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Special Combo (Machine Learning + Python Programming)

Special Combo (Machine Learning + Python Programming)

Embark on a transformative journey into the realms of Machine Learning and Python programming with our comprehensive course. Designed for both beginners and seasoned enthusiasts, this dynamic program merges theoretical knowledge with hands-on practicality to empower you in the world of data science.

Unlock the potential of Python, the versatile programming language driving innovations across industries. From fundamental syntax to advanced libraries like NumPy, Pandas, and Matplotlib, master the tools essential for data manipulation, analysis, and visualization.

Dive deep into the heart of Machine Learning, understanding algorithms, model training, and evaluation techniques. Explore supervised and unsupervised learning, delve into neural networks, and grasp the intricacies of deep learning.

With expert guidance and interactive exercises, accelerate your proficiency and gain the confidence to tackle real-world projects. Whether you’re aiming for a career upgrade or pursuing personal enrichment, this course equips you with the skills to thrive in the data-driven landscape.

Original price was: ₹5,000.00.Current price is: ₹1,999.00.

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Cloud Computing With AWS

Demo Lecture

Course Curriculum

Module 1: Introduction to Cloud Computing

Overview of Cloud Computing
- Definition, Characteristics, and Benefits
- Types of Cloud Services: IaaS, PaaS, SaaS
- Deployment Models: Public, Private, Hybrid, and Community Clouds
History and Evolution of Cloud Computing
- From On-Premises to the Cloud
- Major Milestones and Innovations
Why AWS for Cloud Computing?
- AWS Overview and Market Leadership
- Global Infrastructure: Regions and Availability Zones

Module 2: Core Concepts of Cloud Computing

Virtualization Basics
- AWS EC2 Instances as an Example of Virtual Machines
- Amazon ECS and EKS for Container Management
Networking in the Cloud
- Amazon VPC: Subnets, Route Tables, and Gateways
- Elastic Load Balancing (ELB) and AWS Direct Connect
Storage in the Cloud
- AWS S3 for Object Storage: Buckets, Access Policies, and Lifecycle Management
- Amazon EBS for Block Storage

Module 3: Cloud Infrastructure and Architecture

Scalability and Elasticity
- Using AWS Auto Scaling for Elastic Workloads
- Horizontal and Vertical Scaling with Amazon EC2
Cloud-Native Architecture
- Serverless Computing with AWS Lambda
- Orchestrating Containers with Amazon ECS and EKS
High Availability and Disaster Recovery
- Multi-Region Deployments with AWS Route 53
- Backup Strategies Using AWS Backup

Module 4: Security in the Cloud

Cloud Security Fundamentals
- Shared Responsibility Model with AWS
- Identity and Access Management (IAM) for User Roles and Permissions
Data Security
- Encryption Using AWS Key Management Service (KMS)
- Monitoring and Auditing with AWS CloudTrail
Compliance and Governance
- Managing Compliance with AWS Config and Artifact

Module 5: Cloud Service Models

Infrastructure as a Service (IaaS)
- Provisioning EC2 Instances
- Managing Storage and Networking with Amazon VPC and Elastic IPs
Platform as a Service (PaaS)
- Deploying Applications Using AWS Elastic Beanstalk
Software as a Service (SaaS)
- Exploring AWS Marketplace for SaaS Solutions

Module 6: DevOps and Automation in the Cloud

Cloud and DevOps Integration
- Building CI/CD Pipelines with AWS CodePipeline and CodeDeploy
Infrastructure as Code (IaC)
- Automating Resource Provisioning Using AWS CloudFormation and Terraform
Monitoring and Logging
- Application Monitoring with Amazon CloudWatch

Module 7: Cloud Economics and Optimization

Cost Management in AWS
- Exploring AWS Pricing Models
- Using AWS Budgets and Cost Explorer to Track and Optimize Costs
Resource Optimization
- Reserved Instances and Savings Plans in EC2
- Using Trusted Advisor for Recommendations
Sustainability in the Cloud
- AWS’s Commitment to Renewable Energy and Carbon Footprint Reduction

Module 8: Emerging Trends in Cloud Computing

Edge Computing with AWS
- AWS IoT Greengrass and AWS Wavelength
AI and Machine Learning in the Cloud
- Using Amazon Sage Maker for Machine Learning Workflows
Hybrid and Multi-Cloud Strategies
- Managing Hybrid Environments with AWS Outposts

Module 9: Projects