Data Science + Embedded system Job Assistance Program - ( Warriors Way Gold Membership )

₹ 29,998

What you will get :
19 Courses
JOB Assistance
300 + Projects
Intensive Hackathon Live session
From Scratch
Live session on every Saturday
Interview Questions
JOB Posting
14 Internship Certificate
2 year validity
Soft Skill Courses
Technical Skill Set:
✅Python Programming

✅Data Analytics

✅Artificial Intelligence

✅Machine Learning

✅Deep Learning

✅Computer Vision

✅R Programming

✅Raspberry Pi

✅Embedded Design

✅Internet of Things

✅PCB Design




Mindset & Soft Skills:
✅Resume Building

✅LinkedIn Mastery

✅Interview Skill

✅Time Management

✅Leadership Skill

Detailed agenda of technical courses
Python Master Class
✅Introduction to Python

✅Installing & Working with Python IDLE

✅Configuring Environmental Variables - Command Window

✅Installing Anaconda Navigator (Jupyter Notebook)

✅Working with Anaconda Navigator (Spyder Notebook)

✅Working with Google Colab

✅Working with Pycharm

✅Working with Libraries

✅Simple Arithmetic

✅Introduction to Strings

✅Indexing and Slicing with Strings

✅String Properties and Methods

✅Print Formatting with Strings

✅Lists in Python

✅Dictionaries in Python

✅Tuples with Python

✅Sets in Python

✅Booleans in Python

✅I/O with Basic Files in Python

✅Python Objects and Data Structures

✅Comparison Operators in Python

✅Chaining Comparison Operators in Python with Logical Operators

✅If Elif and Else Statements in Python

✅For Loops in Python

✅While Loops in Python

✅Useful Operators in Python

✅List Comprehensions in Python

✅Methods and the Python Documentation

✅Introduction to Functions

✅Basics of Python Functions

✅Logic with Python Functions

✅Tuple Unpacking with Python Functions

✅*args and **kwargs in Python

✅Lambda Expressions, Map, and Filter Functions

✅Attributes & Class Keyword

✅Class Object Attributes and Methods

✅Inheritance and Polymorphism

✅Special(Magic/Dunder) Methods

✅Modules and Packages

✅name and "main"

✅Errors and Exceptions Handling

✅Pylint Overview

✅Decorators with Python Overview

✅Generators with Python

✅Python Collections Module

✅Opening and Reading Files and Folders

✅Python Datetime Module

✅Python Math and Random Modules

✅Python Debugger

✅Python Regular Expressions

✅Timing Your Python Code

✅Zipping and Unzipping files with Python

✅Setting Up Web Scraping Libraries

✅Grabbing a Title

✅Grabbing an Image

✅Book Examples

✅Introduction to Images with Python

✅Working with CSV Files in Python

✅Working with PDF Files in Python

✅Sending Emails with Python

✅Receiving Emails with Python

Computer Vision
✅DAY – 1 Introduction to Python & Computer Vision | Python Installation & Installing Libraries | Basic CV| Reading an image | Display,Writing, Saving an Image | Draw a line, circle, rectangle | Draw a text string |Find and Draw Contours | Image Resizing | Blurring an Image

✅DAY – 2 Create Border around Images | Convert an image from one color space to another | Scaling, Rotating, Shifting, and Edge Detection | Erosion and Dilation of images | Denoising of colored images | OpenCV Bitwise AND, OR, XOR, and NOT | Play a video using OpenCV | Video acquisition from the camera | Video acquisition from the Mobile Camera

✅DAY – 3 OpenCV Haar Cascades - Face detection | Eye detection | Mouth detection | Full/partial body detection

