Attribute

Detail

Format

Online (e-LMS)

Level

Advanced

Duration

3 Weeks

Certification

e-Certification + e-Marksheet

Tools

TensorFlow, TensorFlow Lite, PyTorch, Scikit-Learn, Raspberry Pi, Arduino

About the Ai For Iot Course

The AI for IoT: Intelligent Integration of AI with the Internet of Things is a 3‑week intensive program that blends artificial intelligence with IoT.

Through lectures, labs, and real‑world case studies in healthcare and urban planning, participants will design, deploy, and optimise AI‑driven IoT solutions and leave with a certificate of completion.

Program Highlights

• Comprehensive coverage of AI for IoT from fundamentals to advanced applications

• Hands-on projects and real-world case studies in Artificial Intelligence

• Expert-curated curriculum aligned with current industry standards

• Access to recorded lectures and e-LMS platform for flexible, self-paced learning

• e-Certification and e-Marksheet upon successful completion

• Dedicated mentor support and interactive doubt-clearing sessions

• Practical experience with tools: TensorFlow, TensorFlow Lite, PyTorch, Scikit-Learn

• Career-oriented training for academic and professional growth in Artificial Intelligence

Course Curriculum

Module 1: Introduction to AI and IoT

Explore core concepts of IoT ecosystems and AI techniques
Analyse the synergy between AI and IoT across smart cities, wearables and autonomous vehicles
Set up hardware (Raspberry Pi, Arduino) and software tools (TensorFlow, MQTT)

Module 2: IoT Data Processing and Analytics

Collect and stream sensor data to cloud and edge platforms
Preprocess data – cleaning, normalising, encoding for AI models
Implement edge‑AI on Raspberry Pi and cloud‑AI on AWS/Google/Azure IoT

Module 3: Applying AI to IoT Data

Build supervised and unsupervised models for predictive maintenance and anomaly detection
Deploy deep‑learning models (RNN/LSTM, CNN) for time‑series forecasting and computer‑vision IoT applications
Create reinforcement‑learning agents for smart‑grid optimisation

Module 4: AI Deployment in IoT Systems

Optimise and deploy models on edge devices using TensorFlow Lite
Integrate AI with cloud IoT platforms (Azure IoT Hub, AWS IoT Core) for scalable solutions
Apply security best practices for cloud‑AI‑IoT deployments

Module 5: IoT Security and Ethical Considerations in AI

Identify IoT threat vectors and use AI for intrusion detection
Address data‑privacy, bias, and transparent AI model design
Implement ethical guidelines for responsible AI‑IoT solutions

Tools, Techniques, or Platforms Covered

TensorFlow
TensorFlow Lite
PyTorch
Scikit-Learn
Raspberry Pi
Arduino
MQTT
CoAP
AWS IoT
Azure IoT Hub

Real-World Applications

Apply AI for IoT skills directly to academic research, thesis work, and publications
Build a professional portfolio showcasing practical Artificial Intelligence competencies
Solve industry-relevant problems using AI for IoT methodologies and tools
Contribute to open-source projects and collaborative research in Artificial Intelligence
Prepare for competitive examinations, interviews, and professional certifications in Artificial Intelligence

Who Should Attend & Prerequisites

Industry‑recognised e‑Certification + e‑Marksheet from NSTC
Hands‑on training with practical projects and industrial datasets
Dedicated expert mentorship and doubt resolution

Prerequisites:

Frequently Asked Questions

1. What is the format of this AI for IoT course?

This is an Online (e-LMS) course delivered via our e-LMS platform. You will have access to pre-recorded video lectures, reading materials, assignments, quizzes, and hands-on projects that you can complete at your own pace.

2. Will I receive a certificate after completing this course?

Yes! Upon successful completion of all modules, assignments, and assessments, you will receive an e-Certification along with an e-Marksheet from NanoSchool (NSTC) that you can showcase on your CV and LinkedIn profile.

3. What are the prerequisites for this course?

Learners should have a foundational understanding of Artificial Intelligence concepts. Familiarity with basic tools and programming is recommended.

4. How long will I have access to the course materials?

You will have access to all course materials for the duration of 3 Weeks. The self-paced format allows you to learn according to your own schedule through our online learning management system.

5. Is mentor support available during the course?

Yes, dedicated mentor support is available throughout the course. You can reach out for doubt-clearing sessions, project guidance, and career advice related to Artificial Intelligence. Our mentors are industry experts and experienced professionals.

Enroll in AI for IoT today and take the next step in your professional journey. With expert-curated content, practical projects, and industry-recognized certification, this course is your gateway to mastering Artificial Intelligence skills that matter.

Brand	NSTC
Format	Online (e-LMS)
Duration	3 Weeks
Level	Advanced
Domain	Artificial Intelligence
Hands-On	Yes – Practical projects with industrial datasets
Tools Used	TensorFlow, TensorFlow Lite, PyTorch, Scikit-Learn, Raspberry Pi, Arduino, MQTT, CoAP, AWS IoT, Azure IoT Hub, Google Cloud IoT

Achieve Excellence & Enter the Hall of Fame!

Elevate your research to the next level! Get your groundbreaking work considered for publication in prestigious Open Access Journal (worth USD 1,000) and Opportunity to join esteemed Centre of Excellence. Network with industry leaders, access ongoing learning opportunities, and potentially earn a place in our coveted

Hall of Fame.

Achieve excellence and solidify your reputation among the elite!