Aim
This course aims to equip students and early career professionals with essential knowledge and practical skills to design, deploy, and optimize AI-driven solutions within IoT infrastructures. Through hands-on applications and real-world case studies, participants will learn to implement advanced AI algorithms to enable IoT devices to perform automated decision-making, improve operational efficiency, and introduce new services.
Program Objectives
- Comprehensive Understanding: Master both foundational and advanced AI and IoT concepts.
- Develop Integration Skills: Learn to effectively integrate AI technologies with IoT systems.
- Enhance Practical Skills: Engage in hands-on labs and projects to apply AI and IoT principles in real-world scenarios.
- Problem Solving: Cultivate problem-solving skills for complex challenges in AI and IoT environments.
- Advance Professional Development: Prepare for roles with in-demand skills and industry insights.
- Expand Networking Opportunities: Foster professional connections through networking events and group projects.
- Research and Innovation: Participate in research opportunities, contributing new knowledge and insights.
- Certification and Recognition: Earn certificates validating expertise and recognizing outstanding contributions.
Program Structure
Module 1: Introduction to AI and IoT
- Section 1.1: Overview of AI (History, Evolution, and Applications)
- Section 1.2: Basics of IoT (Key Components and Architecture)
- Section 1.3: Convergence of AI and IoT (Opportunities, Challenges, and Industry Impact)
Module 2: Data Handling and Analytics
- Section 2.1: Data Collection in IoT (Sensors and Data Acquisition, Data Filtering)
- Section 2.2: AI for Data Analysis (Machine Learning, Real-Time Processing)
- Section 2.3: Data Storage and Management (Cloud vs. Edge Computing, Data Privacy)
Module 3: AI Technologies for IoT
- Section 3.1: Machine Learning Techniques (Supervised, Unsupervised, Reinforcement Learning)
- Section 3.2: Deep Learning and Neural Networks (Image and Speech Recognition, Predictive Maintenance)
- Section 3.3: Natural Language Processing (Voice Assistants, Chatbots in IoT)
Module 4: IoT Development Platforms and Tools
- Section 4.1: IoT Platforms Overview (Commercial, Open Source)
- Section 4.2: Integrating AI with IoT Platforms (APIs, Middleware, Developing Intelligent IoT Devices)
- Section 4.3: Case Studies (Smart Cities, Healthcare, Manufacturing Applications)
Module 5: Project and Industry Applications
- Section 5.1: Designing AI-IoT Solutions (Problem Identification, Solution Design)
- Section 5.2: Implementation Challenges (Scalability, Interoperability, Regulatory Concerns)
- Section 5.3: Project Presentation and Evaluation (Final Project Submission and Peer Review)
Participant’s Eligibility
- Students: B.Tech, M.Tech, and M.Sc students in Computer Science, IT, and Electronics.
- Professionals: Early career IT professionals looking to apply AI in real-world IoT scenarios.
Program Outcomes
- Mastery of AI and IoT Concepts: Deep understanding of fundamental and advanced AI-IoT integration.
- Practical Skills Development: Hands-on experience in implementing AI-driven IoT solutions.
- Problem-Solving Abilities: Enhanced skills to solve real-world challenges using AI and IoT frameworks.
- Industry Readiness: Up-to-date knowledge and skills tailored for the tech industry.
- Professional Networking: Build connections with industry professionals and peers.
- Research and Development Skills: Develop research capabilities in AI-IoT innovations.
- Certification and Recognition: Earn a certificate to validate expertise and boost career prospects.
Fee Structure
- Standard Fee: INR 4,998 | USD 78
- Discounted Fee: INR 2,499 | USD 39
Program Deliverables
- Access to e-LMS
- Real-Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self-Assessment
- Final Examination
- e-Certification
- e-Marksheet
Placement Assistance
- Corporate Networking Events
- Resume and Interview Preparation
- Corporate Guest Lectures
- Alumni Network
Future Career Prospects
- IoT Solution Architect: Design and manage comprehensive IoT systems.
- AI Systems Developer: Develop AI algorithms to enhance IoT solutions.
- Data Scientist for IoT: Analyze IoT data to generate actionable insights.
- Cybersecurity Analyst for IoT: Implement security measures for IoT infrastructures.
- IoT Project Manager: Lead and manage IoT project initiatives.
- Industrial IoT Engineer: Optimize industrial processes using IoT.
- Smart City Technology Coordinator: Oversee and enhance urban IoT applications.
- AI and IoT Research Analyst: Conduct research on advancements in AI for IoT.
- IoT Business Development Manager: Drive business growth through innovative IoT solutions.
- Consultant for AI and IoT Integration: Advise businesses on integrating AI into IoT frameworks.
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