Industrial IoT and Al Systems Engineer
Course title: Edge Computing : Master the Next Frontier of Computing
Target group: Junior (Fresh Employee)
Level: Awareness
Edge Computing : Master the Next Frontier of Computing
Provider
Udemy
Description
Edge Computing: From Buzzword to Breakthrough
Unleash the power of data processing where it happens – at the edge of the network. In this comprehensive course, you’ll unlock the secrets of Edge Computing, the transformative technology powering faster, smarter, and more efficient operations across industries.
No prior knowledge needed! Whether you’re a tech leader, data scientist, IT pro, or simply curious about this future-forward trend, this course will equip you with everything you need to:
- Master the fundamentals:Â Understand what Edge Computing is, its key benefits, and how it redefines data processing.
- Discover real-world potential:Â Explore diverse use cases in banking, manufacturing, retail, healthcare, and beyond.
- Tame the challenges:Â Learn best practices for overcoming security, data management, and implementation hurdles.
- Get hands-on:Â Put your knowledge into action with practical labs and industry-standard tools.
- Shape the future:Â Position yourself as an Edge Computing pioneer, ready to capitalize on this game-changing technology.
Target
- Tech Enthusiasts: Curious about the next frontier of computing and its impact on various industries?
- Tech Professionals: Looking to expand your skillset and stay ahead of the curve in the ever-evolving tech landscape?
- Data Science Leaders: Seeking new ways to optimize data processing and unlock faster, real-time insights?
- IT Professionals: Eager to understand how Edge Computing can revolutionize network infrastructure and security?
- Business Leaders: Visionaries driven to identify and implement transformative technologies for a competitive edge?
Sector
- Banking
- Manufacturing
- Retail
- Healthcare
- Other industries
Area
- Edge Computing
- Data Processing
- Industry-specific use cases
Learning outcomes
- Define Edge Computing & explain its core advantages like reduced latency and enhanced security.
- Identify potential use cases for Edge Computing across diverse industries like finance, manufacturing, and healthcare.
- Analyze the impact of Multi-access Edge Computing (MEC) and position yourself for the future of distributed processing.
- Position yourself as a thought leader in the Edge Computing space, gaining valuable skills for career advancement.
- Stay updated on emerging trends in Edge Computing, such as artificial intelligence and machine learning at the edge.
- Implement security best practices for protecting data and devices in an Edge Computing environment.
Learning content
- Introduction to Edge Computing
- Edge Computing: Challenges, Strategies and Best Practices
- Applications of Edge Computing
- Tools, Implementation & Multi-Access Edge Computing
- Edge Computing: Technologies, Vendors and Edge AI
- Project #1: Temperature Monitoring (Edge Computing in Healthcare Industry)
- Project #2: Vehicle Maintenance System (Edge Computing in Automobile Industry)
- Project #3: Production Line Monitoring System (Edge Computing in Manufacturing)
- #4: Inventory Management System (Edge Computing in Retail Industry)
Approach/method
Online
Duration
2 hours on-demand video
Assessment
No
Certification
Yes
Cost
€19.99
Provider contacts
Date
Always available
Location
Online
Website
Course title: Machine Learning and Advanced AI Techniques
Target group: Mid Level Employee
Level: Foundations
Machine Learning and Advanced AI Techniques
Provider
Alison
Description
Have you ever wondered how Amazon or Netflix knows exactly which product or show to recommend to you? The answer lies in the adoption of machine learning (ML) in business. In this course, we’ll explore, through real-world examples, the various applications of machine learning and deep learning across different types of businesses.
We’ll begin with an introduction to machine learning, where you’ll explore the different types of machine learning, the uses of labelled and unlabelled datasets, and the key algorithms that power machine learning models. Using examples from healthcare, finance, marketing, and more, you’ll learn the importance of selecting the right algorithm based on the specific problem and dataset characteristics. Next, we’ll introduce you to deep learning, where you’ll explore the architecture of neural networks and learn how neurons, layers, and activation functions work together to create powerful models capable of solving complex tasks. You’ll learn about the specific uses of Convolutional neural networks (CNN) and Recurrent neural networks (RNN), the challenges they offer and how to address them. You’ll explore methods to train models to prevent overfitting and optimising techniques for enhancing model performance. The prerequisite for taking this course is completing our previous course in this series, ‘ Introduction to AI in Business’. Enroll now and embark on a learning journey to unlock the transformative potential of AI.
