Overview
The course is aimed to be a game changer for participants by taking them through the technical as well as leadership aspects of the IoT technology. The course discusses the Internet of Things framework for digital transformation and IoT strategic leadership. This two day course will take participants through an exploratory journey of this new evolution n sensor, cloud and Big Data.
What You'll Learn
- Discover the IoT landscape and technology stack (IoT vs. Industry IoT)
- Learn about IoT product management
- Understand how IoT influences financial cost consideration
- Discover how data flows through IoT through Big Data and analytics
- Overview of different types of sensors (temperature, proximity, pressure, water quality, chemical/smoke, gas, level and IR)
- Create a business model for IoT
- Integrate business model canvas for IoT using Business Model Generation
- Analyze importance of Big Data and Analytics for IoT
- Keeping up with the latest trends for IoT
Curriculum
- Welcome
- What is IoT and technology landscape
- Samples of IoT and how they are being used in the market
- What are IoT applications in industries (Industry IoT)
- Differences between IoT and Industry IoT
- Differentiate IoT and Industry IoT n terms of targets, sales cycle, marketing, installation and cost
- The IoT technology stack and how they are being used (Devices, embedded software, communications, cloud and applications)
- IoT decisions framework
- IoT layer consideration for successful implementation
- Consideration for design, data, business, technology, security, standard and regulation
- How to identify target users for IoT
- Identifying IoT persona
- What are different IoT personas
- Examples of IoT – User Experience (UX)?
- Define the target audience, problem statement and value proposition?
- Exercise: Create a plan within the industry of how to implement an IoT framework end-to end
- How data flows through the IoT through big data & analytics
- The most important value of IoT
- Importance of big data & analytics for IoT
- Metrics of performance analytics in IoT
- The business model for IoT
- Steps for creating a business model for IoT
- Integrate business model canvas for IoT using Business Model Generation
- What is the IoT value chain
- How to monetize per layer
- Cost per unit in each layer
- Exercise: Monetizing an IoT application in retail inventory
- The different types of sensors for IoT
- Temperature sensors
- Proximity sensors
- Pressure sensors
- Water quality sensors
- Chemical/smoke and gas sensors
- Level sensors
- IR
- Device considerations for implementing IoT
- Types of sensors
- Processing power
- Amount of local storage
- Power requirements
- Communication ports
- Usable lifespan
- Environmental requirements (temperature, noise, vibrations, etc.)
- Gateway architecture
- The latest Internet of Things (IoT) trends in the industry
- Blockchain implementing IoT
- How DDoS Stack (Distributed Denial of Service) implements IoT
- The six principles of IoT security across the stack
- Trends in mobile for IoT? How do they relate
- Categories being added to smart markets for IoT
- The relation between IoT and market talent
Who should attend
The course is highly recommended for –
- Business analysts
- Technical architects
- Software engineers
- IT managers
- Executives
- Entrepreneurs
Prerequisites
There are no mandatory prerequisites for this course. However, completing the Applied Statistics for Data Scientists course prior to taking up this course, would be beneficial.
