Instructor-led Sessions
36 Hours of Online Live Instructor-Led Classes. Weekend Class : 12 sessions of 3 hours each. Weekday Class : 18 sessions of 2 hours each.
Learn IoT from iteanz the market leader!
Enhance your skill set and boost your hirability through innovative and hands on Internet of Things (IoT) with iteanz.
Come 2020 and millions or even billions of smart electronic devices, linked by the Internet, would interact with each other independent of human intervention. This network of interacting electronic devices is named as the Internet of Things (IoT). Looking at it from our times (2013), one could expect the IoT to consist of PCs, tablet computers, digital cameras, e-Book readers, mobile phones, robots, private and public computer networks and whatever new smart electronic devices that would be developed between now and 2020.
Ultimately, the “Internet of Things” represents only the latest in the ongoing evolution of the Internet. It will almost certainly be a different landscape six months from now. Choose IoT training with iteanz and accelerate your IT career.
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Training Features
Lifetime Access
You get lifetime access to Learning Management System (LMS) where presentations, quizzes, installation guide & class recordings are there.
Real-life Case Studies
Live project based on any of the selected use cases, involving implementation of the various IOT services.
24 x 7 Expert Support
We have 24x7 online support team to resolve all your technical queries, through ticket based tracking system, for the lifetime.
Assignments
Live project based on any of the selected use cases, involving implementation of the various IOT services.
Certification
Towards the end of the course, you will be working on a project. Iteanz certifies you as an IOT Expert based on the project.
Course Outline
Chapter 1:Introduction
- Case Studies from Nest, CISCO and top industries
- IoT adaptation rate in North American & and how they are aligning their future
- business model and operation around IoT
- Broad Scale Application Area
- Smart House and Smart City
- Industrial Internet
- Smart Cars
- Wearables
- Home Healthcare
- Business Rule Generation for IoT
- 3 layered architecture of Big Data — Physical (Sensors), Communication , and Data
- Intelligence
Chapter 2: All about Sensors – Electronics
- Basic function and architecture of a sensor — sensor body, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure,
- legacy and modern sensor network — all the basics about the sensors
- Development of sensor electronics — IoT vs legacy, and open source vs traditional PCB design style
- Development of sensor communication protocols — history to modern days. Legacy protocols like Modbus, relay, HART to modern day Zigbee, Zwave, X10,Bluetooth, ANT, etc.
- Business driver for sensor deployment — FDA/EPA regulation, fraud/tempering detection, supervision, quality control and process management
- Different Kind of Calibration Techniques — manual, automation, infield,
- secondary primary and calibration — and their implication in IoT
- Powering options for sensors — battery, solar, Witricity, Mobile and PoE
- Hands on training with single silicon and other sensors like temperature, pressure, vibration, magnetic field, power factor etc.
Chapter 3: Fundamental of M2M communication — Sensor Network and Wireless protocol
- What is a sensor network? What is ad-hoc network?
- Wireless vs. Wireline network
- WiFi- 802.11 families: N to S — application of standards and common vendors.
- Zigbee and Zwave — advantage of low power mesh networking.
- Long distance Zigbee.
- Introduction to different Zigbee chips.
- Bluetooth/BLE: Low power vs high power, speed of detection, class of BLE.
- Introduction of Bluetooth vendors & their review.
- Creating network with Wireless protocols such as Piconet by BLE
- Protocol stacks and packet structure for BLE and Zigbee
- Other long distance RF communication link
- LOS vs NLOS links
- Capacity and throughput calculation
- Application issues in wireless protocols — power consumption, reliability, PER,QoS,LOS
- Hands on training with sensor network
1. PICO NET- BLE Base network
2. Zigbee network-master/slave communication
3. Data Hubs : MC and single computer ( like Beaglebone ) based datahub
CHAPTER 4:Review of Electronics Platform, production and cost projection
- PCB vs FPGA vs ASIC design-how to take decision
- Prototyping electronics vs Production electronics
- QA certificate for IoT- CE/CSA/UL/IEC/RoHS/IP65: What are those and when needed?
