Microsoft Certified Training Program

Data on Cloud Job-oriented Program with 8 Certifications

Elevate your career with our Data on Cloud Job-Oriented Program. Gain 8 certifications and practical expertise to excel in the rapidly growing field of cloud data. 

15 Weeks

Intensive Training

Live Sessions

Expert Instructors

100% Job

Placement Support

8 Certificates

Microsoft Official

4.5 ( 141 Ratings )
Learners
40000 +

About Our Course

The Cloud Job-Oriented Program with 8 Certifications is made to get you ready for real jobs in cloud and data. 🚀 In this course, you’ll train for 8 popular certifications: AWS Cloud Practitioner, AZ-900, DP-900, DEA-C01, DP-700, PL-300, DP-600, and DP-300

You’ll learn a mix of cloud skills (AWS + Azure), data engineering, analytics, BI, and database management—all the things companies are looking for today. By the time you finish, you’ll not only have the certifications but also hands-on skills and project experience to confidently apply for roles like Cloud Engineer, Data Engineer, Power BI Analyst, Fabric Engineer, Database Administrator, Big Data Engineer, or Cloud Data Architect.

Who Should Enroll in This Program?

IT Professionals

If you’re already working in tech but want to advance into high-demand roles such as Cloud Engineer, Data Engineer, or DevOps Engineer, this program will give you the skills, certifications, and hands-on experience to take your career to the next level.

Developers

For developers who want to build, deploy, and manage applications on the cloud, this program provides practical training in modern tools like Azure, AWS, and DevOps practices, enabling you to create scalable and secure cloud solutions.

System & Network Administrators

If your goal is to upgrade your existing infrastructure, security, or database skills to work with cloud environments, this program equips you with the knowledge and hands-on expertise to manage cloud networks and resources confidently.

Fresh Graduates & Career Switchers

If you are new to tech or looking to change careers, this program offers a clear, structured path to enter the fast-growing cloud and data industry. You’ll gain practical experience, build a strong portfolio, earn recognized certifications, and position yourself for high-paying roles.

Tools Covered

Key Outcomes of This Program

8 In-Demand Certifications

Get certified in AWS, Azure, Microsoft Fabric, and Power BI with globally recognized credentials that boost your career profile.

Hands-On Experience

Practice with real tools like Python, SQL, AWS, Azure, Fabric, and Power BI through guided labs and exercises.

Real-World Projects

Work on industry-level projects in cloud data engineering, analytics, and BI to build a strong portfolio that impresses recruiters.

Job-Ready Skills

Gain the skills, confidence, and practical knowledge to step into roles like Data Engineer, Cloud Data Architect, or Analytics Specialist.

Career Support & Extras

Go beyond technical learning with personalized resume reviews, LinkedIn profile optimization, and mock interviews so you can confidently showcase your skills and secure offers.

Expert Mentorship & Lifetime Access

Get 24/7 support from certified cloud experts, plus lifetime access to course content and updates so you never fall behind.

