Embedded Systems

Qfour offeres :

The Experimental Learning Phase
Industry expected Course contents
Quality R&D Work Labs
24 weeks of efficient Professional training
Daily based assignments
Module wise Lab exams
Real Time project assistance
Week wise Mock Interviews
Industry ready professionals

Target Audience :

Entry level engineers who want to learn Embedded programming using C
Experienced professionals who want to switch into development career

Qfour Embedded Modules:

Practical C :

Fundamentals of C
Conditional Statements
Loops
Functions
Arrays
Strings
Storage Classes
Structures & Unions
Enumerated data types
Bit Operations
Pointers
Dynamic Memory Allocation
File Handling Concepts
Low-level Programming
Command line Arguments
Compiler in Practical
Data Structures
Sorting and Searching Techniques
Concepts and Real Time Exposure
Application development

Microcontroller INTEL – 8051 :

Introduction Overview of Architecture of 8051
Low-level Programming Concepts
Middle Level Programming Concepts
Cross Compiler
Embedded C Programming
Embedded C Debugging
Memory Models
Library Reference
On-Chip Peripherals

Ports: Input/Output
Timers & Counters
Interrupts
UART External Interfaces
LEDS and Switches
LCD Display
Seven Segment Display
Keypad Matrix
Stepper Motor
DC Motor
Sensors
Communication Devices
GSM and GPS

ARM :

Introduction to ARM Microcontroller Architecture and Core Feature
Version History
Data Flow Model
Registers and CPU Modes
Memory Organization
Interrupts
Pipelining
ARM Assembly Language Programming
Addressing Modes
ARM 7 Instruction Set
Usage of Keil IDE
Demonstrating ARM ISA
Demonstrating THUMB ISA
ARM Embedded C language Implementation
Exposure to an ARM7 CPU Core Based Microcontroller
LPC2114-ARM7 Based Microcontroller from Philips Semiconductors
On-Chip System Peripherals
Bus Structure (AMBA)
Memory Map
Phase Locked Loop
VPB Divider
Pin Connect Block
On-Chip User Peripherals
All Input and output peripherals

Linux programming

Qfour offeres: :

The Experimental Learning Phase
Industry expected Course contents
Quality R&D Work Labs
24 weeks of efficient Professional training
Daily based assignments
Module wise Lab exams
Real Time project assistance
Week wise Mock Interviews
Industry ready professionals

Target Audience:

Entry level engineers who want to learn Embedded programming using C
Experienced professionals who want to switch into development career

Embedded Linux Modules :

Data Structures :

Introduction to Data Structures
Timing and Complexity
Linked List
Stack
Queue
Searching
Sorting
Trees
Hashing

Linux Systems :

Over view of Linux Systems
Command Line Interface
User Interface
Directory & File System Structure
VIsual Editor
Shell Scripting
Application Development
Demo and Exam

Linux Internals

OS & LINUX Basics
Components of LINUX
Overview of the Kernel Sturcture
Kernel Designs
LINUX File System
System Calls
Processes
Process States
Schedular
Process Descriptor/Structure
Basic Process Management
Creating a Process
Special Case of Processes
Signal
How Programs Responds to Signals
Handling Signals
signal.h and Signal Related Functions
Signal and Interrupts
Threads
Synchronization
Mutexes
Semaphores for Threads

IOT and Machine Learing

Qfour offeres :

The Experimental Learning Phase
Industry expected Course contents
Quality R&D Work Labs
24 weeks of efficient Professional training
Daily based assignments
Module wise Lab exams
Real Time project assistance
Week wise Mock Interviews
Industry ready professionals

Target Audience :

Entry level engineers who want to learn IOT and Machine learning using C and Python
Experienced professionals who want to switch into development career

IOT Modules:

IoT in Industry also called as IIoT Industrial internet of thing which provides integrated solutions of industrial problems. IIot is used to identify and correct problems and inefficiencies which could save both time and money. IIoT leverage Sensors Machine-to-Machine communications and automation technologies to use Bigdata and machine learning technologies to streamline and optimize industrial processes.

