Value Added Courses

PHCET > Academics > Other Programs > Value Added Courses

Electrical Engineering


Introduction to PSpice and LTspice and Its Application

Course ContentCourse Summary
Topic Contents
Introduction to PSpice and LTspiceAn outline of Pspice, Types of Analysis in Pspice
Getting statring with PSpice and LTspiceDC simulation, PSpice Component Layout, DC Bias Simulation ,Linear Resistance ,Non-Linear Resistance Operating Point, Markers, Parametric DC Sweep Thévenin and Norton Equivalents
AC SimulationsAC Inputs, Time Domain (transient analysis), AC Sweep Analysis
Solar cell and Module simulation for STCSolar cell modelling and simulation analysis

Course Title

Introduction to PSpice and LTspice and Its Application

Course Outcome

  • Student can acquire experience in designing electronic circuits to perform real task
  • Student can understand what is PSPICE or LTSPICE and its use in industrial application
  • Student knows how to simulate a circuit using a PSPICE or LTSPICE simulator.
  • Student can demonstrate how to simulate an actual circuit using a PSPICE or LTSPICE in laboratory setting
  • Students can able to conduct circuit analysis using a PSPICE or LTSPICE circuit simulator
  • Student can able to apply acquire for various application

Class

BE/TE – Electrical Engineering

Duration

15 hrs

Course Fees

Free

Course Instructor

Ms. Asokan Selvaraj
aselvaraj@mes.ac.in


PCB Designing

Course ContentCourse Summary
Topic Contents
Overview of PCB DesigningDefinition and Need/Relevance of PCB, Background and History of PCB
Basics of PCB Designing: Types of PCB, Layering of PCBTypes of PCB, Classes of PCB Design, Terminology in PCB Design
PCB-CAD tools: DipTrace, Eagle, AltiumDifferent Electronic design automation (EDA) tools , Introduction to DipTrace, Eagle and Altium Environment, Latest Trends in Market
Electronic and Semiconductor Component package typesDifferent types of electronic components, Electronic components according to their size, power-ratings, package style and placements
Practical ImplementationSteps involved in fabrication of PCB. PCB Fabrication techniques-single, double sided and multilayer, Auto routing, Drilling, Etching: chemical principles and mechanisms, Post operations- stripping, black oxide coating and solder masking, PCB component assembly processes
Fundamental and real world projectDesign and fabricate PCB for any one project, mount the components, testing and troubleshooting methods

Course Title

PCB Designing

Course Outcome

  • Students can learn various types of PCBs. Schematic Design. entry Rules for Schematic Entry, Component Layout methods
  • Students can design and fabricate their own PCB for their Project

Class

BE/TE – Electrical Engineering

Duration

15 hrs

Course Fees

Free

Course Instructor

Ms. Supriya Sunil Shigwan
sshigwan@mes.ac.in

Ms. Ronita Pawn
ronita@mes.ac.in


Introduction to MATLAB and Its Application

Course ContentCourse Summary
Topic Contents
Starting with MATLAB Starting MATLAB, MATLAB windows
Working in the command window
Arithmetic operations with Scalars
Using MATLAB as a calculator
Creating Arrays Creating a one-dimensional array (vector), Creating a two-dimensional array (matrix) Addition and subtraction with arrays Array multiplication and array division
Applications in Numerical Analysis Numerical analysis
Solving an equation with one variable
finding a minimum or a maximum of a function examples of MATLAB applications
Applications in Control System Plotting bode plots using MATLAB plotting root locus using MATLAB
Applications in Power System and power Electronics Introduction to SIMULINK toolbox
Simpower system
Developing Simulation models of power system and Power electronics examples

Course Title

Introduction to MATLAB and Its Application

Course Outcome

  • To improve employability skills of engineering students
  • To bridge the skill gaps and make students industry ready.
  • Student can able to generate plots and export this for use in reports and presentations.
  • Student can able to program scripts and functions using the Matlab development environment.
  • Student can able to understand various toolboxes and their application in various domains
  • Student can able to model and simulate system to analysis its performance.

Class

BE/TE – Electrical Engineering

Duration

15 hrs

Course Fees

Free

Course Instructor

Ms. Lakshmi C R
crlakshmi@mes.ac.in
Ms. Pranita Chavan
pranitachavan@mes.ac.in


Information Technology


UIUX Jumpstarter Course

Course ContentCourse Summary
Topic Contents
Introduction to UX

  • Introduction to User Experience

  • Definition and concept Evolution of UX

  • UX around us Class activity UX Trends (Personalization, gestures, white interfaces.) Emerging Technologies AR VR AI IOT Misconception about UX

  • 6D process

The 6D UX Process

  • Introduction and Definition 6D process for a great User Experience

  • The 6D Steps explained Why use 6D?

  • Competitor Analysis Case Study Class Studio OLX , NETFLIX, DUNZO

Heuristic Evaluation

  • Introduction & Definition 10 Laws of Heuristic Evaluation

  • Case Study - Google pay Case Study - Uber Case Study - Gmail Class Studio

Introduction to Visual Design Tools 1

  • What is Photoshop? Examples of UI

  • What is Illustrator?

