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Radical Data Science PG program consists of Practical learning of Data Science with Python & R, Apache Spark & Scala, AI & Deep Learning with TensorFlow, Tableau. Consists of 25 Projects | 200 + Assignments and 50 hours of Mock interview session. You will acquire a knowledge of 4+ year experienced data scientist.
This program is good for freshers and up to 3 – 4 years of industry experienced professional.Those who have career gap
- Join Our Live Online Classes
Why Radical Technologies
Live Online Training
Highly practical oriented training
Installation of Software On your System
24/7 Email and Phone Support
100% Placement Assistance until you get placed
Global Certification Preparation
Trainer Student Interactive Portal
Assignments and Projects Guided by Mentors
And Many More Features
Course completion certificate and Global Certifications are part of our all Master Program
Live Classroom Training
Weekend / Weekdays / Morning / Evening Batches
80:20 Practical and Theory Ratio
Real-life Case Studies
Easy Coverup if you missed any sessions
PSI | Kryterion | Redhat Test Centers
Life Time Video Classroom Access ( coming soon )
Resume Preparations and Mock Interviews
And Many More Features
Course completion certificate and Global Certifications are part of our all Master Program
Self Paced Training
Self Paced Learning
Learn 300+ Courses at Your Own Time
50000+ Satisfied Learners
Course Completion Certificate
Practical Labs Available
Mentor Support Available
Doubt Clearing Session Available
Attend Our Virtual Job Fair
10% Discounted Global Certification
Course completion certificate and Global Certifications are part of our all Master Program
Live Online Training
Highly practical oriented training
Installation of Software On your System
24/7 Email and Phone Support
100% Placement Assistance until you get placed
Global Certification Preparation
Trainer Student Interactive Portal
Assignments and Projects Guided by Mentors
And Many More Features
Course completion certificate and Global Certifications are part of our all Master Program
Live Classroom Training
Weekend / Weekdays / Morning / Evening Batches
80:20 Practical and Theory Ratio
Real-life Case Studies
Easy Coverup if you missed any sessions
PSI | Kryterion | Redhat Test Centers
Life Time Video Classroom Access ( coming soon )
Resume Preparations and Mock Interviews
And Many More Features
Course completion certificate and Global Certifications are part of our all Master Program
Self Test Training
300+ Technologies - Learn at your Convenience
4500+ High Quality Videos
Self Paced Training By Experts
Self Paced Hands-On Practical LABS
Cloud Sand Boxes
Do Projects and Assignments with Live LABS
100+ Exam Simulators & Discounted Vouchers
Live Mentor Support - By 10+ Years Experts
Course completion certificate and Global Certifications are part of our all Master Program
Overview
Why enroll Redhat Linux
Why enroll for LINUX RHEL 8 course ?
Course Benefits
- Post Graduate Diploma without Spending full time in College
- Eligible for Ofqual regulates qualifications – UK Certified and World Recognised programs
- Level 7 Program recognised world wide for your Higher studies
- Get recognised by High Value world recognised UK equal Master Degree
Designations
Want to become Engineer?
Want to become Engineer?
Want to become Engineer?
WhyTerraform ?
Multi-Cloud Support
Terraform supports multiple cloud providers, including AWS, Azure, Google Cloud Platform (GCP), and others. This allows you to use a single tool and consistent workflow across different cloud environments, enabling hybrid and multi-cloud deployments.
Declarative Configuration
Terraform uses a declarative language to define infrastructure configurations. This means you specify the desired state of your infrastructure, and Terraform handles the provisioning and management to achieve that state. This approach is intuitive and allows for easier understanding and maintenance of infrastructure code.
Resource Graph
Terraform builds a dependency graph of your infrastructure resources based on their relationships and dependencies. This enables Terraform to determine the correct order of resource provisioning and manage complex infrastructures with ease.
Modularity and Reusability
Terraform encourages modularization and code reuse through the use of modules. Modules are self-contained units of Terraform configurations that can be reused across projects, teams, and environments. This promotes consistency, reduces duplication, and speeds up development.
State Management
Terraform maintains a state file that tracks the current state of your infrastructure. This state file is used to plan and apply changes, track resource attributes, and manage updates. Terraform's state management ensures consistency and facilitates collaboration among team members.
Plan and Apply Workflow
Terraform follows a plan and apply workflow, where changes to infrastructure are first planned and previewed before being applied. This allows you to review the proposed changes, identify potential issues, and apply changes safely, minimizing the risk of unintended consequences.