100+ Labs

Practice Labs

200+ Videos

Video Course

15 Projects

Projects Course

500+ QA's

Q&A Exams

Course Break-Down

Lessons:
  • Lesson 1: Concepts of Data Engineering
  • Lesson 2: Data Types & Properties
  • Lesson 3: Data Warehouse, Data Lake, Lakehouse
  • Lesson 4: Data Mesh, ETL Pipeline, Data Sampling, Data Skew
  • Lesson 5: APIs & Data Fundamentals in Azure
Labs:
  • Lab 1: SQL Review & Practice
  • Lab 2: Python Basics Setup (Jupyter/Colab)
  • Lab 3: Git Fundamentals
Lessons:
  • Lesson 1: Python Basics, Data Structures & Functions
  • Lesson 2: Key ML Packages (NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn)
  • Lesson 3: Exploratory Data Analysis & Feature Engineering
  • Lesson 4: Supervised Learning (Regression, Classification)
  • Lesson 5: Unsupervised Learning & Clustering
  • Lesson 6: Ensemble Learning & Advanced ML Algorithms
  • Lesson 7: Neural Networks, CNN, RNN, LSTM
  • Lesson 8: Deep Learning & Time Series Analysis
Labs:
  • Lab 1: Python Data Structures (Lists, Tuples, Dictionaries)
  • Lab 2: Control Statements & Functions
  • Lab 3: Central Tendency (Mean, Median, Mode)
  • Lab 4: Data Visualization with Matplotlib & Seaborn
  • Lab 5: Build ML Models (Linear, Logistic, SVM, Decision Trees, XGBoost)
  • Lab 6: Model Evaluation Metrics
  • Lab 7: Feature Engineering & Dimensionality Reduction
  • Lab 8: Hyperparameter Tuning & Ensemble Learning
  • Lab 9: Clustering & Association Rule Mining
  • Lab 10: ML with PySpark
Lessons:
  • Lesson 1: Introduction to Cloud
  • Lesson 2: Characteristics & Benefits of Cloud
  • Lesson 3: Capex vs Opex
  • Lesson 4: Cloud Service Models (IaaS, PaaS, SaaS)
  • Lesson 5: Shared Responsibility Model
  • Lesson 6: Cloud Deployment Models (Public, Private, Hybrid)
  • Lesson 7: Choosing a Cloud Platform (AWS, Azure, GCP, OCI)
  • Lesson 8: Multi-Cloud Strategy
Lessons:
  • Lesson 1: AWS Overview & Global Infrastructure
  • Lesson 2: IAM: Users, Groups, Policies, Roles
  • Lesson 3: Compute Services (EC2, Lambda, ECS, EKS, Fargate)
  • Lesson 4: Storage & Networking (S3, EBS, VPC, Subnet, Gateway, LB)
  • Lesson 5: Database Services (RDS, DynamoDB, ElastiCache)
  • Lesson 6: Automation & Monitoring (CloudFormation, CloudWatch, CloudTrail)
  • Lesson 7: Application & DevOps Services (SNS, SES, SQS, CodeCommit, CodeBuild)
  • Lesson 8: AWS Architecture & Access Methods
Labs:
  • Lab 1: Create AWS Free Tier Account
  • Lab 2: Set Up CloudWatch Billing Alerts
  • Lab 3: Manage AWS Costs & Budgets
  • Lab 4: Troubleshoot Billing Issues
  • Lab 5: Connect a Linux Machine on AWS
  • Lab 6: Create & Connect Windows Machine
  • Lab 7: Install & Configure AWS CLI
  • Lab 8: Create Ubuntu EC2 Instance
  • Lab 9: Create IAM User with Administrator Access
Lessons:
  • Lesson 1: Azure Account & Subscription
  • Lesson 2: Azure Services Overview
  • Lesson 3: IAM & Azure Active Directory
  • Lesson 4: Compute Services (VMs, App Service, Functions, Logic App)
  • Lesson 5: Containers & Kubernetes (ACR, ACI, AKS)
  • Lesson 6: Networking & Storage Services
  • Lesson 7: Data Services (SQL, Synapse, Data Factory, Data Lake)
  • Lesson 8: Data Protection & Backup
  • Lesson 9: Monitoring & Log Analytics
Labs:
  • Lab 1: Register for an Azure Free Trial Account
  • Lab 2: Create Budget & Billing Alert
  • Lab 3: Create Windows VM (Quick Start)
  • Lab 4: Troubleshoot Connection to VM
  • Lab 5: Create Ubuntu VM on Azure
  • Lab 6: Deploy Docker Container on ACI
Lessons:
  • Lesson 1: What is Microsoft Fabric? (Components & Benefits)
  • Lesson 2: OneLake & Lakehouse in Microsoft Fabric
  • Lesson 3: Ingesting Data into Fabric Lakehouse
  • Lesson 4: Licensing, Concepts & Terminology
  • Lesson 5: CI/CD Workflow Options & Git Integration
  • Lesson 6: Deployment Pipelines in Fabric
Labs:
  • Lab 1: Create Fabric Free Trial Account
  • Lab 2: Workspace Management in Fabric
  • Lab 3: Create Lakehouse & Ingest Data
  • Lab 4: Build Deployment Pipeline
Lessons:
  • Lesson 1: Cloud Concepts & Architecture
  • Lesson 2: Compute & Networking
  • Lesson 3: Azure Storage & Databases
  • Lesson 4: Identity, Access & Security
  • Lesson 5: Cost Management, Governance & Compliance
  • Lesson 6: Deployment & Monitoring Tools
Labs:
  • Lab 1: Create Virtual Machine (Linux)
  • Lab 2: Create a Web App in Azure
  • Lab 3: Implement Container Instance
  • Lab 4: Create RG, VNet, Subnet & VM
  • Lab 5: Deploy Blob Storage & SQL Database
  • Lab 6: Manage Access with RBAC
  • Lab 7: Create & Deploy Azure Functions
  • Lab 8: Implement Azure Key Vault
  • Lab 9: Secure Network Traffic & Apply Policies
  • Lab 10: Use Azure Pricing & TCO Calculator
Lessons:
  • Lesson 1: Introduction to Data Fundamentals
  • Lesson 2: Relational Databases in Azure
  • Lesson 3: Non-Relational Databases in Azure
  • Lesson 4: Data Analytics Concepts & Use Cases
Labs:
  • Lab 1: Explore Azure SQL Database
  • Lab 2: Explore Azure Storage & Cosmos DB
  • Lab 3: Explore Data Analytics in Microsoft Fabric
  • Lab 4: Explore Azure Stream Analytics & Real-Time Analytics
  • Lab 5: Visualize Data with Power BI
  • Lab 6: Explore Azure Synapse Data Explorer
Lessons:
  • Lesson 1: Introduction to Analytics in Fabric
  • Lesson 2: Data Engineering with Apache Spark Pools
  • Lesson 3: Azure Databricks Fundamentals
  • Lesson 4: Advanced Databricks & PySpark APIs
  • Lesson 5: Data Migration & Lakehouse in Fabric
  • Lesson 6: Data Warehousing with Fabric
  • Lesson 7: Manage Fabric Environments & Pipelines
Labs:
  • Lab 1: Explore Synapse Analytics & Serverless SQL
  • Lab 2: Transform Data Using Spark & Delta Lake
  • Lab 3: Automate Databricks with ADF
  • Lab 4: Create & Ingest Data into Lakehouse
  • Lab 5: Build Dataflows & Pipelines in Fabric
  • Lab 6: Secure & Monitor Fabric Workspaces
Lessons:
  • Lesson 1: Prepare Data in Power BI Desktop
  • Lesson 2: Model Data & Create Relationships
  • Lesson 3: DAX Calculations (Basic & Advanced)
  • Lesson 4: Build Visuals, Reports & Dashboards
  • Lesson 5: Apply Row-Level Security & Governance
Labs:
  • Lab 1: Prepare & Load Data in Power BI Desktop
  • Lab 2: Create Data Model & Relationships
  • Lab 3: Build DAX Measures & Calculations
  • Lab 4: Design Reports & Dashboards
  • Lab 5: Enforce Row-Level Security in Power BI
Lessons:
  • Lesson 1: End-to-End Analytics with Microsoft Fabric
  • Lesson 2: Data Warehousing in Fabric
  • Lesson 3: Real-Time Intelligence in Fabric
  • Lesson 4: Scalable Semantic Models & DAX in Power BI
  • Lesson 5: Deployment & Governance in Fabric
Labs:
  • Lab 1: Query Data Warehouse in Fabric
  • Lab 2: Create DAX Calculations in Power BI
  • Lab 3: Design Semantic Models & Reusable Assets
  • Lab 4: Ingest & Analyze Real-Time Data with Eventstream
  • Lab 5: Implement Deployment Pipelines in Fabric
  • Lab 6: Monitor & Secure Fabric Analytics Environment

