable writing machine learning code in Python, and should have experience working with data in a NumPy/Pandas environment.

Suggested Read

C++ Programming, Chapter 9.3, Part 1, “Introduction to C++” by Michael F. Neibut (NIIHB, C++AM)

This course has been designed to be enjoyable even for those that have mastered advanced computer science. Much of the material will still be familiar to those of you that have taken introductory courses in computer science, but the course will challenge you to think critically and creatively about the issues and problems that you will face in the course. The course will also give you the opportunity to practice and to share your own approaches to the problems that you will solve.

The course has been divided into 4 sections: (1) Machine Learning, (2) Convolutional Neural Networks, (3) Regularization, and (4) Optimization. Each section is introduced and completed using examples from a wide range of fields. The final section of the course provides an overview of the field and a review of what is to come.

The course is intended for advanced computer science majors and high-school students. It will be challenging at first but rewarding after you master the material and become familiar with some of the key concepts

Course Link: https://www.coursera.org/learn/art-science-ml

Configuration Management and the Cloud

Course Link: https://www.coursera.org/learn/configuration-management-cloud

Configuration Management and the Cloud
Have you ever wondered how companies like Google, Microsoft, Amazon, and Apple manage to have their IT departments run efficiently and to the point where they almost seem to be on a single infrastructure?

Have you ever wondered how it is that these companies manage to have their IT departments run efficiently and to the point where they almost seem to be on a single infrastructure?

In this course, we will explore the basics of how companies like Google, Microsoft, Amazon, and Apple manage to have their IT departments run efficiently and to the point where they almost seem to be on a single infrastructure. We will also cover topics such as network operations, domain names, virtualization, and network access control, which will be applied to the common IT tasks that are performed by the IT department. We will cover topics such as network traffic management, domain name resolution, and computer security. We will also cover topics such as domain names and virtual machines, which will be applied to the common Windows and Linux computer tasks that are performed by the IT department. We will also cover topics such as domain names and virtual machines, which will be applied to the common Windows and Linux computer tasks that are performed by the IT department.

At the end of this course, you will be able to:
• Describe the state of a web server and how to maintain a domain name.
• Manage domain names using the command line interface.
• Use various command line utilities to manage a domain name.
• Describe how a customer’s IT department operates.
• Describe how a customer uses the command line interface.
• Understand how Apple and Google use the command line interface.
• Discuss the common command line utilities.
• Explain how virtual machines are implemented.
• Discuss the common command line utilities.
• Explain how customer and IT departments work.

This is the third course in the Digital Manufacturing and Design Technology specialization that explores the many facets of manufacturing, and the digital manufacturing and design technology behind it. The specialization focuses on the many design and manufacturing related aspects of the manufacturing process, including:

• Design and machining of electronic devices, sensors, and other manufacturing and design activities
• Distribution of design and manufacturing processes in software and hardware
• Distribution and application of design and manufacturing processes in software and hardware
• Software and hardware that implements design and manufacturing processes in a physical product or service.

This course is the fourth and last course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing, and the digital manufacturing and design technology behind it. The specialization focuses on the many design and manufacturing related aspects of the manufacturing process, including:

• Design and machining of electronic devices, sensors, and other manufacturing and design activities
• Distribution of design and manufacturing processes in software

