Some #free #online #courses from #Google, #Microsoft, #Meta, #AWS, and other big #universities

Google

• Google AI Crash Course: https://developers.google.com/machine-learning/crash-course
• Google Cloud Skills Fundamentals: https://www.cloudskillsboost.google/course_templates/60
• Android Developer Fundaments: https://google-developer-training.github.io/android-developer-fundamentals-course-concepts/
• Google Analytics for Beginners: https://analytics.google.com/analytics/academy/course/6
• Google Ads for Beginners: https://blog.hootsuite.com/google-ads/
• Google Data Science Professional Certificate: https://www.coursera.org/professional-certificates/google-data-analytics
• Google IT Support Professional Certificate: https://www.coursera.org/professional-certificates/google-it-support
• Google Project Management Professional Certificate: https://grow.google/certificates/project-management/
• Google Cybersecurity Professional Certificate: https://grow.google/certificates/cybersecurity/
• Google Digital Marketing & E-commerce Professional Certificate: https://www.coursera.org/professional-certificates/google-digital-marketing-ecommerce

Microsoft

• Microsoft Azure Fundamentals: https://learn.microsoft.com/en-us/credentials/certifications/azure-fundamentals/
• Microsoft Power BI: https://powerbi.microsoft.com/en-us/
• Microsoft Excel: https://www.microsoft.com/en-us/microsoft-365/excel
• Microsoft PowerPoint: https://www.microsoft.com/en-us/microsoft-365/powerpoint
• Microsoft Teams: https://www.microsoft.com/en-us/microsoft-teams/group-chat-software
• Microsoft Data Science Professional Certificate: https://learn.microsoft.com/en-us/credentials/certifications/azure-data-scientist/
• Microsoft Power Platform Professional Certificate: https://learn.microsoft.com/en-us/credentials/certifications/power-platform-fundamentals/
• Microsoft Azure AI Fundamentals: https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900/
• Microsoft Security, Compliance, and Identity Fundamentals: https://learn.microsoft.com/en-us/credentials/certifications/security-compliance-and-identity-fundamentals/
• Microsoft Azure DevOps Fundamentals: https://azure.microsoft.com/en-us/solutions/devops/tutorial

Meta

• Meta Blueprint: https://www.facebookblueprint.com/
• Meta Spark: https://spark.meta.com/
• Meta AI: https://ai.meta.com/
• Meta AR/VR: https://www.meta.com/
• Meta Social Media Marketing: https://www.coursera.org/professional-certificates/facebook-social-media-marketing
• Meta Digital Marketing Professional Certificate: https://www.coursera.org/professional-certificates/facebook-social-media-marketing
• Meta Data Science Professional Certificate: https://anyinstructor.com/meta-marketing-analytics-professional-certificate/
• Meta Software Engineering Immersive: https://blockclubchicago.org/2022/06/09/meta-chicago-formerly-facebook-launches-software-engineering-courses-to-bring-more-black-people-into-tech/

AWS

• AWS Cloud Practitioner Essentials: https://aws.amazon.com/training/classroom/aws-cloud-practitioner-essentials/
• AWS Developer Fundamentals: https://aws.amazon.com/training/learn-about/developer/
• AWS Certified Solution Architect - Associate: https://aws.amazon.com/certification/certified-solutions-architect-associate/
• AWS Certified Data Analytics - Associate: https://aws.amazon.com/certification/certified-data-analytics-specialty/
• AWS Certified Machine Learning - Specialist: https://aws.amazon.com/certification/certified-machine-learning-specialty/
• AWS Cloud Practitioner Professional Certificate: https://aws.amazon.com/certification/certified-cloud-practitioner/
• AWS Solutions Architect Professional Certificate: https://aws.amazon.com/certification/certified-solutions-architect-professional/
• AWS Data Analytics Professional Certificate: https://aws.amazon.com/certification/certified-data-analytics-specialty/
• AWS Machine Learning Professional Certificate: https://aws.amazon.com/certification/certified-machine-learning-specialty/

