Savitribai Phule Pune University

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Advanced Course in Embedded System Design with AI

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  • Advanced Course in Embedded System Design with AI

Course Objective

Prepare students for an in-depth comprehensive knowledge of the underlying technologies like Electronics, Computer Science, Energy Conversion & Management, Automatic Controls, Telecommunications & Networks involved in embedded systems along with Artificial Intelligence by focussing both on practical and theoretical aspects. On the practical front, focus on developing system approach through integrated projects to master specific methods and tools applied in the aeronautics, space, automobiles, and multimedia domains.

Course Structure

  • Duration: 7 months (990 hours) full-time
  • Classes: Monday to Friday (Lecture: 2 hrs, Lab work: 5 hrs). Saturday will be available for additional lab work.
  • Industry standard project of 3 months duration will be an integral part of this course.

Eligibility

B.E/B.Tech (Electronics,E&TC, Instrumentation), M.Sc. (Electronics) or equivalent degree

Application Form & Entrance Exam Fee

Rs.500/- to be paid online
Account Name: ICIT PVT LTD
A/c no: 27205000514
IFSC Code: SCBL0036107
Bank: Aundh Branch, 163, Harsh Orchid, New DP Road, Nagras Road Mall, Ward no 8, Aundh, Pune 411007

Course Fee

Rs 97,000/-

This course fees is Non Refundable, To be Paid by Demand Draft drawn on any nationalized bank in favour of “ICIT Pvt. Ltd., Pune” and Payable at pune.

Admission Notification
Event Date
Last date of registration 10th October 2024
Online common entrance test 13th October 2024 and 14th October 2024
Commencement of course 5th November 2024

Reservation : As per rules of Government of Maharashtra.

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Course Syllabus

Pre-requisites: Basic understanding of computers and basic programming knowledge.

 

  • Introduction to GNU Toolchain, Linux environment, and VI editor
  • Overview of C Programming language
    • Tokens of C: Keywords, Data Types, Variables, Constants, Operators, Identifiers, Storage Class Specifiers
    • Control Flow Statements
    • GNU Make utility
    • Arrays, Multidimensional arrays, Data Input & Output, Strings, Loops (for, while, etc.)
    • Functions and Recursion
  • Pointers
    • Introduction
    • Pointer Arithmetic
    • Pointers and Arrays
    • Pointers and Functions
    • Pointers and Strings
    • Structures, Unions, Enum, Typedef, Bit field operators, and pointers with structures
    • Preprocessors
    • C and Assembly
    • Files, I/O
    • Variable number of arguments
    • Command Line arguments
    • Error handling and debugging with GNU GDB
  • Basics of Program Writing & Coding Practices
    • Debugging and Optimization of C programs
    • Bit operations
    • Handling portability issues in C
    • Hardware, Time, Space, and Power aware Programming
  • Introduction to Data Structures, Algorithms, and Abstract Data Types
    • Complexity of Algorithms
    • Linked Lists
    • Stacks
    • Queues
    • Searching and Sorting Algorithms
    • Hashing
    • Trees

Pre-requisites:

Basic understanding of an Operating System.

Embedded Operating System:

  • Introduction to Embedded Operating Systems
  • Anatomy of an Embedded Linux System: Bootloader, Kernel, Root File System, Application
  • Process Management
  • Interprocess Communication & Synchronization
  • Memory Management
  • I/O Sub-system & Embedded File Systems
  • POSIX Thread Programming
  • POSIX Semaphores, Mutexes, Conditional Variables, Barriers
  • Message Queues
  • Shared Memory
  • Debugging and Testing of Multithreaded Applications
  • Socket Programming

Embedded System Linux Device Drivers:

  • The Embedded Linux Software Eco-System
  • Linux Kernel Modules and Module Programming
  • Char Device Drivers
  • Kernel Internals: Dynamic Memory Allocations, Handling Delays, Timers, Synchronization, Locking, I/O Memory and Ports, Interrupts, Deferred Executions, Driver Debugging Techniques
  • USB Device Driver
  • Drivers for GPIO, I2C, and SPI

Real Time Operating System:

  • Introduction to Real-Time Concepts
  • RTOS Internals & Real-Time Scheduling
  • Performance Metrics of RTOS
  • Task Specifications
  • Schedulability Analysis
  • Application Programming on RTOS
  • Porting of RTOS
  • Configuring RTOS
  • Building RTOS Image for Target Platforms

Pre-requisites:

Must have knowledge of C++ Programming.

