JOB Oriented Training in IoT , Machine Learning using Node MCU and Raspberry Pi @Hyderabad

Designed suitably with inputs from Academic personnel’s,this specific training program on IoT using Node NCU, Raspberry Pi,Python Programming & Machine Learning is floated with an Industrial point of view. This training program is designed in a way with a mix of 80% Hands on Sessions & subsequent theory sessions to cater to the industrial requirements and make the candidates industry ready.

Course Outcomes:

Upon successful completion of the training program, the candidate will

• Have Adept knowledge of Controller Architectures – Raspberry Pi , Node MCU
• Be able to acquire vast Python & Embedded C Programming Skills
• Have definite knowledge on accessing the Open Source Cloud platforms
• Gain a deep thrust to the Machine Learning Algorithms – Program specific & from the coding point
• Acquire specific skillsets on Image Processing Concepts & Open CV
• Have a better understanding on the Interfacing of Peripherals & Sensors to the Controllers  

Week 1: Node MCU Controller & Interface

DAY – 1| Introduction to Node MCU and IDE

• Basic NODE MCU and ARDUINO Uno Presentation
• Software Installation Node MCU in ArduinoIDE
• Embedded CProgramming
• Interface LED, Buzzer on GPIO
• Interface IR / PIR Sensor with Node MCU.

Day – 2 | UART communication and Ultrasonic (Hands on Training)

• (Switch Application) on/off using char and string Receive
• Interface Ultrasonic sensor with Arduino
• Ultrasonic sensor distance measuring and display on serial monitor
• Ultrasonic sensor with buzzer "obstacle detected," on serial monitor
• Interface PIR Sensor and develop an Security Alert

DAY - 3 | ADC &IoT (Hands on Training)

• Control LED / Buzzer through Wifi
• Comparison of ESP8266 and NODE MCU
• Interface Temperature Sensor with Node MCU
• ON/OFF Switching of appliances or home device from the cloud
• Creating a webpage in HTML/PHP
• Reading sensor values and passing it to local server.

DAY - 4 | Internet of things with free Cloud service (Hands on Training)

• Thingspeak introduction
• Account creation in thingspeak and getting API key
• Passing analog and digital sensor values to thingspeakusing API key
• Remote controlling of the devices.

 DAY - 5 | Task with digital sensor and IoT

• PWM with ultrasonic sensor
• Changing the intensity of buzzer with respect to distance
• NODE MCU (PWM) with LED

Week 2: Python Programming & Open CV

DAY – 6| Introduction to Python

• Introduction to Basic programming and concepts
• Core objects and Built-in-Functions
• Conditional statements and loops
• Hands on Training with Python Programmes

Day – 7 | Python Programming

• Inheritance&File Handling With Python
• Classes, methods, functions and set of objects
• Exception handling
• Creating a new data type

DAY - 8 | Python for IoT

• Weather application with python
• Weather notification
• Python with Thingspeak application
• Python GUI creation basics
• Project implementation

DAY - 9 | Open CV- image processing with python

• Open CV basics
• Basic image commands in open CV
• Colour conversions
• Object detection
• Threshold segmentation – binary , colour etc

 DAY - 10 | Task with digital sensor and IoT

• Video processing Concepts
• Interface IP CAM android app- using wireless method for video and image capturing
• Develop a Code for Video frame conversion
• Develop a Face recognition Algorithm and Demonstrate.
• Project Development - Multiple object tracking based on colours
• Project Development - Digital ART Demo.
• Project Development - Vehicle and pedestrian detection

 Week 3: Raspberry Pi & Internet of Things [IoT]

 DAY - 11 | Raspberry Pi & Its Programming

• Raspberry pi 3 with python fundamentals
• OS installation
• Python Programme on Peripheral Interface
• Peripheral interface with Pi - led and buzzer.

DAY - 12 | Hardware Peripheral Interface with Pi (Hands on Training)

• Interface IR and PIR Sensor
• Develop a code using IR sensor for object detection
• Develop a code usingPIR sensor for security application
• Develop a project for Smart room using PIR Sensor – person count

DAY - 13 | Sensors and Camera Interface with Pi (Hands on Training)

• Internet of things with raspberry Pi
• Interface Ultrasonic with Pi
• Develop a Code for Object detection with distance measurement- blind spot detection
• Interface a Camera with Pi for security application
• Project Development - Capturing and sending image on sensor detection through mail

DAY - 14| Sensors and Camera Interface with Pi (Hands on Training)

• Creating webpage for controlling devices
• Espeak software introduction
• Audio output for sensor detection for visually impaired person
• Passing Sensor Information To Our Webpage

DAY - 15 | Pi interface with Open Source Cloud

• Develop a Platform for Thingspeak with Pi
• Writing and reading values from thingspeak
• Thingspeak security system
• Android app with raspberry and thingspeak for controlling devices

Week 4: Machine Learning Algorithms and Concepts

 DAY - 16 | Python on Machine Learning

• Introduction to Algorithm
• File handling, Exception handling, Command line arguments, modules and packages
• Functions, String, List
• Python Regular Expressions
• Accessing CSV,JSON,XML files and Logging in python

 DAY - 17 | NumPy, Pandas in for Data analysis and ML

• Data types:Array creation, I/O with NumPy, Indexing,Broadcasting,Byte-swapping,Structuredarrays, Sub classing array
• Data Visualization, 2D plotting with Matplotlib
• Advanced data visualization with Seaborn
• Exploring Data with Pandas, Data manipulation with Pandas
• Statistical & Tine Series analysis with Pandas

DAY - 18 | Machine Learning Theory with hands on Programming

• Design a Learning System
• Bayesian Learning Techniques
• Linear models for Regression/Classification
• Non-linear Models &Decision Trees

DAY - 19 | Machine Learning Algorithms

• Instance-based Learning, k-Nearest Neighbor Learning
• Support Vector Machine,
• Linearly separable data &Non-linearly separable data
• K-means clustering &Genetic Algorithm

 DAY - 20 | Machine Learning Projects Walkthrough

• Data cleaning and formatting , Exploratory data analysis, Feature engineering and selection
• Establish a baseline and compare several machine learning models on a performance metric
• Perform hyper-parameter tuning on the best model to optimize it for the problem
• Developing and Evaluating the Projects on Machine Learning.

Registration Fee 

For Students : Rs.8000/-

Certificate of Participation will be provided by Pantech

Participant Seats are limited to 20 Per Batch. This will be on First Come , First Serve basis .

Please feel free to call the undersigned for any further clarifications .