Project works

Resize Profile Picture Automatically on Social Media (AWS Lambda & S3)

Imagine you upload a photo on social media, and it instantly creates a smaller version for your profile. This project uses AWS tools to make that happen automatically without anyone doing it manually.

Build an ETL Pipeline for Data Transfer (AWS Glue & Redshift)

This project is about moving data from one place to another (like from files to a database) in a smart way. It changes data formats (CSV, JSON, etc.) into a faster format (Parquet) and loads it into Amazon Redshift for quick analysis.

Real-Time Data Analysis with Amazon Athena

Here, you learn how to ask questions (queries) to your data stored in Amazon S3 and get instant answers. It also makes sure the data stays correct and safe while people are using it.

Run Big Data Jobs on Amazon EMR

This project shows how to set up Amazon EMR (a big data system) to handle a lot of information at once. It’s like creating a supercomputer in the cloud that can quickly process data for you.

Migrate MySQL Database to Amazon RDS

Think of it like shifting your school books from an old bag to a new, more modern one. This project moves databases from MySQL to Amazon RDS with the help of AWS DMS, so data is safer and easier to manage.

Tokyo Olympics Insights with Power BI

This project uses Olympic data (like medals and sports) to make cool charts and dashboards in Power BI. For example, you can see which country won the most medals or how men and women performed in different sports.

Formula One (F1) Race Insights

Here, you collect and clean Formula One racing data to find patterns. For example, which driver is fastest, which car performs better, or how tracks affect the race outcome.

Transform Data with Azure Data Factory

This project is like building a factory that takes raw data, cleans it, and stores it in a neat way. You’ll use Azure Data Factory to move and transform data into a storage system for future use.

COVID-19 Data Insights with Azure & Power BI

Using COVID-19 data, this project builds reports and dashboards showing cases, deaths, and hospitalizations. With tools like Azure and Power BI, it helps people understand how the virus spread and how it affected different countries.

Skills You Need to Get Started

No Prior Experience Required

We start from the basics.

Step-by-Step Learning

Python → Data Engineering → AI/ML → Cloud (AWS & Azure).

Hands-On Tools

AWS Glue, Data Lakes, Warehouses, Microsoft Fabric, Power BI, ADF, Redshift, Databricks.

Real projects + certifications

Build a portfolio that shows your skills to recruiters.

End goal

Become job-ready in data & cloud with confidence.

