IoT Data Analytics with AWS Certified Course

Course Description:

The IoT Data Analytics with AWS course empowers learners to transform raw IoT sensor data into actionable insights using the powerful cloud services of Amazon Web Services. This program covers end-to-end IoT data workflows—from device connectivity and secure data ingestion to real-time analytics, machine learning integration, and data visualization. Students will work with AWS IoT Core, AWS Lambda, Amazon Kinesis, and AWS Analytics tools to build scalable, intelligent IoT solutions widely used in smart industries, connected healthcare, transportation systems, and home automation. By the end of the course, learners will be confident in deploying production-ready IoT analytics applications in the cloud, driving innovation and data-driven decisions.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

Career Opportunities After IoT Data Analytics with AWS Certified Course:

• IoT Data Analyst
• Cloud IoT Engineer
• AWS Cloud Developer
• IoT Solutions Architect
• Data Engineer (IoT Focus)
• Machine Learning Engineer for IoT Applications
• Industrial IoT (IIoT) Specialist
• Smart Infrastructure Engineer
• DevOps Engineer – IoT Systems
• IoT Product Consultant / Technical Analyst

Essential Skills you will Develop IoT Data Analytics with AWS Certified Course:

• IoT device data acquisition and communication
• Secure data ingestion using AWS IoT Core
• Real-time data processing with AWS Lambda & Kinesis
• Data storage and management in AWS cloud services
• Data visualization and dashboard creation
• Applying analytics and ML for IoT data insights
• Cloud security practices for IoT environments
• Building scalable and distributed IoT architectures
• Integration of IoT systems with enterprise applications
• Deployment, monitoring, and optimization of IoT solutions

Tools Covered:

• AWS IoT Core
• AWS Lambda
• Amazon Kinesis Data Streams & Firehose
• Amazon S3 (Storage & Data Lake)
• AWS DynamoDB / Amazon RDS
• AWS Glue (ETL & Data Processing)
• Amazon QuickSight (Data Visualization & Analytics)
• AWS IoT Analytics & AWS IoT Device Defender
• Amazon SageMaker (Machine Learning for IoT)
• MQTT Protocol & IoT Device SDKs

Syllabus:

Module 1: Introduction to IoT & Cloud Computing IoT fundamentals, architectures & use cases Cloud concepts and AWS overview IoT communication protocols (MQTT, HTTP, CoAP).

Module 2: AWS IoT Core Setup & Device Connectivity Creating AWS IoT Things & device certificates Secure communication (X.509, TLS) Publishing & subscribing IoT data.

Module 3: IoT Data Ingestion & Messaging AWS IoT Core rules engine Amazon Kinesis Data Streams & Firehose Data routing to S3, DynamoDB & Analytics services. 

 Module 4: Serverless Computing with AWS Lambda Event-driven data processing Writing Lambda functions for IoT analytics Real-time alerting & automation.

Module 5: IoT Data Storage & Databases Amazon S3 for Data Lake DynamoDB & RDS for structured storage AWS Glue for ETL tasks.

Module 6: IoT Data Analytics & Visualization AWS IoT Analytics pipeline design Visualization using Amazon QuickSight KPI dashboards for IoT operations.

Module 7: Machine Learning for IoT Data Predictive analytics using Amazon SageMaker Anomaly detection & maintenance prediction models ML deployment & result monitoring.

Module 8: IoT Security & Identity Management Device authentication & policies AWS IoT Device Defender & monitoring Data encryption & secure communication.

Module 9: Scalable IoT Architecture & Integration Industrial & enterprise IoT data flows Edge computing with AWS Greengrass CI/CD & DevOps for IoT.

Module 10: Capstone Project & Deployment Real-time IoT analytics application development Cloud deployment & dashboard presentation Project documentation & review.

Industry Projects:

• Smart Home Monitoring System
• Industrial Machine Health Analytics
• Smart Agriculture – Soil & Weather Insights
• Connected Fleet Management System
• Smart Energy Metering & Optimization

Who is this program for?

• Students interested in IoT
• Cloud & Data Analytics learners
• Working IT professionals
• Electronics & Embedded engineers
• Software developers
• Data analysts
• Tech entrepreneurs
• Anyone interested in smart systems

How To Apply:

Mobile: 9100348679                   

Email: coursedivine@gmail.com