Course Link: https://www.coursera.org/learn/configuration-management-cloud

Getting Started With Application Development

Course Link: https://www.coursera.org/learn/getting-started-app-development

Getting Started With Application Development
In this course, you will learn a detailed, step-by-step application development method in C#. You will learn about the application model that we use for large scale projects, what the common elements of our application model are, and how we use dependency injection to decouple application state from the application code. We will also cover the basics of .NET standard and common usage patterns, including methods, dependency injection, and shared libraries. We will also cover the basics of using LINQ to make your code more efficient and to enable you to use common data structures such as Lists and Reductions. You will also learn the basics of using .NET standard and common usage patterns, including methods, dependency injection, and shared libraries. We will also cover the basics of using .NET standard and common usage patterns, including methods, dependency injection, and shared libraries. We will also cover the basics of using LINQ to make your code more efficient and to enable you to use common data structures such as Lists and Reductions. You will also learn the basics of using .NET standard and common usage patterns, including methods, dependency injection, and shared libraries. We will also cover the basics of using LINQ to make your code more efficient and to enable you to use common data structures such as Lists and Reductions. You will also learn the basics of using LINQ to make your code more efficient and to enable you to use common data structures such as Lists and Reductions. This course is designed to act as a gateway to more advanced course on Modeling Application Programs. The course is structured around five key topics: Application Modeling, Data Binding, Dependency Injection, and Shared Libraries, and their Subprograms and Drivers. Throughout the course, you will work through a large number of examples and projects. You will also have an opportunity to apply your learning across multiple sessions. This is the second course in the .NET Framework and it will be a tough course to grade since you will work through so many examples and projects.

What You’ll Learn:

How we design for efficiency
We use LINQ to decouple application state from the application code
We use .NET standard and common usage patterns
We use LINQ to make your code more efficient and to enable you to use common data structures such as Lists and Reductions
We cover modeling application programs and modeling intermediate results

Formatting, formatting, and indenting are key considerations for LINQ
Indentation matters for LINQ
Maturity of the application model matters for LINQ
Getting Started with AWS Cloud Identity
In this course you will learn how to set up and use AWS Cloud Identity for client-server communications. You’ll learn how to retrieve information from cloud storage using AWS EC2 instances and how to use AWS LoadBalancer orchestration to dynamically distribute the load between AWS EC2 instances. You will

Course Link: https://www.coursera.org/learn/getting-started-app-development

Google Cloud Platform Big Data and Machine Learning Fundamentals

Course Link: https://www.coursera.org/learn/gcp-big-data-ml-fundamentals

Google Cloud Platform Big Data and Machine Learning Fundamentals
This 1-week, accelerated online course introduces the machine learning and data science concepts that you need in order to be an effective machine learning expert. You’ll learn:
* Modeling and optimization problems in computer vision and natural language understanding
* Identify the unique attributes of deep learning and apply them to solve training and testing problems
* Leverage common machine learning algorithms and Python libraries to solve training and testing problems
* Train and reuse neural networks
* Build a deep neural network using Python

>>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<https://www.coursera.org/learn/gcp-big-data-ml-fundamentals

Industrial IoT on Google Cloud Platform

Course Link: https://www.coursera.org/learn/iiot-google-cloud-platform

Industrial IoT on Google Cloud Platform
This two-week course focuses on the high-level fundamentals of the Internet of Things (IoT) and its applications, including systems requirements, networking, and system design. The course will guide you through the process of applying the top three topics covered in the specialization, namely:

System Design
Networking
System Interfaces and Transceivers
System Modules
Interprofessional Web Development
This course focuses on the interprofessional development of web applications in C++ and other languages. The focus is on the client-server architecture, and the emphasis is on the client-server side of the internet. In particular, we will learn how to develop web applications that run on mobile devices, and how to develop web applications that run on desktops or laptops. You’ll also learn how to build scalable data pipelines, and how to build web applications that run across virtual machines, on Google Cloud’s infrastructure.

You’ll learn how to solve problems using the data model that you have developed in this specialization, and you’ll also build skills for the general programming. We’ll show you how to use the command line to develop the application you wanted to develop, and how to use the -verbose switch to debug the application. We’ll also show you how to use a text editor to write your application. You’ll learn how to run your code in the foreground and be able to use the debugger to verify that your code is behaving properly. In the second half of the course, we’ll focus on the web server side, and how to develop web applications using the command line. We’ll learn how to install applications, configure your routers and firewall, and set up your computer for development. You’ll also learn how to debug your application. You’ll learn how to test if your application works by running it with command line tools. The last course in the specialization is about how to learn how to write your application. Our hope is that you’ll be able to apply what you’ve learned to write your own application.Interprofessional Web Development Part 1
Interprofessional Web Development Part 2
Interprofessional Web Development Part 3
Interprofessional Web Development Part 4
Image and Video Processing
This is a course where you will learn about the field of Image and Video Post-Production, and how it all comes together to deliver a professional quality video or image. You’ll learn about the various professional image and video post-exposure effects from film and television to digital image and music, and how they are applied to video and image files. We’ll also look at the tools and techniques for manipulating and converting image and video post-images, and how post-image quality is managed.

