Join FAVORIOT’s three-day training program and unlock the power of integrating Artificial Intelligence (AI) with Internet of Things (IoT) technology. Gain a solid understanding of AI fundamentals and its application within the IoT landscape. Develop proficiency in creating intelligent IoT applications using Raspberry Pi, Python programming, and the Favoriot IoT Platform.
Become an expert in harnessing the potential of AI and IoT together. Acquire the skills to design and build real-world IoT applications that leverage cutting-edge AI techniques. Expand your knowledge and stay at the forefront of this exciting intersection between AI and IoT.
Transform your understanding of AI and IoT with our comprehensive training. From grasping the fundamentals to mastering advanced techniques, you will embark on a journey that will empower you to create innovative IoT solutions. Gain hands-on experience and develop the expertise needed to thrive in the AI-driven IoT ecosystem.
Don’t miss this opportunity to become a trailblazer in the fusion of AI and IoT. Join us as we explore the limitless possibilities and practical applications of this transformative technology. Get ready to unlock new opportunities and propel your career forward in this rapidly evolving field.
- Integrate AI and IoT: familiarize participants with the fusion of technologies.
- Explore IoT ecosystem: understand architecture and components in depth.
- Master Raspberry Pi for IoT: gain expertise in its architecture and components.
- Connect and transmit: interface sensors with Raspberry Pi, transferring data to the Favoriot IoT Platform.
- Discover IoT data analytics: unlock insights using specialized techniques.
- Empower creativity: design and build intelligent IoT applications with AI, Raspberry Pi, Python, and the Favoriot IoT Platform.
5 Learning Outcomes:
- Grasp the fundamental concepts of AI and its integration with IoT technologies.
- Develop the skills to create IoT applications using Raspberry Pi, Python programming, and the Favoriot IoT Platform.
- Gain the ability to interface sensors with Raspberry Pi and collect data for use in IoT applications.
- Apply data analytics techniques tailored for IoT to extract meaningful insights from collected data.
- Utilize machine learning algorithms for effective analysis and interpretation of IoT data.
These outcomes will equip participants with the knowledge and practical skills to confidently navigate the integration of AI and IoT, enabling them to design and build intelligent IoT applications and make informed decisions based on data-driven insights.
Module 1: Introduction to IoT and Artificial Intelligence
- Introduction to IoT
- IoT Architecture and Ecosystem
- Introduction of AI
- Types of AI: supervised learning, unsupervised learning, and reinforcement learning
- Understanding the concepts of AI and its applications in IoT
Module 2: Raspberry Pi for AI
- Understanding Raspberry Pi architecture and components
- Setting up Raspberry Pi
- Configuring sensors and devices for IoT applications
- Introduction to Python Programming for IoT
- Hands-on exercise: Collecting and analysing data from IoT devices/Sensors using Python programming
Module 3: Favoriot IoT Platform, Data Acquisition and Analysis for IoT
- Introduction to data acquisition and analysis for IoT
- Favoriot Platform User profile and API Keys
- Favoriot Platform Hierarchy
- Setup platform to receive sensor data
- Hands-on exercise: Acquiring and analysing data using Raspberry Pi and Favoriot Platform
Module 4: Machine Learning Basics
- Overview of data analytics techniques for IoT
- What is Machine Learning?
- Types of Machine Learning: Supervised, Unsupervised, Reinforcement
- Machine Learning Algorithms
- Overview of AI and machine learning tools: TensorFlow, PyTorch, scikit-learn, and Keras
- Setting up a development environment with Python and Jupyter Notebook
- Introduction to basic machine learning concepts: data pre-processing, feature selection, and model selection
- Hands-on activity: Building a simple linear regression model using scikit-learn and Jupyter Notebook
Module 5: Neural Networks and Deep Learning
- Overview of deep learning and neural networks
- Understanding convolutional neural networks (CNNs) and recurrent neural networks (RNNs)
- Autoencoders and Generative Adversarial Networks (GANs)
- Hands-on activity: Building a simple CNN using Keras and Jupyter Notebook
Module 6: Machine Learning Analysis of IoT Data
- Preparing IoT data for Machine Learning Analysis
- Applying Machine Learning Algorithms to IoT data
- Visualising and Interpreting Machine Learning results
- Jupyter Notebook
- Raspberry Pi
- Sensors (DHT 22)
The training program is designed for individuals who are interested in integrating Artificial Intelligence (AI) with Internet of Things (IoT) technology. The target participants may include:
- AI and IoT Enthusiasts: Individuals who have a keen interest in both AI and IoT and want to explore the potential of combining these technologies. They may have a basic understanding of AI and IoT concepts and want to expand their knowledge and skills.
- IoT Developers: Professionals who are already working in the field of IoT development and want to enhance their expertise by integrating AI into their projects. They may have experience with IoT platforms, Raspberry Pi, and sensor interfacing.
- Data Scientists and Analysts: Individuals who work with data analysis and want to explore the application of AI techniques in the context of IoT. They may already possess knowledge of data analytics and want to learn how to apply machine learning algorithms to IoT data.
- Software Engineers and Programmers: Professionals with programming skills who are interested in building intelligent IoT applications. They may have experience with Python programming and want to learn how to leverage AI and IoT together using tools like Raspberry Pi and Favoriot IoT Platform.
- Technology Managers and Innovators: Individuals in managerial or leadership roles who want to gain a comprehensive understanding of AI and IoT integration. They may be responsible for guiding their organizations’ technology strategies and want to stay at the forefront of this rapidly evolving field.
It’s important to note that the above list is not exhaustive, and the training program may also attract participants from various other backgrounds who are interested in gaining knowledge and practical skills in the intersection of AI and IoT.
If you are interested in attending the training program or need more specific information about participants, it would be best to contact the organizers or training providers directly for enrolment details and participant profiles.