✅DAY – 4 Multi-template Matching with OpenCV

✅DAY – 5 OCR a Document, Form with Tesseract & OpenCV

✅DAY – 6 Object Tracking using OpenCV

✅DAY – 7 Watermarking images with OpenCV

✅DAY – 8 Saving Key event video clips with OpenCV

✅DAY – 9 Determining Object Shape and Color with OpenCV

✅DAY – 10 Real-time Panorama & Image Stitching with OpenCV

✅DAY – 11 Barcode reader using Computer Vision

✅DAY – 12 OpenCV Video Augmented Reality

✅DAY – 13 Recognizing digits with OpenCV and Python

✅DAY – 14 Document Scanner using OpenCV

✅DAY – 15 Harry Potter Invisible Cloak

Artificial Intelligence
✅DAY – 1 Overview of this course | Introduction to AI | How to create basic AI application (Chat bot using DialogFlow)

✅DAY – 2 How to install Python & Libraries | Basics of python Programming for AI.


✅DAY – 3 Introduction to Computer Vision| How to install computer vision libraries

✅DAY – 4 Moving Object Detection and tracking using OpenCV

✅DAY – 5 Face Detection and Tracking using OpenCV

✅DAY – 6 Object Tracking based on color using OpenCV

✅DAY – 7 Face Recognition using OpenCV

✅DAY – 8 Face Emotion recognition using 68-Landmark Predictor OpenCV


✅DAY – 9 Introduction to Deep learning | How to install DL libraries

✅DAY – 10 Designing your First Neural Network

✅DAY – 11 Object recognition from Pre-trained model

✅DAY – 12 Image classification using Convolutional Neural Network

✅DAY – 13 Hand gesture recognition using Deep Learning

✅DAY – 14 Leaf disease detection using Deep Learning

✅DAY – 15 Character recognition using Convolutional Neural Network

✅DAY – 16 Label reading using Optical Character recognition

✅DAY – 17 Smart Attendance system using Deep Learning

✅DAY – 18 Vehicle detection using Deep Learning

✅DAY – 19 License plate recognition using Deep Learning

✅DAY – 20 Drowsiness detection using Deep Learning

✅DAY – 21 Road sign recognition using Deep Learning


✅DAY – 22 Introduction to Machine learning| How to install ML libraries

✅DAY – 23 Evaluating and Deploying the various ML model

✅DAY – 24 Fake news detection using ML

✅DAY – 25 AI snake game design using ML


✅DAY – 26 Introduction to NLP & it’s Terminology | How to install NLP Libraries NLTK

✅DAY – 27 Title Formation from the paragraph design using NLP

✅DAY – 28 Speech emotion analysis using NLP


✅DAY – 29 Cloud-based AI, Object recognition using Amazon Web Service (AWS) & Imagga

✅DAY – 30 Deploying AI application in Raspberry Pi with Neural Compute stick & Nvidia Jetson Nano

Machine Learning
✅Day-1: Overview A.I | Machine Learning

✅Day-2: Introduction to Python | How to write code in Google Colab, Jupyter Notebook, Pycharm & IDLE


✅Day-3: Advertisement Sale prediction from an existing customer using


✅Day-4: Salary Estimation using K-NEAREST NEIGHBOR

✅Day-5: Character Recognition using SUPPORT VECTOR MACHINE

✅Day-6: Titanic Survival Prediction using NAIVE BAYES

✅Day-7: Leaf Detection using DECISION TREE

✅Day-8: Handwritten digit recognition using RANDOM FOREST

✅Day-9: Evaluating Classification model Performance using CONFUSION


✅Day-10: Classification Model Selection for Breast Cancer classification

✅Day-11: House Price Prediction using LINEAR REGRESSION Single Variable

✅Day-12: Exam Mark Prediction using LINEAR REGRESSION Multiple Variable

✅Day-13: Predicting the Previous salary of the New Employee using


✅Day-14: Stock price prediction using SUPPORT VECTOR REGRESSION

✅Day-15: Height Prediction from the Age using DECISION TREE REGRESSION

✅Day-16: Car price prediction using RANDOM FOREST

✅Day-17: Evaluating Regression model performance using R-SQUARED


✅Day-18: Regression Model Selection for Engine Energy prediction.