Other big universities

• Harvard University: CS50's Introduction to Computer Science: https://pll.harvard.edu/course/cs50-introduction-computer-science
• Stanford University: Introduction to Artificial Intelligence: https://www.guru99.com/artificial-intelligence-tutorial.html
• Massachusetts Institute of Technology: Introduction to Computer Science and Programming Using Python: https://www.edx.org/learn/computer-science/massachusetts-institute-of-technology-introduction-to-computer-science-and-programming-using-python
• University of California, Berkeley: Data Science Specialization: https://www.coursera.org/specializations/jhu-data-science
• University of Michigan: Python for Data Science: https://www.coursera.org/learn/python-for-applied-data-science-ai
• Georgia Institute of Technology: Machine Learning: https://en.wikipedia.org/wiki/Machine_learning
• University of Toronto: Neural Networks and Deep Learning: http://neuralnetworksanddeeplearning.com/

Comparing #Microsoft #Azure, #AWS (#Amazon #WebServices), and #GCP (#Google #Cloud #Platform)

1. Popularity and Market Share:

   - AWS: The most popular and widely adopted cloud platform with the largest market share.

   - Azure: A close second in terms of market share and popularity.

   - GCP: Growing rapidly but still behind AWS and Azure in terms of market share.

2. Global Data Centers and Regions:

   - AWS: Operates in 25 geographical regions worldwide.

   - Azure: Operates in 60+ regions, with plans for further expansion.

   - GCP: Operates in 24 regions globally.

3. Compute Services:

   - AWS: Offers Amazon EC2 for virtual machines.

   - Azure: Provides Azure Virtual Machines.

   - GCP: Offers Google Compute Engine.

4. Container Services:

   - AWS: Amazon ECS and EKS for container management.

   - Azure: Azure Kubernetes Service (AKS) and Azure Container Instances.

   - GCP: Google Kubernetes Engine (GKE) for container orchestration.

5. Serverless Computing:

   - AWS: AWS Lambda for serverless functions.

   - Azure: Azure Functions.

   - GCP: Google Cloud Functions.

6. Storage Services:

   - AWS: Amazon S3 for object storage, Amazon EBS for block storage.

   - Azure: Azure Blob Storage, Azure Disk Storage.

   - GCP: Google Cloud Storage, Google Persistent Disk.

7. Databases:

   - AWS: Amazon RDS (Relational Database Service), Amazon DynamoDB (NoSQL).

   - Azure: Azure SQL Database, Azure Cosmos DB (NoSQL).

   - GCP: Cloud SQL, Cloud Spanner (globally distributed relational), Firestore (NoSQL).

8. Networking:

   - AWS: Amazon VPC (Virtual Private Cloud), AWS Direct Connect.

   - Azure: Azure Virtual Network, ExpressRoute.

   - GCP: Virtual Private Cloud (VPC), Dedicated Interconnect.

9. Analytics and Big Data:

   - AWS: Amazon EMR, Redshift, Athena, Glue.

   - Azure: Azure HDInsight, Azure Databricks, Azure Data Lake.

   - GCP: BigQuery, Dataprep, Dataflow.

10. Machine Learning and AI:

    - AWS: Amazon SageMaker, Lex, Rekognition.

    - Azure: Azure Machine Learning, Cognitive Services.

    - GCP: AI Platform, Vision AI, Natural Language Processing.

11. Identity and Security:

    - AWS: AWS Identity and Access Management (IAM), Cognito.

    - Azure: Azure Active Directory (AD), Azure Identity Protection.

    - GCP: Google Identity and Access Management (IAM), Identity-Aware Proxy.

12. DevOps and Management Tools:

    - AWS: AWS CloudFormation, AWS CodeDeploy.

    - Azure: Azure DevOps, Azure Resource Manager.

    - GCP: Google Cloud Deployment Manager, Cloud Source Repositories.

13. Pricing and Cost Management:

    - Pricing models vary across services and regions. Detailed cost analysis is essential to choose the most cost-effective solution.

14. Support and Documentation:

    - All three providers offer extensive documentation, a range of support plans, and active user communities.

15. Hybrid and Multi-Cloud:

    - AWS offers AWS Outposts for hybrid deployments.

    - Azure provides Azure Arc for managing resources across on-premises, multi-cloud, and edge environments.

    - GCP offers Anthos for managing applications across hybrid and multi-cloud environments.