Extensibility
Terraform is highly extensible and integrates with a wide range of third-party tools and services. This includes integrations with configuration management tools, CI/CD pipelines, monitoring solutions, and more, allowing you to build comprehensive infrastructure automation workflows. While other IaC tools offer similar capabilities, Terraform's multi-cloud support, declarative configuration, resource graph, modularity, state management, workflow, and extensibility make it a popular choice for infrastructure automation in diverse environments. Additionally, Terraform's active community, robust documentation, and frequent updates contribute to its widespread adoption and continued development.
About your Terraform Certification Course
Terraform Skills Covered
Curriculum Designed by Experts
IMS – Linux | AWS | Devops Course Syllabus
Overview of tools covered
Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Regression Modelling , Scala Programming language, HDFS, Sqoop, FLume, Spark GraphX, Apache Cassandra, Spark, and Kafka
Python Statistics for Data Science Course Classroom / Online
Python Scripting allows programmers to build applications easily and rapidly. This course is an introduction to Python scripting, which focuses on the concepts of Python, it will help you to perform operations on variable types using Pycharm. You will learn the importance of Python in real time environment and will be able to develop applications based on Object Oriented Programming concept. End of this course, you will be able to develop networking applications with suitable GUI
Python Statistics for Data Science Course
Python Scripting allows programmers to build applications easily and rapidly. This course is an introduction to Python scripting, which focuses on the concepts of Python, it will help you to perform operations on variable types using Pycharm.
Python Statistics for Data Science Course
Python Scripting allows programmers to build applications easily and rapidly. This course is an introduction to Python scripting, which focuses on the concepts of Python, it will help you to perform operations on variable types using Pycharm.
Python Statistics for Data Science Course
Python Scripting allows programmers to build applications easily and rapidly. This course is an introduction to Python scripting, which focuses on the concepts of Python, it will help you to perform operations on variable types using Pycharm.
Python Statistics for Data Science Course
Python Scripting allows programmers to build applications easily and rapidly. This course is an introduction to Python scripting, which focuses on the concepts of Python, it will help you to perform operations on variable types using Pycharm.
Free Career Counselling
+91 8882400500
Global Certification
Terraform Course Projects in Seattle
Multi-Cloud
Deployment
Create Terraform configurations to provision identical infrastructure across multiple cloud providers such as AWS, Azure, and Google Cloud Platform. This project will help you understand how to leverage Terraform's multi-cloud support and manage resources in a heterogeneous cloud environment.
Highly Available Web Application
Design and deploy a highly available web application using Terraform. Configure load balancers, auto-scaling groups, database clusters, and other resources to ensure fault tolerance and scalability. Implement infrastructure as code best practices to manage the application's lifecycle.
Infrastructure Governance and Compliance
Implement infrastructure governance and compliance policies using Terraform to enforce security, compliance, and regulatory requirements. Define and enforce policies for resource tagging, access control, encryption, and configuration drift detection.
Container Orchestration with Kubernetes
Set up a Kubernetes cluster on a cloud provider using Terraform. Deploy and manage Kubernetes resources such as pods, services, and ingresses using Terraform configurations. Experiment with different deployment strategies and configurations to gain insights into Kubernetes orchestration.
Infrastructure Monitoring and Logging
Implement infrastructure monitoring and logging using Terraform and cloud-native services such as AWS CloudWatch, Azure Monitor, or Google Cloud Monitoring. Configure alerts, dashboards, and log sinks to monitor resource health, performance, and security.
Disaster Recovery (DR) Setup
Design and deploy a disaster recovery solution using Terraform to replicate infrastructure resources across regions or cloud providers. Configure automated failover mechanisms, data replication, and backup strategies to ensure business continuity and data resilience.
Microservices Architecture
Build a microservices architecture using Terraform to provision containerized services on a container orchestration platform such as Kubernetes or AWS ECS. Design modular Terraform configurations for each microservice and define service dependencies and communication channels.
Serverless Architecture
Explore serverless computing by using Terraform to provision serverless resources such as AWS Lambda functions, API Gateway endpoints, and DynamoDB tables. Build a serverless application that processes events, triggers functions, and stores data without managing servers or infrastructure.
