Radical Technologies
DATA SCIENCE
★★★★★
(2,095 ratings)  50,000+ Student

DESIGNING AND IMPLEMENTING DATA SCIENCE SOLUTION ON AZURE - DP 100

The Designing and Implementing Data Science Solution on Azure – DP 100 course by Radical Technologies in Bangalore offers comprehensive training to master data science solutions using Azure. This certification course covers data exploration, model training, and deployment using Azure Machine Learning. With hands-on projects and expert guidance, students gain practical skills in designing scalable data science models. The program includes job assistance to help participants secure roles in the industry. Ideal for aspiring data scientists, this course equips learners with the knowledge to excel in Azure-based data science careers.

RT
Radical Technologies
50,000+ English 60 hours Weekdays / Weekends Classroom / Online / Corporate
Online / Classroom

DESIGNING AND IMPLEMENTING DATA SCIENCE SOLUTION ON AZURE - DP 100

IT Training Programme

Duration 60 hours
Batch Type Weekdays / Weekends
Mode of Training Classroom / Online / Corporate
Locations Pune, Bangalore, Kochi
Language English
Certification Globally Recognized
Call Now

100% placement assistance

What you'll learn

Understand core concepts and architecture from the ground up
Get hands-on with the tools used by working professionals
Build real-world projects you can add to your portfolio
Learn industry best practices and coding standards
Practice with real datasets and real-world scenarios
Prepare for certification and technical interviews
Work on collaborative, team-based exercises
Apply performance tuning and optimization techniques
Understand how the technology fits into a larger ecosystem
Complete assignments reviewed by mentors

Programme Overview

4 sections covering the complete curriculum — a single, progressive learning arc.

60 hours
Training Duration
4
Core Modules
82
Total Lessons
4.4
Average Rating
50K+
Students Trained
01

Foundations & Core Concepts

Get hands-on with the fundamentals and architecture — the building blocks for everything that follows.

Fundamentals Architecture Setup
02

Hands-On Practical Training

Work through real exercises and assignments designed to mirror what you will do on the job.

Practicals Assignments Labs
03

Real-World Projects

Apply what you have learned to end-to-end projects that go straight into your portfolio.

Projects Portfolio Case Studies
04

Advanced Techniques

Go beyond the basics with advanced concepts, integrations and production-grade practices.

Advanced Integration Best Practices
05

Ecosystem Integration

Understand how this technology connects with the broader tools and platforms used in the industry.

Ecosystem Tools Platforms
06

Performance & Interview Prep

Master optimization techniques and prepare for the technical interview questions employers actually ask.

Optimization Interview Prep Certification

Who is this programme for?

Whether you're already writing code, working with data, or supporting applications today — this programme is built to take you into a DATA SCIENCE role.

Software Developers

Engineers who want to add this skill set to their toolkit

Analysts & Consultants

Professionals moving into a more technical, hands-on role

IT Professionals

System admins and support engineers upskilling into a new domain

Fresh Graduates

CS/IT graduates aiming for a job-ready technical role

Course Curriculum

4 sections  •  82 lessons  •  60 hours

01 Design and prepare a machine learning solution

Design a machine learning solution

Determine the appropriate compute specifications for a training workload
Describe model deployment requirements
Select which development approach to use to build or train a model

Manage an Azure Machine Learning workspace

Create an Azure Machine Learning workspace
Manage a workspace by using developer tools for workspace interaction
Set up Git integration for source control

Manage data in an Azure Machine Learning workspace

Select Azure Storage resources
Register and maintain datastores
Create and manage data assets

Manage compute for experiments in Azure Machine Learning

Create compute targets for experiments and training
Select an environment for a machine learning use case
Configure attached compute resources, including Apache Spark pools
Monitor compute utilization
02 Explore data and train models

Explore data by using data assets and data stores

Access and wrangle data during interactive development
Wrangle interactive data with Apache Spark

Create models by using the Azure Machine Learning designer

Create a training pipeline
Consume data assets from the designer
Use custom code components in designer
Evaluate the model, including responsible AI guidelines

Use automated machine learning to explore optimal models

Use automated machine learning for tabular data
Use automated machine learning for computer vision
Use automated machine learning for natural language processing (NLP)
Select and understand training options, including preprocessing and algorithms
Evaluate an automated machine learning run, including responsible AI guidelines

Use notebooks for custom model training

Develop code by using a compute instance
Track model training by using MLflow
Evaluate a model
Train a model by using Python SDK
Use the terminal to configure a compute instance

Tune hyperparameters with Azure Machine Learning

Select a sampling method
Define the search space
Define the primary metric
Define early termination options
03 Prepare a model for deployment

Run model training scripts

Configure job run settings for a script
Configure compute for a job run
Consume data from a data asset in a job
Run a script as a job by using Azure Machine Learning
Use MLflow to log metrics from a job run
Use logs to troubleshoot job run errors
Configure an environment for a job run
Define parameters for a job

Implement training pipelines

Create a pipeline
Pass data between steps in a pipeline
Run and schedule a pipeline
Monitor pipeline runs
Create custom components
Use component-based pipelines

Manage models in Azure Machine Learning

Describe MLflow model output
Identify an appropriate framework to package a model
Assess a model by using responsible AI guidelines
04 Deploy and retrain a model

Deploy a model

Configure settings for online deployment
Configure compute for a batch deployment
Deploy a model to an online endpoint
Deploy a model to a batch endpoint
Test an online deployed service
Invoke the batch endpoint to start a batch scoring job

Apply machine learning operations (MLOps) practices

Trigger an Azure Machine Learning job, including from Azure DevOps or GitHub
Automate model retraining based on new data additions or data changes
Define event-based retraining triggers

Tools & Technologies

Every tool listed here is installed, configured and used in a hands-on lab session.