✅Day-19: Identifying the Pattern of the Customer spent using K-MEANS


✅Day-20: Customer Spending analysis using HIERARCHICAL CLUSTERING

✅Day-21: Leaf types data visualization using PRINCIPLE COMPONENT


✅Day-22: Finding Similar Movie based on ranking using SINGULAR VALUE



✅Day-23: Market Basket Analysis using APIRIORI

✅Day-24: Market Basket Optimization/Analysis using ECLAT


✅Day-25: Web Ads. Click through Rate optimization using UPPER BOUND


Natural Language Processing

✅Day-26: Sentimental Analysis using Natural Language Processing

✅Day-27: Breast cancer Tumor prediction using XGBOOST


✅Day-28: Bank Customer classification using ANN

✅Day-29: Pima-Indians Diabetes Classification using CONVOLUTIONAL


✅Day-30: A.I Snake Game using REINFORCEMENT LEARNING

Data Analytics
✅Day-1: Introduction to Artificial Intelligence, Data Analytics & Road Map to become a Data Scientist


✅Day-2: Data Preparation - Power Query & Tables

✅Day-3: Data analytics- Formula & Pivot Table

✅Day-4: Story Telling - Charts & Dashboard

✅Day-5: Automation - VBA Macros & Power Query


✅Day-6: Descriptive Statistics - Mean, Mode, Median, Quartile, Range, InterQuartile Range, Standard Deviation

✅Day-7: Probability - Permutations, Combinations

✅Day-8: Population and Sampling

✅Day-9: Probability Distributions - Normal, Binomial and Poisson Distributions

✅Day-10: Hypothesis Testing & ANOVA - One Sample and Two Samples - z Test, t-Test, F Test and Chi-Square Test

BI tools - Tableu

✅Day-11: Connect Tableau to a Variety of Datasets

✅Day-12: Analyze, Blend, Join, and Calculate Data

✅Day-13: Visualize Data in the Form of Various Charts, Plots, and Maps

BI tools - Power BI

✅Day-14: Connect Tableau to a Variety of Datasets

✅Day-15: Visualize Data in the Form of Various Charts, Plots, and Maps and Calculate Data


✅Day-16: Introduction to Python & Installing Python and its Libraries

✅Day-17: Basic Python Programming for Data Analytics

Numpy & Pandas

✅Day-18: Python Numpy functions

✅Day-19: Pandas for Data analytics in Python

Data Visualization

✅Day-20: Matplotlib for data visualization

✅Day-21: Seaborn for data visualization

Kaggle Exploratory

✅Day-22: Kaggle Dataset and Notebooks

Database - SQL

✅Day-23: SQL basics for Data analytics - Part-1

✅Day-24: SQL basics for Data analytics - Part-2

Database - MongoDB

✅Day-25: MongoDB basics for Data analytics

Machine Learning

✅Day-26: Introduction to Machine Learning & its libraries

✅Day-27: Evaluating and Deploying Machine Learning Classification algorithm for classification of State of Electric power system

Deep Learning

✅Day-28: Introduction to Deep Learning & its libraries

✅Day-29: Covid-19 Detection using X-Ray Images with CNN

Natural Language Processing

✅Day-30: Tag Identification system using NLTK

Deep Learning
Section 1: Course Overview

✅ DAY–1 Introduction to Deep Learning

✅ DAY–2 Basic Computer Vision

Section 2: Artificial Neural Network

✅ DAY–3 Neurons & Perceptron

✅ DAY–4 Activation Function

✅ DAY–5 Gradient Descent

✅ DAY – 6 Stochastic Gradient Descent

✅ DAY – 7 Backpropagation

✅ DAY – 8 Artificial Neural Network – Project 1

Section 3: Deep Neural Network

✅ DAY – 9 Optimization Algorithms – SGD, Momentum, NAG, Adagrad, Adadelta , RMSprop, Adam