- Basic introduction of multi-layer PCB design and its workflow
- Electronics reliability-basic concept of FIT and early mortality rate
- Environmental and reliability testing-basic concepts
- Basic Open source platforms: Arduino, Raspberry Pi, Beaglebone, when needed?
- RedBack, Diamond Back
CHAPTER 5:Conceiving a new IoT product- Product requirement document for IoT
- State of the present art and review of existing technology in the market place
- Suggestion for new features and technologies based on market analysis and patent issues
- Detailed technical specs for new products- System, software, hardware, mechanical, installation etc.
- Packaging and documentation requirements
- Servicing and customer support requirements
- High level design (HLD) for understanding of product concept
- Release plan for phase wise introduction of the new features
- Skill set for the development team and proposed project plan -cost & duration
- Target manufacturing price
CHAPTER 6:Introduction to Mobile app platform for IoT
- Protocol stack of Mobile app for IoT
- Mobile to server integration –what are the factors to look out
- What are the intelligent layer that can be introduced at Mobile app level ?
- iBeacon in IoS
- Window Azure
- Linkafy Mobile platform for IoT
- Axeda
- Xively
CHAPTER 7:Machine learning for intelligent IoT
- Introduction to Machine learning
- Learning classification techniques
- Bayesian Prediction-preparing training file
- Support Vector Machine
- Image and video analytic for IoT
- Fraud and alert analytic through IoT
- Bio –metric ID integration with IoT
- Real Time Analytic/Stream Analytic
- Scalability issues of IoT and machine learning
- What are the architectural implementation of Machine learning for IoT
CHAPTER 8:Analytic Engine for IoT
- Insight analytic
- Visualization analytic
- Structured predictive analytic
- Unstructured predictive analytic
- Recommendation Engine
- Pattern detection
- Rule/Scenario discovery — failure, fraud, optimization
- Root cause discovery
CHAPTER 9:Security in IoT implementation
- Why security is absolutely essential for IoT
- Mechanism of security breach in IOT layer
- Privacy enhancing technologies
- Fundamental of network security
- Encryption and cryptography implementation for IoT data
- Security standard for available platform
- European legislation for security in IoT platform
- Secure booting
- Device authentication
- Firewalling and IPS
- Updates and patches
CHAPTER 10:Database implementation for IoT : Cloud based IoT platforms
- SQL vs NoSQL-Which one is good for your IoT application
- Open sourced vs. Licensed Database
- Available M2M cloud platform
- Axeda
- Xively
- Omega
- NovoTech
- Ayla
- Libellium
- CISCO M2M platform
- AT &T M2M platform
- Google M2M platform
CHAPTER 11:A few common IoT systems
- Home automation
- Energy optimization in Home
- Automotive-OBD
- IoT-Lock
- Smart Smoke alarm
- BAC ( Blood alcohol monitoring ) for drug abusers under probation
- Pet cam for Pet lovers
- Wearable IOT
- Mobile parking ticketing system
- Indoor location tracking in Retail store
- Home health care
- Smart Sports Watch
CHAPTER 12: Big Data for IoT
- 4V- Volume, velocity, variety and veracity of Big Data
- Why Big Data is important in IoT
- Big Data vs legacy data in IoT
- Hadoop for IoT-when and why?
- Storage technique for image, Geospatial and video data
- Distributed database
- Parallel computing basics for IoT
Why iteanz for iot training?
- Top technical trainers
- Real Time and Hands on Experience Training
- On Time Course Completion
- Comprehensive curriculum
- Innovative & interactive Training
- Superb satisfaction scores
- High Certification Pass Rate
Prerequisites
- There are no prerequisites for this data science online training course. If you are new in the field of data science, this is the best course to start with.
- A Windows, Linux or Mac PC/Laptop
Intended Audience
- IOT Absolute Beginners. No prior IOT experience necessary
- Any IT professionals looking for a career switch into IoT
- Any Graduates looking to build a career in IoT and who are interested in Programming
What People Say
I've never seen any training company like iteanz, the training was very good and highly practical. Good support Staff to address any support request on time.
Ram
Software Professional
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