IOT :

Concepts and Definitions of The Internet of Things (IoT)
History of IoT
Requirements of IoT
Functionalists and structure of IoT
IoT enabling technologies
IoT Architecture
Major component of IoT(Hardware & Software)
IoT communication and networking protocols
Role of wired and wireless communication
IoT services and applications
IoT Standards
Connectivity
How to Design IoT Application (Web, Mobile, Device)
Controllers and Processors (Intel Edison, Orange Pi, Onion Omega, Proton, ESP, Raspberry pi, ARM based Controllers)
Real-time systems and embedded software
OS and Drivers
Hardware & Software Requirements
How to transfer data by Wireless / Wired connectivity
Ipv4/Ipv6, Ethernet/GigE
GSM , 2g ,3g ,4g & 5g
IEEE 802.15.4, IEEE 802.15.4e, 802.11ah
Relay Access Point (AP)
Grouping of station
Overview and Role of Storage in Cloud / Server /Inhouse Storage.
Databases Connectivity with IOT and Use Cases
Case Study over Mysql
Case Study over Cloud Services And Administration
Analysis Of data using Ipython Module
Visualization and interpretation of Data
Data Cleaning in IOT
Testing over Different technologies
Transformation and Security over various Platform
Planning and Implementation

Machine Learing :

Need of Machine Learning
Introduction to Machine Learning
Types of Machine Learning, such as supervised, unsupervised and reinforcement learning, why Machine Learning with Python and applications of Machine Learning.
Introduction to supervised learning, types of supervised learning, such as regression and classification
Introduction to regression,
simple linear regression,
Multiple linear regression, assumptions in linear regression
Math behind linear regression.
Introduction to classification
Linear regression vs Logistic regression
Math behind logistic regression, detailed formulas, log it function and odds, confusion matrix and accuracy, true positive rate, false positive rate, and threshold evaluation with ROCR.
Introduction to tree-based classification
Understanding a decision tree, impurity function, entropy, to understand the concept of information gain for the right split of node, impurity function, information gain
Understand the concept of information gain for the right split of node, impurity function, Gini index, to understand the concept of Gini index for the right split of node, overfitting, pruning, pre-pruning, post-pruning, cost-complexity pruning
Introduction to ensemble techniques, understanding bagging, introduction to random forests, and finding the right number of trees in a random forest.
Introduction to probabilistic classifiers,
Understanding Naïve Bayes, math behind the Bayes theorem
Understanding a support vector machine (SVM)
Kernel functions in SVM, and math behind SVM.
Unsupervised Learning
Natural Language Processing and Text Mining
OS modules, Natural Language Toolkit (NLTK) environment

Python Programming and Cloud

Introduction :

Numbers: Operations, Types, and Variables
To Open a Jupyter Notebook
Python as a Calculator
Standard Math Operations
Basic Math Operations
Order of Operations
Spacing in Python
Number Types: Integers and Floats
Complex Number Types
Errors in Python

Variables :

Variable Assignment
Changing Types
Reassigning Variables in Terms of Themselves
Variable Names
Multiple Variables
Comments
Docstrings
Theorem in Python

Strings: Concatenation, Methods, and input() :

String Syntax
Escape Sequences with Quotes
Multi-Line Strings
The print() Function
String Operations and Concatenation
String Interpolation
Comma Separators
Format
The len() Function
String Methods
Casting
The input() Function
String Indexing and Slicing
Indexing
Slicing

Strings and Their Methods :

Booleans and Conditionals
Booleans
Logical Operators
Comparison Operators
Comparing Strings
Conditionals
The if Syntax
Indentation
if else
The elif Statement
Loops
The while Loops
An Infinite Loop
break
Programs
The for Loop
The continue Keyword

Python Structures :

The Power of Lists
List Methods
Accessing an Item from a List
Adding an Item to a List
Dictionary Keys and Values
a List and a Dictionary
Zipping and Unzipping Dictionaries Using zip()
Dictionary Methods
Tuples
A Survey of Sets
Set Operations
Choosing Types
Docstrings
Imports
The if __name__ == "__main__" Statement
Basic Functions
Positional Arguments
Keyword Arguments
Iterative Functions
Exiting Early
Activity 10: The Fibonacci Function with an Iteration
Helper Functions
Don't Repeat Yourself
Variable Scope
Variables
Defining inside versus outside a Function
The Global Keyword
The Nonlocal Keyword
Lambda Functions
Mapping with Lambda Functions
Filtering with Lambda Functions
Sorting with Lambda Functions