✅ DAY – 10 Batch Normalization

✅ DAY– 11 Hyperparameter tuning

✅ DAY– 12 Interpretability

✅ DAY– 13 Deep Neural Network – Project 2

Section 4: Convolutional Neural Network

✅ DAY– 14 Convolutional Neural Network & its Layers

✅ DAY– 15 CNN Architecture

✅ Day–16 Different frameworks on Deep Learning (Tensorflow, Keras, PyTorch & Caffe)

✅ Day-17 Object Recognition using Pre Trained Model – Caffe – Project 3

✅ Day-18 Image classification using Convolutional Neural Network from Scratch – Tensorflow & Keras – Project 4

✅ Day-19 Custom Image Classification using Transfer Learning – Project 5

✅ Day-20 YOLO Object recognition – Project 6

✅ Day 21 Image Segmentation – Project 7

✅ Day 22 Project using MxNet – Project 8

✅ Day 23 Project using PyTorch – Project 9

✅ Day 24 Social Distancing detector – Project 10

✅ Day 25 Face Mask detector – Project 11

Section 5: Recurrent Neural Network

✅ Day 26 Introduction to RNN and LSTM

✅ Day 27 Project using RNN – Project 12

Section 6:

✅ Day 28 Introduction CUDA Toolkit and cuDNN for deep learning

✅ Day 29 Getting started with the Intel Movidius Neural Compute Stick – Project 13

✅ Day 30 Custom Object classification using Nvidia Jetson – Project 15

R Programming
✅Day - 1 Introduction to R | Installing R studio | Fundamentals of R (Basic Syntax | Comments | Operators | Keywords | Data Types )

✅Day - 2 Variables | Decision Making | Control Flow | Functions

✅Day - 3 Data Structures - Strings | Vectors | Lists | Arrays | Matrices | Factors.

✅Day - 4 Data Frames

✅Day - 5 OOP’s Concepts - Classes | Objects | Encapsulation

✅Day - 6 OOP’s Concepts - Polymorphism | Inheritance | Abstraction | Looping over Objects

✅Day - 7 Error Handling | File handling | Packages in R

✅Day - 8 Data Interfaces | Data Visualization

✅Day - 9 R Statistics

✅Day - 10 R Regression

Raspberry Pi
✅Day 1 - Overview of this course | Details about Raspberry Pi&its Application

✅Day 2 - InstallingOperating System in Raspberry Pi | Basic Python Programming

✅Day 3 - Overview on Embedded Systems | Digital I/O with Raspberry Pi

✅Day 4 - Analog sensor interface using MCP3008 ADC | SPI Protocol

✅Day 5 - RFID based authentication system using Arduino | UART Protocol

✅Day 6 - Temperature &Humidity Detection & Alert using DHT11 Sensor

✅Day 7 - Water quality detection using PH Sensor | UART Protocol

✅Day 8 - Waterflow detection using Flow sensor | Pulse sensor | Interrupt

✅Day 9 - Message Transmission using MQTT & UDP Protocol

✅Day 10 - Sending Email Alert using SMTP Protocol

✅Day 11 - Simple Message Chat using LCD Display using Raspberry Pi

✅Day 12 - Touch screen display Interface with Raspberry Pi

✅Day 13 - DC Motor Speed Control using TrimPot | DC Motor

✅Day 14 - Automatic Door lock system using PIR | Servo Motor & Stepper Motor

✅Day 15 - Smart Energy meter system| ADC | SPI Protocol

✅Day 16 - Industry Monitoring System using IoT | Cloud

✅Day 17 - Webpage design forappliance control | Webserver | HTTP

✅Day 18 - Mobile controlled appliance via Internet| Application

✅Day 19 - Video surveillance system using Webserver

✅Day 20 - Weather reporter system using Weather Cloud | Smart Umbrella

✅Day 21 - Interfacing USB Webcamera | Pi Camera | Android Mobile camera with Raspberry Pi