Overview:

  • Microcontrollers, Microprocessors, and SoC
  • RISC vs. CISC
  • Harvard vs. Princeton Architectures
  • Overview of Computer Architecture
  • Embedded Memories
  • Timers/Counters
  • UART, SPI, PWM, WDT
  • Input Capture, Output Compare Modes
  • I2C, CAN
  • LED, Switches
  • ADC, DAC
  • LCD, RTC
  • Bus Standards (USB, PCI)
  • Programming in Assembly and Embedded C
  • Overview of ARM Architecture and Organization
  • Introduction to Cortex-M Architecture
    • Programming Model and Instruction Set Architecture
    • Alignment and Endianness
    • Register Access, State, Privilege, Stack, System Control Block
    • Power Modes
    • Memory Model
    • NVIC
    • Exception Handling
    • Bit Banding
    • Peripheral Programming
    • SVCall, SysTick, PendSv, MPU, DMA
  • Mixing Assembly and C Programs
  • Introduction to CMSIS & CMSIS Components
  • Overview of Cortex A & R Architectures
  • Introduction to Multi-Core Embedded Systems
  • Introduction to FPGA

Pre-requisites:

Must have completed (Microcontroller Programming & Interfacing)

Programming Crash Course:

  • Python:
    • Basics
    • Loops
    • Blocks and Statements
    • Lists
    • Sets
    • File I/O
    • Modules and Functions
    • OOPs concepts
  • Keras:
    • Introduction
    • Installation and Configuration
  • TensorFlow:
    • Tensors
    • TensorFlow Installation
    • TensorFlow basics

Machine Learning:

  • Introduction
  • Supervised Machine Learning:
    • Data gathering
    • Data Cleaning
    • Data Labeling
    • Build ML models using Python
    • Training and Testing the models
    • Algorithms:
      • Linear and Nonlinear classification
      • Regression Techniques
      • Decision Trees
      • Oblique trees
      • Random Forest
      • Bayesian analysis and Naive Bayes classifier
      • Algorithm Performance
  • Unsupervised Machine Learning
  • Text Classification using Python and NLTK / Naive Bayes

Deep Learning:

  • Introduction to Neural Networks:
    • Deep Neural Networks
    • Perceptrons
    • RNN, CNN, LSTM
    • Deep Belief Network
    • Semantic Hashing
    • Building Deep Learning Models / Neural Networks using Keras and TensorFlow
    • Testing and Training the models
  • Convolutional Neural Networks

AI in Automobile Industry:

  • Introduction
  • Applications of AI in Automobile Industry:
    • Computer Vision
    • NLP
    • Autonomous Driving
    • Sensors
    • Cameras
    • Gathering and Processing Data from Devices / Sensors
    • Vehicle Control Systems
    • Decision Making
    • Automatic Navigation

Pre-requisites:

Must have completed (C++ Programming and Data Structure Algorithm), (Embedded OS, Linux Device Drivers, & RT Linux), (Microcontroller Programming & Interfacing), and (Embedded System Hardware Design & Project).

Introduction to Model-Based Development:

  • Model Creation using Simulink
  • Stateflow
  • Control Systems in Automotive Engineering
  • Requirements Analysis and System Design
  • Model Design Technique
  • Optimization and Code Generation for Automotive Embedded Systems
  • MIL Testing
  • SIL Testing
  • Modified Condition/Decision Coverage

Pre-requisites:

Must have completed any 4 Certificates of CCDESD101 to 105

Study of Data Sheets:

  • Hardware device interface with Microcontroller will require studying data sheets of the device
  • Selection of components
  • Power supply design

Microcontroller-Based Application:

  • Hardware design as per specification

Study of Automotive Protocols:

  • CAN, LIN in detail and implementation

Introduction to MATLAB:

  • Model development
  • SIMULINK

Case Study:

  • Standard chips such as:
    • RTC chip DS1307
    • EEPROM 24LC256
    • Temperature Sensor TC74
    • Based on I2C, SPI protocols