This is a true passion

Course Link: https://www.coursera.org/learn/iiot-google-cloud-platform

Intro to TensorFlow

Course Link: https://www.coursera.org/learn/intro-tensorflow

Intro to TensorFlow
This course introduces the basic concepts of TensorFlow. It will cover topics such as integration, machine learning, and deep learning, as well as the use of libraries on the TensorFlow side. TensorFlow is a modern GPU-based deep learning framework that is very popular in industry and is used by big names in industry-level research. TensorFlow is a high-performance ML framework that is very valuable in HPC applications. This course also covers the use of linear models in TensorFlow.

Pre-requisites
To get the most out of this course, learners should have access to:
*Pre-bought hardware or recent NVIDIA GTX 1080ti or GTX 1080m video cards
*Basic proficiency with common query language such as Python
*Experience with data modeling and visualization
*Knowledge of machine architecture such as CPU, GPU, and FPGA
*Basic familiarity with Python
*Basic familiarity with client-server architecture
*Knowledge of common data modeling frameworks, including linear models, matrix and array
*Basic familiarity with linear algebra and data manipulation
*Basic familiarity with basic data analysis

>>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<https://www.coursera.org/learn/intro-tensorflow

Introduction to Cloud Identity

Course Link: https://www.coursera.org/learn/cloud-identity

Introduction to Cloud Identity
In this introductory course to Cloud Identity, we will dive into the core security model of virtualization (VMD) and how this is managed on AWS. We will cover AWS VMD basics, basic security design principles, cloud authentication, and basic security operations. You will also learn about AWS HAProxy, security design for hybrid clouds, and virtual networks. This course is intended to give you a start on understanding VMD and how it differs from traditional VMD, as well as provide a basic foundation for more advanced topics in the future.

At the end of this course, you will be able to:
• Describe AWS virtualization and basic security design principles.
• Investigate AWS security operations and basic security design principles in a safe environment.
• Investigate basic security design principles and security model for VMD.
• Investigate AWS HAProxy services.
• Investigate basic security design principles and security model for VMD.
• Describe AWS services and features.

This is an introductory course designed to provide you with a basic understanding of VMD and AWS security operations. We will be covering AWS security services and features, as well as basic security design principles. To keep you updated on course content, you can follow us on Twitter and Facebook!

Course Structure
Week 1
Module 1.0 : AWS Security Services

Module 2.0 : Basic Security Design
Module 3.0 : Basic Security Operations

Week 2

Module 1.0 : Cloud Identity
Module 2.0 : Basic Security Design
Module 3.0 : Basic Security Operations

Week 3

Module 1.0 : HAProxy Services
Module 2.0 : Basic Security Design
Module 3.0 : Basic Security Operations

Week 4

Module 1.0 : Hybrid Clouds
Module 2.0 : HAProxy Services

Module 3.0 : Basic Security Design
Module 4.0 : Basic Security Operations

Week 5

Module 1.0 : Hybrid Networks
Module 2.0 : HAProxy Services

Module 3.0 : Basic Security Design
Module 4.0 : Basic Security Operations

Week 6

Module 1.0 : Security Model for VMD
Module 2.0 : Security Model for VMD

Module 3.0 : Basic Security Design
Module 4.0 : Basic Security Operations

Week 7

Module 1.0 : Security model for VMD
Module 2.0 : Security model for VMD

Module 3.0 : Basic Security Design
Module 4.0 : Basic Security Operations

Week 8

Module 1.0 : Security model for VMD
Module 2.0 : Security model for VMD

Module 3.0 : Basic Security Design
Module 4.0 : Basic Security Operations

Week 9

Module 1.0 : Security model for V

Course Link: https://www.coursera.org/learn/cloud-identity