✅Day 22 - Face Detection ,Tracking & Recognition using Raspberry Pi

✅Day 23 - Simple Book reader with OCR & Text to speech conversion using Raspberry Pi

✅Day 24 - Obstacle Avoidance Robot using Ultrasonic

✅Day 25 - Color Following Robot

✅Day 26 - Baby emotion recognition & Alert system | Music Play

✅Day 27 - Blind assistance system for Object recognition | Deep Learning

✅Day 28 - Re-speaker 4 Mic array interface with Raspberry Pi

✅Day 29 - 360 Degree LIDAR Interface with Raspberry Pi | ROS

✅ Day 30 - Brain Controlled Robot using Raspberry Pi & Brainsense

Embedded System Design & IoT
Week 1

✅ Day 1 - Introduction to Embedded System Design

✅ Day 2 - Choosing the Right Processor and Embedded Product Life cycle

✅ Day 3 - Challenges and Design Issues in Embedded Systems,

✅ Day 4 - Introduction to Real-Time Concepts,

✅ Day 5 - IoT Trends, IoT Architecture, IoT Applications, IoT Standards, and Protocols,

Week 2 - 8051

✅ Day 6 - 8051 Architecture-Keil

✅ Day 7 - Switch ,Relay,

✅ Day 8 - UART,SPI

✅ Day 9 - LCD,IIC

✅ Day 10 - 8051 Mini Project-Bluetooth based Home automation

Week 3- ARM7

✅ Day 11- ARM Architecture-Keil, LED Blinking

✅ Day 12- Switch ,Relay,

✅ Day 13- UART,SPI

✅ Day 14- LCD,IIC

✅ Day 15- ARM Mini Project -IoT based weather monitoirng system

Week 4 - CORTEX M4

✅ DAY 16- CORTEXM4 LPC4088 Architecture-Keil, LED Blinking

✅ DAY 17- Switch ,Relay,



✅ DAY 20 - Cortex -M4 - Temperature Monitroing using Zigbee and LORA

Week 5 - PIC

✅ DAY 21- Introduction to PIC Architecture

✅ DAY 22- MPLABIDE and LED Blinking

✅ DAY 23- Switch ,Relay, PWM



Week 6 - NodeMCU/ESP8266

✅ DAY 26 - Introduction to NODE MCU

✅ DAY 27 - Led,switch,relay,UART

✅ DAY 28 - Iot Temperature Data Logging

✅ DAY 29 - Build Your Home Automation with ESP8266 and Control Devices from Anywhere in the World

✅ DAY 30 - Conclusion and Wrap up-Graduation Day

Internet of Things -IoT
IoT Introduction and Architectures

✅ DAY–1 Introduction to IoT

✅ DAY–2 IoT Communication Protocols

✅ DAY–3 Introduction to ESP32 and NodeMCU

✅ DAY–4 Iot Clouds,Analytics & Datascience

✅ DAY–5 Sensors for IoT

IoT using Thingspeak

✅ DAY – 6 Sending Data to Thingspeak -Arduino+Humidity+Air quality(Weather monitoring system)

✅ DAY – 7 How to Analyze IoT Data in ThingSpeak

✅ DAY – 8 Deploying a Machine learning Model on the Cloud

✅ DAY – 9 Thingspeak for IoT in agriculture

✅ DAY – 10 Smart Humidity Sensor – ThingSpeak, MATLAB, and IFTTT

IoT with Microsoft Azure

✅ DAY– 11 Introduction to IoT with Microsoft Azure

✅ DAY– 12 Implementing IoT with Azure

✅ DAY– 13 Edge Computing and Analytics

✅ DAY– 14 Coginitive services,Computer vision API

✅ DAY– 15 Weather monitoring station using Microsoft Azure and Arduino

Iot Projects and Case Study

✅ Day-16 Home automation using Google Assistant

✅ Day-17 Industrial Iot using Zigbee and WIFI(Windmill case study)

