Service Solution
About Project
AI for Industrial IoT Platform
1. What You Will Learn
- In-Depth Understanding: Delve into AI technologies, intelligent systems, machine learning, and neural networks for effective industrial applications.
- Practical Application Skills: Learn to leverage AI to solve problems, optimize factory and production processes, reduce costs, and boost profits.
- Development Capabilities: Build a foundation in basic AI programming to independently develop and enhance AI projects within your organization.
- Expert Network: Connect and exchange knowledge with AI professionals and executives, fostering business opportunities and collaboration.
- Real-World Case Studies: Learn from successful AI implementations in industries like AI-powered quality inspection, predictive maintenance, and intelligent control systems.
2. Instructor
Piyorot Khongchuay, a leading AI industry expert with hands-on experience implementing AI in factories and production processes, ready to share practical knowledge and techniques.
3. Course Content
Overview of Artificial Intelligence (AI) and Its Current Significance: Understand the fundamentals of AI, different types of AI, and the crucial role of AI in the modern world, particularly in the industrial sector.
Intelligent Systems: Learn about AI systems capable of learning and adapting, along with algorithms used to build them, such as Supervised and Unsupervised Learning.
Introduction to Neural Networks and Fuzzy Logic: Explore neural networks, the foundation of AI for learning and processing data, and fuzzy logic for handling data uncertainties.
AI Applications in Industry: Examine examples of AI implementation in various sectors, including demand forecasting, product defect detection, production optimization, and supply chain management.
K-Means Clustering: Learn about the K-Means Clustering algorithm, a widely used method for grouping data in AI, and practice its application in Python.
Neural Networks: Dive into the concepts and structure of neural networks, the operation of Multilayer Perceptron (MLP), and Deep Learning, including their differences from traditional neural networks. Practice building neural networks with Python.
Examples of AI Applications in Industry:
Chemical Substance Classification with Electronic Sensors: Utilizing AI to analyze sensor data for chemical classification.
Facial Recognition: Employing AI for security and identity verification through facial recognition.
Automatic Shade Detection System: Using AI to detect and control shades in production processes.
Automatic Tool Change: Implementing AI to control and change tools in automated manufacturing.
Sugarcane Management: Leveraging AI to manage and optimize sugarcane production.
Hardware for AI: Understand the necessary hardware for AI implementation in industry, such as AI servers, and considerations for hardware selection.
Software for AI: Learn about software and tools used to develop and deploy AI in industry.
4. Schedule, Location, and Cost
- Duration: 2 days (Session 1: August 30, 2018; Session 2: March 15, 2019)
- Location: Thai-German Institute
Cost: 3,000 baht/person