Core Tools

Hands-On Labs

Practical Environment

Industry-Standard Tools

Real-World Setup

Guided Exercises

Skill Building

Sample Datasets

Practice Material

Practice & Projects

Mini Projects

Applied Practice

Assignments

Mentor Reviewed

Doubt Sessions

Live Support

Career Readiness

Resume Building

Career Support

Mock Interviews

Interview Prep

Certification Prep

Global Recognition

Deployment & Delivery

Production Practices

Real-World Ready

Best Practices

Industry Standards

82+
Hands-On Lessons
4
Core Modules
60 hours
Training Duration
100%
Practical Training

You don't just learn DESIGNING AND IMPLEMENTING DATA SCIENCE SOLUTION ON AZURE - DP 100. You ship it.

Three major projects, each mirroring how production teams actually work — from guided foundations to a portfolio-ready capstone.

PROJECT // 01

Guided Foundation Project

Requirement Analysis

Guided Implementation

Mentor Review

Iteration

Foundation Beginner

Apply the fundamentals in a structured, mentor-reviewed project

Take the core concepts from the first half of the curriculum and apply them to a realistic scenario, with guidance and feedback from your mentor at every step.

Structured project brief
Step-by-step implementation
Mentor feedback and review
Documented outcome
Stack Core Concepts Best Practices
PROJECT // 02

Applied Practice Project

Scenario Design

Independent Build

Testing & Validation

Peer Review

Applied Intermediate

Build a more independent project mirroring real production scenarios

Work through a project that combines multiple concepts from the curriculum, closer to how work is actually structured on the job — less hand-holding, more ownership.

End-to-end implementation
Testing and validation
Documentation
Peer/mentor review
Stack Applied Skills Testing
PROJECT // 03

Capstone Project

Planning

End-to-End Build

Review & Refinement

Presentation

Capstone Advanced

Take a project from requirements to a polished, portfolio-ready deliverable

Your final project — plan, build, test and present a complete solution using everything covered in the curriculum, reviewed by mentors before you graduate.

Complete working solution
Presentation-ready documentation
Mentor sign-off
Portfolio-ready deliverable
Stack Full Curriculum Portfolio

All 3 projects go directly into your portfolio & resume — reviewed by mentors before you graduate.

See Sample Project Reports

Upcoming Batches

No upcoming batches scheduled right now. Enquire to get notified.

Why Radical Technologies

Live Online Training
  • Highly practical oriented training
  • Installation support on your system
  • 24/7 Email and Phone support
  • 100% Placement Assistance
  • Global Certification Preparation
  • Trainer-Student Interactive Portal
  • Assignments and Projects by Mentors
Enroll Now
Live Classroom Training
  • Weekend / Weekdays / Morning / Evening batches
  • 80:20 Practical and Theory ratio
  • Real-life Case Studies
  • Easy make-up for missed sessions
  • PSI | Kryterion | Redhat Test Centers
  • Lifetime Video Classroom Access (coming soon)
  • Resume Prep and Mock Interviews
Enroll Now
Self-Paced Training
  • Learn 300+ courses at your own time
  • 50,000+ Satisfied Learners
  • Course Completion Certificate
  • Practical Labs available
  • Mentor Support available
  • Doubt Clearing Session available
  • 10% Discounted Global Certification
Enroll Now

Like the Curriculum? Let's Get Started

Join 50,000+ students already enrolled at Radical Technologies

Enroll Now

Global Certification

Radical Technologies is the leading IT certification institute in Pune, offering globally recognized certifications across various domains. With expert trainers and comprehensive materials, we ensure students gain in-depth knowledge and hands-on experience to excel in their careers. Our certification programs are tailored to meet industry standards — from cloud technologies to data science — empowering individuals to stay ahead in the ever-evolving tech landscape.

Certificate of Completion

Career Services

At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalised resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career.

Career Support

Course Completed? Need next steps?
Need Interview Supports?
Need Job Assistance?
Came from any other Institute?

Join our Brush-up Session & get support until you find a job!

Get Started

Radical Learning Eco-System

Exam Simulator

Cloud SandBox

Hands-on Cloud Lab

Developer Coding Ground

Student Reviews

4.4★
Average learner rating
50K+
Students trained
30+
Hiring companies alumni work at
100%
Placement assistance
4.4
★★★★★

Course Rating

★★★★★
62%
★★★★☆
21%
★★★☆☆
10%
★★☆☆☆
4%
★☆☆☆☆
3%

Our Alumni Work At

Accenture
Amazon
Avisys Services
Birlasoft
Capgemini
Catchpoint
Cognizant
Darwish Cybertech
DataVision
GiBots
Google
Groots Software
HCL Technologies
IBM
Info Gain
Infosys
ITCube Solutions
KPIT
L&T Infotech
Microsoft
Mphasis
mPhatek
Oracle
Quantbit Technologies
Saina Cloud
TCS
Tech Mahindra
Wipro
YASH Technologies
Zensar Technologies
Accenture
Amazon
Avisys Services
Birlasoft
Capgemini
Catchpoint
Cognizant
Darwish Cybertech
DataVision
GiBots
Google
Groots Software
HCL Technologies
IBM
Info Gain
Infosys
ITCube Solutions
KPIT
L&T Infotech
Microsoft
Mphasis
mPhatek
Oracle
Quantbit Technologies
Saina Cloud
TCS
Tech Mahindra
Wipro
YASH Technologies
Zensar Technologies