Target
- Professionals and students interested in AI
- Machine learning, and deep learning
- Individuals seeking to apply AI in business contexts
Sector
- Business
- Healthcare
- Finance
- Marketing
- Technology
Area
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Data Science
Learning outcomes
- Define the foundational concepts and frameworks of Machine learning (ML)
- Illustrate how ML differs from traditional programming methodologies
- Recognise the different types of machine learning and their applications
- Analyse the applications, advantages and limitations of supervised and unsupervised ML
- Identify the key algorithms in machine learning, their functionalities and implementations
- Discuss the application of deep learning for optimising operations across various business domains
- Explain how neural networks are used to build intricate AI systems
- Create powerful models capable of solving complex tasks
- Describe how convolutional neural networks are used for image processing and computer vision applications
- Distinguish the uses of convolutional neural networks (CNN) and recurrent neural networks (RNN)
- Outline methods for training and optimising various types of AI models
Learning content
- Machine Learning and Use of Neural Networks
This module introduces different types of machine learning, their key algorithms and their applications across various industries, including healthcare, finance, marketing, and autonomous systems. You’ll learn the key concepts of deep learning, neural network architectures, and the techniques used to train and optimise AI models - Course assessment
Approach/method
Online
Duration
1.5-3 Hours on average
Assessment
Yes
Certification
Yes
Cost
Free
Provider contacts
Date
Always available
Location
Online
Website
Course title: Cybersecurity for IoT (Internet of Things)
Target group: Expert
Level: Extended Know-How
Cybersecurity for IoT (Internet of Things)
Provider
Udemy
Description
professionals, security specialists, and IoT enthusiasts. Over seven modules, you’ll gain in-depth knowledge and practical skills to secure IoT ecosystems from evolving cyber threats.
Starting with the fundamentals of IoT and cybersecurity, you’ll quickly progress to advanced topics such as securing IoT devices, networks, and cloud backends. Through a combination of lectures, hands-on labs, and real-world case studies, you’ll learn to implement robust security measures, conduct thorough security testing, and respond effectively to IoT security incidents.
Key topics covered include:
- IoT device security and firmware management
- Secure network protocols and data encryption
- Cloud and backend security for IoT platforms
- Vulnerability assessment and penetration testing for IoT
- Implementation of IoT security best practices and standards
- Incident response and forensics in IoT environments
By the end of this course, you’ll be equipped with the knowledge and skills to design, implement, and maintain secure IoT systems. You’ll understand how to apply industry-standard frameworks like OWASP IoT Top 10 and NIST guidelines, and be prepared to tackle real-world IoT security challenges. Whether you’re looking to enhance your organization’s IoT security, develop secure IoT products, or advance your career in this rapidly growing field, this course provides the comprehensive training you need to succeed in IoT cybersecurity
Target
- IT professionals and network administrators who want to expand their expertise into IoT security
- Cybersecurity specialists looking to focus on the unique challenges of securing Internet of Things ecosystems
- Software developers and hardware engineers working on IoT products who need to integrate security best practices
- Information security managers and CISOs seeking to understand and address IoT-specific security risks in their organizations
- Computer science and IT students with a basic understanding of networking and cybersecurity, interested in specializing in IoT security
- IoT enthusiasts and makers with some technical background who want to ensure their projects are secure
- Business leaders and decision-makers who need a technical understanding of IoT security for their organization’s IoT implementations
Sector
- IoT security and cybersecurity
Area
- IoT ecosystems (devices, networks, cloud platforms)
Learning outcomes
- IT professionals and cybersecurity specialists looking to expand their knowledge into the growing field of IoT security
- Network administrators and system engineers responsible for implementing and maintaining IoT systems in their organizations
- Software developers and hardware engineers working on IoT products who want to integrate security best practices into their development process
- Information security managers and CISOs seeking to understand the unique challenges and solutions in securing IoT ecosystems
- Students and graduates in computer science, information technology, or cybersecurity fields interested in specializing in IoT security
- IoT enthusiasts and makers who want to ensure their projects and devices are secure from potential threats
- Business leaders and decision-makers who need to understand IoT security risks and mitigation strategies for their organizations
- Anyone with a basic understanding of networking and cybersecurity concepts who wants to dive deep into the world of IoT security
Learning content
- Securing IoT Devices
- IoT Network and Communication Security
- Cloud and Backend Security for IoT
- IoT Security Testing and Auditing
- IoT Security Best Practices and Standards
- IoT Security Incident Response and Forensics
Approach/method
Online
Duration
3 hours on-demand video
Assessment
No
Certification
Yes
Cost
€49.99
Provider contacts
Date
Always available
Location
Online
Website