✅ Day-18 Recording sensor data to google sheet using IFTTT with Arduino and sending alerts

✅ Day-19 Real time Video surveillance esp32cam and Blynk App

✅ Day-20 Predictive Maintenance of a Duct Fan Using Nodemcu, ThingSpeak and MATLAB

IoT with AWS IoT

✅ Day 21 Introduction to AWS IoT,Setting up Free tier AWS, AWS CLI, Policys, Security Credentials, and Testing

✅ Day 22 Raspberry PI3 with AWS IOT SDK

✅ Day 23 SNS Push Notifications,AWS IoT Analytics

✅ Day 24 AWS Lambda Functions for IoT

✅ Day 25 HTTPs Arduino sketch to AWS IoT Core for the ESP8266 and ESP32

✅ Day 26 Using Mongoose OS on embedded devices for AWS IoT

✅ Day 27 Storing data into the Dynamo Database from the AWS IoT control panel

✅ Day 28 AWS Quicksight for data analytics and visulizations

✅ Day 29 AWS Device Shadows and multiple Pub/Sub’s

✅ Day 30 Weather monitoring station using AWS IOT

PCB Design
✅Day 1- Introduction to PCB Design and Terminologies and Installation of Orcad Trail version

✅Day 2 -Introduction to Schematic Capture

✅Day 3- Introduction to Allegro and Footprint Creation

✅Day 4- Importing Schematics in allegro ,Placement and route

✅Day 5- Gerber Creation, BOM, PDF

✅Day 6- How to Design a 8051 Microcontroller Board

✅Day 7- Library Creation

✅Day 8- Schematics Design

✅Day 9- Footprint Creation

✅Day 10- Design rules check-Import and Placement

✅Day 11- Layout

✅Day 12- Layout Design , Gerber Creation, Recap, schematic design consideration,Layout Design Consideration

✅DAY –1 Overview of this course | Details about Arduino & Application

✅DAY –2 InstallingArduino Software & Libraries | Programming Arduino


✅DAY –3 Overview on Embedded Systems | LED , Switch & Buzzer with Arduino


✅DAY –4 Rat Trap design using LDR & Laser Arduino | ADC - SPI Protocol

✅DAY –5 Bluetooth controlled Light with Arduino | UART Protocol

✅DAY –6 I2C LCD with Arduino | I2C Protocol

✅DAY –7 RFID based authentication system using Arduino | UART Protocol


✅DAY –8 Motion Detection using PIR & IR Sensor | Digital Sensor

✅DAY –9 Temperature Monitoring System using Temperature sensor | Analog Sensor

✅DAY –10 Distance Measurement using Ultrasonic Sensor

✅DAY –11 Water level Detection & Alert system | Analog & Digital Sensor

✅DAY –12 Humidity Detection & Alert using DHT11 Sensor

✅DAY –13 Water quality detection using PH Sensor | UART Protocol

✅DAY –14 Waterflow detection using Flow sensor | Pulse sensor

✅DAY –15 Keypad with Arduino for Stop Clock


✅DAY –16 Simple Message Chat using LCD Display Arduino

✅DAY –17 Switch press Counter using 7-Segment display

✅DAY –18 TFT Display with Arduino


✅DAY –19 DC Motor Speed Control using TrimPot | DC Motor

✅DAY –20 Automatic Door lock system using PIR & Servo | Servo Motor

✅DAY –21 Stepper Motor Control using Arduino


✅DAY –22 Robot Design | Bluetooth & Voice controlled robot using Arduino

✅DAY –23 Obstacle Avoidance Robot using Ultrasonic


✅DAY –24 Power Monitoring system | ADC | SPI Protocol

✅DAY –25 Fault Detection | ADC

Internet of Things - ARDUINO

✅DAY –26 Industry Monitoring System using IoT | ESP8266


✅DAY–27 RADAR using Ultrasonic & Arduino with Matlab


✅DAY –28 Audio speaker from a Signal using Arduino & Signal Generator

✅DAY –29 Li-Fi based Data transmission using Arduino

✅DAY –30 Brain Controlled Robot using Arduino

✅Day 1 Introduction to FPGA

✅Day 2 Introduction to VHDL , How to create a Project in Xilinx ISE .