16. Compliance and Certifications:

    - AWS, Azure, and GCP comply with various industry standards and hold certifications like ISO, SOC, and HIPAA.

17. Specialized Services:

    - Each cloud provider offers unique, specialized services. For example, AWS has AWS Lambda, Azure has Azure DevTest Labs, and GCP has BigQuery ML.

18. Customer Base:

    - AWS has a diverse customer base, including startups, enterprises, and government agencies.

    - Azure is popular among enterprises, especially those already using Microsoft products.

    - GCP attracts startups and enterprises looking for machine learning and data analytics capabilities.

19. Ecosystem and Partnerships:

    - AWS has a vast ecosystem of partners and integrations.

    - Azure leverages Microsoft's partnerships, especially in the enterprise space.

    - GCP focuses on partnerships for AI and data analytics.

20. Licensing and Vendor Lock-In:

    - Consider the implications of vendor lock-in when choosing a cloud provider. Each has its own set of proprietary services.

In summary, the choice between AWS, Azure, and GCP depends on your specific needs, existing technologies, and preferences. It's often a good idea to perform a thorough evaluation of your requirements and conduct cost comparisons before making a decision. Each provider offers a free tier and credits to help you get started and explore their services.

#List of some popular #AWS #services

1. Amazon EC2 (Elastic Compute Cloud):

   - Description: Virtual servers in the cloud that you can configure and scale as needed.

   - #AWS #EC2 #VirtualServers

2. Amazon S3 (Simple Storage Service):

   - Description: Scalable object storage for storing and retrieving data, such as files or backups.

   - #AWS #S3 #ObjectStorage

3. Amazon RDS (Relational Database Service):

   - Description: Managed database service for popular databases like MySQL, PostgreSQL, and more.

   - #AWS #RDS #ManagedDatabases

4. Amazon Lambda:

   - Description: Serverless computing service that lets you run code in response to events.

   - #AWS #Lambda #Serverless

5. Amazon VPC (Virtual Private Cloud):

   - Description: Networking service that allows you to create isolated networks in the AWS cloud.

   - #AWS #VPC #Networking

6. Amazon ECS (Elastic Container Service):

   - Description: Managed container orchestration service for running Docker containers.

   - #AWS #ECS #Containers

7. Amazon Redshift:

   - Description: Data warehousing service for analyzing large datasets.

   - #AWS #Redshift #DataWarehousing

8. Amazon SNS (Simple Notification Service):

   - Description: Messaging service for sending notifications and alerts.

   - #AWS #SNS #Notifications

9. Amazon SQS (Simple Queue Service):

   - Description: Managed message queue service for decoupling components in applications.

   - #AWS #SQS #MessageQueue

10. Amazon CloudWatch:

    - Description: Monitoring and logging service to gain insights into AWS resources and applications.

    - #AWS #CloudWatch #Monitoring

11. Amazon Elastic Beanstalk:

    - Description: Platform as a Service (PaaS) for deploying and managing web applications.

    - #AWS #ElasticBeanstalk #PaaS

12. Amazon DynamoDB:

    - Description: Managed NoSQL database service for fast and scalable data storage.

    - #AWS #DynamoDB #NoSQL

13. AWS IAM (Identity and Access Management):

    - Description: Service for controlling access to AWS resources securely.

    - #AWS #IAM #Security

14. AWS Glue:

    - Description: Fully managed ETL (Extract, Transform, Load) service for data preparation.

    - #AWS #Glue #ETL

15. Amazon Route 53:

    - Description: Scalable and highly available domain name system (DNS) web service.

    - #AWS #Route53 #DNS

16. AWS Lambda Layers:

    - Description: Share code and resources across multiple Lambda functions.

    - #AWS #LambdaLayers #Serverless

17. AWS Elastic Load Balancing:

    - Description: Automatically distribute incoming traffic across multiple EC2 instances.

    - #AWS #ELB #LoadBalancing

18. AWS Step Functions:

    - Description: Coordinate multiple AWS services into serverless workflows.

    - #AWS #StepFunctions #Serverless

19. Amazon Aurora:

    - Description: High-performance relational database compatible with MySQL and PostgreSQL.