Why You Should Enroll

8 Industry Certifications

Boost your profile with globally recognized AWS & Azure certifications that open doors to high-paying data and cloud jobs.

Hands-On Experience

Work on real-world projects using tools like Power BI, Microsoft Fabric, Redshift, Databricks, and ADF to gain practical skills.

Career Support

Get guidance with resume building, interview preparation, and job strategies to confidently land your dream role.

Higher Earning Potential

With in-demand data & cloud skills, position yourself for stable, future-proof, and high-paying career opportunities.

Flexible Learning

Learn at your own pace with lifetime access to course materials, so you never feel rushed.

Certification Preparation

Be fully prepared for 8 globally recognized Azure & AWS certifications.

Job-Ready Skills

Build practical expertise aligned with real industry requirements.

Why Choose Us for the Data on Cloud Job-Oriented Program with 8 Certifications?

Practical, Hands-On Learning

Go beyond theory with 100+ labs, real-world projects, and guided exercises designed to build skills you can apply from day one.

24/7 Query Support

Get your doubts resolved quickly through WhatsApp, a ticketing system, or live Q&A sessions. You’ll never be left stuck or learning alone.

Weekly Live Interactive Classes

Stay engaged with expert-led sessions where you can ask questions, collaborate with peers, and gain clarity on complex topics.

Career-Focused Preparation

From resume building and mock interviews to job placement strategies, we help you stand out and land the right opportunity.

Expert Mentorship

Learn directly from Atul, a veteran with 20+ years in IT (a century in cloud years), who has crafted a proven roadmap to take learners from beginner to job-ready.

Structured Roadmap to Success

A guided learning path covering fundamentals → hands-on practice → real-world projects → certifications → career support.

Post-Placement Guidance

Our support doesn’t end when you get hired. Continue receiving mentorship and guidance to excel in your new role with confidence.

What Our Trainees Say

Trusted by thousands of satisfied trainees across multiple platforms

Insights from Our Achievers..

FAQs – Frequently Asked Questions

Who is the Instructor?

Industry-certified experts in Azure, AWS, Google Cloud, DevOps & AI/ML — all with real-world experience and trained by K21Academy for online delivery.

Yes. With 100+ labs and real-world projects, you’ll build practical skills that count as experience on your resume.

The longer you wait, the further you fall behind. Learn at your own pace with lifetime access + weekly live sessions.

Think of it as an investment in your future — higher-paying jobs, promotions, certifications, and career security.

No issue. Many learners with gaps transitioned successfully using our step-by-step roadmap.

We provide 24×7 WhatsApp support, a ticketing system, and weekly Q&A sessions. You’ll never feel stuck.

Check real success stories here: k21academy.com/reviews. Learners worldwide have landed high-paying jobs.

Resume reviews, mock interviews, and job strategies are part of the program. Start applying as soon as you feel ready.

That’s why we start from the basics and follow a proven roadmap. Even complete beginners succeed here.

Yes. With 8 certifications, hands-on projects, and a strong portfolio, you’ll be job-ready for top cloud & data roles.

Yes. 100+ guided labs and real projects ensure you practice, not just study theory.

Thousands have trusted us. Our roadmap, mentors, and hands-on approach are proven. See reviews: k21academy.com/reviews  

Yes. Resume building, interview prep, and job support — plus on-job guidance even after placement. 

6 Months Money Back Guarantee

When you join the K21Academy, you are fully protected by our 100% Money back guarantee.

We strive to provide the best training programs, but if you don’t get the desired results even after following every step of our learning style, you can claim your money back! 100% money-back guarantee covers the price of online training.

You have 6 Months from the date of the original purchase, to claim a refund. All you will be required to do is, show us the proof that you took action and attended sessions, completing the hands-on labs, Projects & applying to at least 50 jobs & get CV Reviewed (share proof) & you feel that the program is not worth the money you invested, you will receive a full refund.

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My 24+ Years of Experience with over 45,000+ trainees

I started my IT career in 2000 as an Oracle DBA/Apps DBA. The first few years were tough (<$100/month), with very little growth.

In 2004, I moved to the UK. After working really hard, I landed a job that paid me £2700 per month.

In February 2005, I saw a job that was £450 per day, which was nearly 4 times of my then salary.

So I looked at training from Oracle for 5 days. In November, I successfully transitioned to Oracle Security & IAM, and my career took off.

Around 2012–13, Cloud, DevOps & Cloud Automation were gaining popularity & there were many job opportunities in these fields.

So, I decided to make a change in my career path, and I transitioned from working on On-premises (Security, Infrastructure & Databases) to focusing on Cloud & DevOps.
Learning Cloud & DevOps gave me the opportunity to work with some of the world’s largest and most prestigious clients.

I then used the same roadmap with 45,000+ individuals (like you) to help them get their dream jobs.

If they can do it, you can do it too!