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PYTHON FOR DATASCIENCE TRAINING IN KOCHI

Join our intensive Python for Data Science training in Kochi! Learn essential Python programming skills and advanced data manipulation techniques. Gain hands-on experience with popular data science libraries like NumPy, Pandas, and Matplotlib. Explore data visualization, statistical analysis, and machine learning concepts. Our expert instructors will guide you through practical projects and real-world applications. Kickstart your career in data science today with our comprehensive training program in Kochi!

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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

Why enroll for LINUX RHEL 8 course ?

Course Benefits

Duration of Training : 60 hrs
Batch type : weekdays /weekends/ Customized Batches
Mode of Training: Offline / Online / Corporate Training
Projects Given : 2 Projects minimum
Trainer Profile : Experienced Faculty from IT Industry
Projects | Assignment | Scenarios and Used Case Studies

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

  • State Management

  • Terraform Modules

  • Dependency Management

  • Terraform CLI

  • Terraform Configuration Language (HCL)

  • Infrastructure as Code (IaC) Principles

  • Resource Provisioning

  • Terraform Providers

  • Terraform Workspaces

  • Terraform Best Practices

Curriculum Designed by Experts

Python for Data Science Course Syllabus

1: Introduction / 2: Variables & Data Types

1: Introduction

What is Python..?
A Brief history of Python
Why Should I learn Python..?
Installing Python
How to execute Python program
Write your first program

2: Variables & Data Types

Variables
Numbers
String
Lists ,Tuples & Dictionary

3: Conditional Statements & Loops / 4: Control Statements

3: Conditional Statements & Loops

if…statement
if…else statement
elif…statement
The while…Loop
The for….Loop

4: Control Statements

continue statement
break statement
pass statement

5: Functions / 6: Modules & Packages

5: Functions

Define function
Calling a function
Function arguments
Built-in function

6: Modules & Packages

Modules
How to import a module…?
Packages
How to create packages

7: Classes & Objects / 8: Files & Exception Handling

7: Classes & Objects

Introduction about classes & objects
Creating a class & object
Inheritance
Methods Overriding
Data hiding

8: Files & Exception Handling

Writing data to a file
Reading data from a file
Read and Write data from csv file
try…except
try…except…else
finally
os module

Module 2:Introduction to Machine learning(ML) / Module 3:NumPy Arrays

Module 2:Introduction to Machine learning(ML) 

What is Machine learing?
Overview about sci-kit learn and tensorflow
Types of ML
Some complementing fields of ML
ML algorithms
Machine learning examples

Module 3:NumPy Arrays

Creating multidimensional array
NumPy-Data types
Array attributes
Indexing and Slicing
Creating array views and copies
Manipulating array shapes
I/O with NumPy