    - #AWS #Aurora #Database

20. Amazon CloudFront:

    - Description: Content delivery network (CDN) service for faster content delivery.

    - #AWS #CloudFront #CDN

#AWS #Identity and #Access #Management (#IAM)

AWS Identity and Access Management (IAM) is like having a set of keys to access different rooms in a building. Let me explain it in simple terms:

__1. IAM Users:__

   - Imagine the building as your AWS account, and each room inside the building as a specific service or resource in AWS, like a storage area, a database, or a server.

   - Now, think of IAM users as people who need to access these rooms. Each user gets their own key.

__2. IAM Groups:__

   - Sometimes, you have groups of people who need access to the same rooms. IAM groups are like groups of users who share access to specific services.

   - Instead of giving each person a key, you can give a key to the group leader, and everyone in the group gets access to the same rooms.

__3. IAM Policies:__

   - Policies are like rules or instructions written on a piece of paper that say who can access which rooms and what they can do inside those rooms.

   - For example, you can have a policy that says, "User A can access Room 1 and Room 2 but can only read in Room 1, not delete anything."

__4. IAM Roles:__

   - Roles are like special passes that you give to temporary visitors. They are not for users but for services or applications.

   - These passes specify what a service can do and which rooms it can access. For example, you can have a role for a backup service that allows it to access your storage room for backup purposes.

__5. Root User:__

   - The root user is like the owner of the building who has access to all rooms and can give keys and set rules for others.

   - It's essential to keep the root user's key safe and not use it for everyday tasks to ensure security.

__6. Multifactor Authentication (MFA):__

   - MFA is like adding an extra layer of security. It's like needing both a key and a fingerprint to open a door.

   - With MFA, even if someone gets hold of your key, they can't access a room without your fingerprint (or another authentication method).

__7. Access Control:__

   - IAM helps you control who can enter which rooms, what they can do there, and when they can access them.

   - You can specify permissions precisely, so someone might have access to one room but not another.

In summary, AWS IAM is like being the manager of a building, deciding who can access which rooms, what they can do in those rooms, and keeping everything secure by providing keys, passes, and rules to the right people or services. It helps you control access to your AWS resources and keep your AWS account safe.

#IAMBasics ,#AWSIAM ,#AccessControl ,#SecurityInAWS ,#IAMUsers ,#IAMGroups ,#IAMPolicies ,#IAMRoles ,#AWSRootUser ,#MFAinAWS ,#AccessManagement ,#AWSAccessKeys ,#AWSPermissions ,#IAMBestPractices ,#AWSIdentity ,#AWSAuthorization ,#IAMSecurity ,#IAMRolesandPolicies ,#IAMAuthentication ,#IAMSecurityModel

#Amazon #AWS #CHEATSHEET

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|                   AWS CHEAT SHEET                           |

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**AWS Basics:**

1. **AWS Account:**

   - Sign up for an AWS account at [AWS Console](https://aws.amazon.com/).

2. **Regions and Availability Zones:**

   - AWS infrastructure is divided into regions and further into availability zones.

**AWS Services:**

3. **Compute Services:**

   - EC2: Elastic Compute Cloud for virtual machines.

   - ECS: Elastic Container Service for container management.

   - Lambda: Serverless compute service.

4. **Storage Services:**

   - S3: Simple Storage Service for scalable object storage.

   - EBS: Elastic Block Store for block-level storage.

   - Glacier: Low-cost archive storage.

5. **Database Services:**

   - RDS: Relational Database Service for managed databases.

   - DynamoDB: NoSQL database service.

   - Redshift: Data warehousing service.

6. **Networking Services:**

   - VPC: Virtual Private Cloud for network isolation.

   - Route 53: DNS web service.

   - ELB: Elastic Load Balancer for distributing traffic.

7. **Security and Identity:**

   - IAM: Identity and Access Management for user and role management.

   - KMS: Key Management Service for encryption.

   - Cognito: Identity and user management.

8. **Developer Tools:**

   - CodeDeploy: Automate code deployments.

   - CodePipeline: Continuous integration and delivery service.

   - CloudFormation: Infrastructure as Code (IaC) tool.

9. **Analytics Services:**

   - EMR: Elastic MapReduce for big data processing.