  • What are Vector Images What are Raster Images Difference between Vector & Raster Images Shapes and Images Icons/Graphics/Illustration Adobe XD

  • Overview Class Studio
User Research- 1&2

  • Definition and Concept Benefits of User Research

  • Elements of User Research

  • User Research Process

  • User Research Methodologies

  • User Interviews

  • Recap of User Research Class Studio

  • Research Execution Create User Interview Questionnaire Class activity

  • Conduct & observe user interviews

  • Analyse findings

  • Create a Persona & an Empathy Map Value proposition canvas - Introduction Create a Customer Journey

  • User Research Report Class Studio
Persona, Scenario & Storyboard

  • What are Personas?

  • How to create Personas Benefits of Persona (Who uses persona) Class Studio What is Scenario?

  • How to create Scenario Importance of Scenario

  • What is a Storyboard? How do we create Storyboard?

  • Importance of Storyboard Class Studio
Customer Journey Mapping

  • What is Customer Journey Mapping?

  • Benefits of Customer Journey Mapping

  • Components of a Customer Journey map

  • Mapping the right journey

  • Case study Class Studio
Task Flow Analysis

  • Introduction to Task Flow Hierarchical and Linear methods

  • Introduction to User Flow

  • Task Flow Vs User Flow

  • Example of Task Flow Analysis

  • Class Studio

Information Architecture

  • What is Information Architecture?

  • What are IA Patterns - L.A.T.C.H Open and Closed Card Sorting

  • Class Studio - Card Sorting Activity
Wireframing and Prototyping

  • What is a Wireframe?

  • Why should I use wireframes?

  • How to use wireframes

  • Different types of wireframes Digital & Non-Digital methods

  • Low & High-fidelity wireframes

  • Intro to UI design patterns Responsive Design Class studio: Make paper wireframes & digitalise them
Design Specifications & Assets

  • Definition and Concept Working on IOS and Android Iconography and Typography Working with specifications & assets

  • Atomic Design - Introduction Native apps Working with GUI kits

Portfolio Evaluation-

Course Title

UX JUMPSTARTER COURSE

Course Outcome

UX aims to provide a clear design and structure to the product, which guides the user throughout the journey of using the product and creates a sense of satisfaction on having completed a task at ease. UX is highly dynamic as it changes with every product. Each product has its own unique set of requirements.

Eligibility

All IT and Computer students

Duration

4 weeks

Course Fees

Free of cost

Course Instructor

Ms. Kajal Patel
kajalpatel@mes.ac.in


EXTC Engineering


Python for Data Science and Machine Learning

Course ContentCourse Summary
Topic Contents
Introduction to AI, ML and Data Science, PythonIntroduction to Data Science, AI and Machine learning and its applications, Examples of AI, Data Science applications in various
engineering disciplines
Introduction to Python, features of Python, Installation, Installing python Packages
Data TypesInteger, Float and Complex- Number Functions (Number Type Functions, Maths Functions, Random Number functions, Trigonometric Functions)
Operators in PythonArithmetic, Assignment, Comparison, Boolean values, Logical, identity, bitwise and membership operators, Shift operators
Data Structures: Lists, Tuples, DictionaryOperations on lists- Append, remove, slicing, insert, pop, reverse, len, count etc,
Operations on Tuples and Dictionary
Decision Flow Control Statementsif, if and else statement, Nested If, While, do and while, for, Continue, Break and pass etc
Functions and File HandlingDefining and calling the functions, return statements, Passing the arguments, Lambda Functions
Recursive functions, Modules and importing packages in python code
File Input/Output: Files I/O operations, Read/Write Operations, File Opening Modes, with keywords, moving within a file, Manipulating files
Numpy, Pandas, Matplotlib, Seaborn, Scipy Libraries:Introduction to Numpy, Creating and Printing Ndaray, Class and Attributes of Ndarray, Basic operation, Copy and view, Mathematical Functions of Numpy.
Introduction to Pandas, Understanding Dataframe, View and Select Data,
Missing Values, Data Operations, File read and write operation.
Introduction to Matplotlib library, Line properties, Plots and subplots, Types of Plots, Introduction to Seaborn.
Introduction to Scipy, Scipy Sub packages Integration and Optimization,
Eigen values and Eigen Vectors, Statistic, Weave and IO.
Graphical User Interface and Image processingGraphical User Interface using Tkinter Library module, creating simple GUI; Buttons, Labels, entry fields, widget attributes
DatabasesSqilite database connection, Create, Append, update, delete records from database using GUI. Basic Image Processing using OpenCV library, simple image manipulation using the image module
Machine Learning Algorithms:Supervised, Unsupervised, Reinforcement Learning, Case Studies, Deep Learning examples, Case Studies
Regression, Classification, Types of classifiersKNN, SVM, Decision Tree, Bayes etc, Case Studies

Course Title

Python for Data Science and Machine Learning

Course Outcome

After the successful completion of the course, students must be able to:

  • Learn about Python fundamentals, Python data structures, and working with data in Python
  • Become familiar with key Python functions, objects, and classes
  • Develop data science and ML applications using Python
  • Gain career skills in one of the world’s most popular programming languages

Eligibility

Any students with basic understanding of programming

Duration

Min 35 hours

Course Fees

Nil

Course Instructor

Dr. Mansi Subhedar
msubhedar@mes.ac.in
Ms. Pooja Shukre
pshukre@mes.ac.in


Mechanical and Automobile Engineering


Solidworks Mechanical Design – Associate Level Certification Course (CSWA)