Hybrid Cloud Deployment
Deploy a hybrid cloud infrastructure using Terraform to bridge on-premises data centers with public cloud environments. Configure hybrid networking, VPN connections, and hybrid cloud management tools to extend your infrastructure seamlessly across cloud and on-premises environments.
Continuous Integration and Delivery (CI/CD) Pipelines
Automate infrastructure deployment using Terraform within CI/CD pipelines. Integrate Terraform with version control systems, build tools, and deployment automation platforms to enable continuous delivery of infrastructure changes with automated testing and validation. These project ideas cover a range of scenarios and use cases that will allow you to apply Terraform's capabilities effectively and gain practical experience in infrastructure automation and management. Tailor these projects to your interests, expertise, and learning objectives to maximize their educational value.
Get Experience Of 4+ Years
IMS – Linux | AWS | Devops Course reviews
Redhat Linux System Administration - Roles and Responsibilities
L1 Tasks
1. Basic user account management (creating, modifying, and deleting users).
2. Password resets and account unlocks.
3. Basic file system navigation and management (creating, deleting, and modifying files and directories).
4. Basic troubleshooting of network connectivity issues.
5. Basic software installation and package management (installing and updating software packages).
6. Viewing system logs and checking for errors or warnings.
7. Running basic system health checks (CPU, memory, disk space).
8. Restarting services or daemons.
9. Monitoring system performance using basic tools (top, df, free).
10. Running basic commands to gather system information (uname, hostname, ifconfig).
L2 Tasks
1. Intermediate user account management (setting permissions, managing groups).
2. Configuring network interfaces and troubleshooting network connectivity issues.
3. Managing file system permissions and access control lists (ACLs).
4. Performing backups and restores of files and directories.
5. Installing and configuring system monitoring tools (Nagios, Zabbix).
6. Analyzing system logs for troubleshooting purposes.
7. Configuring and managing software repositories.
8. Configuring and managing system services (systemd, init.d).
9. Performing system updates and patch management.
10. Monitoring and managing system resources (CPU, memory, disk I/O).
L3 Tasks
1. Advanced user account management (LDAP integration, single sign-on).
2. Configuring and managing network services (DNS, DHCP, LDAP).
3. Configuring and managing storage solutions (RAID, LVM, NFS).
4. Implementing and managing security policies (firewall rules, SELinux).
5. Implementing and managing system backups and disaster recovery plans.
6. Configuring and managing virtualization platforms (KVM, VMware).
7. Performance tuning and optimization of system resources.
8. Implementing and managing high availability solutions (clustering, load balancing).
9. Automating system administration tasks using scripting (Bash, Python).
10. Managing system configurations using configuration management tools (Ansible, Puppet).
L1-L2 Transition Tasks
1. Learning basic shell scripting for automation tasks. 2. Understanding file system permissions and ownership. 3. Learning basic networking concepts (IP addressing, routing). 4. Learning how to use package management tools effectively. 5. Familiarizing with common Linux commands and utilities. 6. Understanding basic system architecture and components. 7. Learning basic troubleshooting techniques and methodologies. 8. Familiarizing with basic security principles and best practices. 9. Learning how to interpret system logs and diagnostic output. 10. Understanding the role and importance of system backups and restores.
L2-L3 Transition Tasks
1. Advanced scripting and automation techniques (error handling, loops).
2. Understanding advanced networking concepts (VLANs, subnetting).
3. Familiarizing with advanced storage technologies (SAN, NAS).
4. Learning advanced security concepts and techniques (encryption, PKI).
5. Understanding advanced system performance tuning techniques.
6. Learning advanced troubleshooting methodologies (root cause analysis).
7. Implementing and managing virtualization and cloud technologies.
8. Configuring and managing advanced network services (VPN, IDS/IPS).
9. Implementing and managing containerization technologies (Docker, Kubernetes).
10. Understanding enterprise-level IT governance and compliance requirements.
L3 Tasks and Beyond
1. Designing and implementing complex IT infrastructure solutions. 2. Architecting and implementing highly available and scalable systems. 3. Developing and implementing disaster recovery and business continuity plans. 4. Conducting security audits and vulnerability assessments. 5. Implementing and managing advanced monitoring and alerting systems. 6. Developing custom automation solutions tailored to specific business needs. 7. Providing leadership and mentorship to junior team members. 8. Collaborating with other IT teams on cross-functional projects. 9. Evaluating new technologies and making recommendations for adoption. 10. Participating in industry conferences, workshops, and training programs.
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