✅Day 3 Operators and Data Flow Modeling (VHDL)

✅Day 4 Structural & Behavioral Modeling

✅Day 5 Creating a Test Bench

✅Day 6 How to Design a Spartan 6 FPGA Board

✅Day 7 FPGA Programming for Blinking LED ,SWITCH, Relays and Buzzer

✅Day 8 UART Programming on FPGA

✅Day 9 LCD, SEVEN SEGMENT Programming on FPGA

✅Day 10 ADC and DAC Programming on FPGA

✅Day 11 Bluetooth and Relay Programming -Bluetooth Home Automation using FPGA

✅Day 12 Internet of Things using FPGA -Part 1 (Interfacing with WIFI)

✅Day 13 Internet of Things using FPGA -Part 2 (Sending Temperature data to Cloud)

✅Day 14 Motor control using FPGA (PWM )

✅Day 15 Embedded system Design using FPGA (C Based programming on FPGA)

✅Day 16 Median Filter on Spartan 6 FPGA

✅Day 17 Edge Detection on FPGA using C Language

✅Day 18 IoT Programming on FPGA using C Language

✅Day 19 Debugging with Chip scope PRO

✅Day 20 Introduction to Python Programming on FPGA

✅Day 21 Yolo object detection on FPGA

✅Day 22 Real time edge detection using ZYNQ FPGA (pynq)

✅Day 23 Real time Moving object detection using ZYNQ FPGA (pynq)

✅Day 24 Discrete Wavelet Transform using Spartan 6 FPGA(C Language)

✅Day 25 Image Segmentation using Spartan6 FPGA(Xilinx XPS)

✅Day 26 Introduction to Vivado Design Suite

✅Day 27 Implementing LED , UART Using - Vivado Design Suite

✅Day 28 Machine Learning with Python in PYNQ

✅Day 29 OpenCV for Image Processing & Video_processing (PYNQ with Python)-ZYNQ FPGA

✅Day 30 Conclusion and Future of VLSI

✅Day - 01 Getting Started With Matlab

✅Day - 02 Image processing using Matlab

✅Day - 03 Video Processing using Matlab

✅Day - 04 Medical Image Processing using Matlab

✅Day - 05 Graphical User Interface Matlab

✅Day - 06 App development using Matlab

✅Day - 07 Computer Vision using Matlab

✅Day - 08 Fuzzy logic design using Matlab

✅Day - 09 Neural Network using Matlab

✅Day - 10 Machine Learning using Matlab

✅Day - 11 Deep Learning using Matlab

✅Day - 12 Neuro-Fuzzy Designer using Matlab

✅Day - 13 Image Segmentation using Matlab

✅Day - 14 Image Compression using Matlab

✅Day - 15 Feature Extraction using Matlab

✅Day - 16 Face Recognition using Matlab

✅Day - 17 Augmented Reality using Matlab

✅Day - 18 Image Denoising using Matlab

✅Day - 19 Arduino Programming using Matlab

✅Day - 20 Image Quality Metrics using Matlab

✅Day - 21 Steganography using Matlab

✅Day - 22 Real-time Object detection using Matlab

✅Day - 23 Raspberry Pi programming using Matlab

✅ Day - 24 Speech Processing using Matlab

✅Day - 25 Audio Processing using Matlab

✅Day - 26 Data Hiding using Matlab

✅Day - 27 Cryptography using Matlab

✅ Day - 28 Machine Learning and IoT using Matlab

✅ Day - 29 SLAM using Matlab

✅ Day - 30 Semantic Segmentation using Deep learning Matlab