   - Athena: Serverless query service.

   - QuickSight: Business intelligence service.

10. **Machine Learning Services:**

    - SageMaker: Managed machine learning platform.

    - Comprehend: Natural language processing.

    - Rekognition: Image and video analysis.

11. **Application Integration:**

    - SQS: Simple Queue Service for message queuing.

    - SNS: Simple Notification Service for event notifications.

    - Step Functions: Serverless workflow service.

**Working with AWS:**

12. **AWS CLI:**

    - `aws configure`: Set up AWS CLI credentials.

    - `aws s3 ls`: List S3 buckets.

    - `aws ec2 describe-instances`: Describe EC2 instances.

13. **AWS Management Console:**

    - Access the AWS web-based management console.

    - Navigate and manage AWS resources through the console.

14. **AWS Billing and Cost Management:**

    - Monitor and manage AWS costs through the billing dashboard.

15. **AWS Documentation:**

    - [AWS Documentation](https://aws.amazon.com/documentation/): Comprehensive documentation for AWS services.

**AWS Resources:**

16. **AWS Well-Architected Framework:**

    - [AWS Well-Architected Framework](https://aws.amazon.com/architecture/well-architected/): Best practices for designing well-architected systems on AWS.

17. **AWS Whitepapers:**

    - [AWS Whitepapers](https://aws.amazon.com/whitepapers/): In-depth technical documents on various AWS topics.

18. **AWS Training and Certification:**

    - [AWS Training and Certification](https://aws.amazon.com/training/): Learn AWS skills and get certified.

what is difference between #user and #role in #aws #iam

In AWS IAM, both users and roles can be used to grant access to AWS resources, but there are some key differences between the two.

Users:

1. A user is an identity within AWS that represents a person or an application that interacts with AWS resources.

2. Users are assigned a unique set of security credentials (such as a username and password) that are used to authenticate their identity and control their access to resources.

3. Users can be granted permissions to access AWS resources directly through policies attached to their user account.

4. Users can be added to groups to simplify permission management and to assign permissions to a group of users at once.

Roles:

1. A role is an AWS IAM entity that defines a set of permissions for making AWS service requests.

2. Unlike a user, a role doesn't have any credentials, such as a password or access key. Instead, roles are assumed by trusted entities, such as an AWS service or a user.

3. Roles can be used to delegate access to AWS resources across accounts, allowing users from one account to access resources in another account.

4. Roles can be associated with AWS services, such as EC2 instances, to grant temporary access to resources when needed.

Overall, while users are typically used to represent human users or applications that need access to AWS resources, roles are used to define a set of permissions that can be assumed by trusted entities. Roles provide a flexible way to manage access to resources across accounts and can be used to grant temporary access to resources when needed.

What are the different cloud platforms available today

There are several cloud platforms available today, and while many of them offer similar services, there are differences in their offerings and approach. Here are some key differences between different cloud platforms:

1. Amazon Web Services (AWS): AWS is one of the largest and most popular cloud platforms, offering a wide range of services and features. It is known for its scalability and flexibility and is often used by enterprise-level organizations.

2. Microsoft Azure: Azure is Microsoft's cloud platform, offering similar services to AWS, but with a focus on integration with Microsoft products and services.

3. Google Cloud Platform (GCP): GCP is Google's cloud platform, offering services for computing, storage, and networking. It is known for its speed and ease of use and is often used by startups and smaller organizations.

4. IBM Cloud: IBM Cloud offers a wide range of services for cloud computing, including AI, analytics, and blockchain. It is often used by enterprises that require high levels of security and compliance.

5. Oracle Cloud: Oracle Cloud is a cloud platform that offers a range of services, including computing, storage, and networking. It is known for its integration with Oracle software and databases and is often used by organizations that already use Oracle products.

6. Alibaba Cloud: Alibaba Cloud is a cloud platform that is popular in Asia, offering services for computing, storage, and networking. It is often used by organizations that require low-latency connections to users in Asia.

In summary, while all of these cloud platforms offer similar services, there are differences in their approach, target audience, and feature sets. Organizations should carefully evaluate each platform based on their needs and requirements before choosing a cloud provider.