Python

Python

(301 reviews)
Python

Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace. It provides constructs that enable clear programming on both small and large scales. In July 2018, Van Rossum stepped down as the leader in the language community after 30 years. Python features a dynamic type system and automatic memory management. It supports multiple programming paradigms, including object-oriented, imperative, functional and procedural, and has a large and comprehensive standard library. Python interpreters are available for many operating systems. CPython, the reference implementation of Python, is open source software and has a community-based development model, as do nearly all of Python's other implementations. Python and CPython are managed by the non-profit Python Software Foundation.

Course Features

  • Students 301
  • Duration4/6 week
  • Skill levelall
  • LanguageEnglish
    • DAY

      DESCRIPTION

       OBJECTIVES

      DEMO

      Da1- Theory

      Day2-coding practices

       

      Introduction to Python

      • Overview of Python

      • Companies using Python

      • Other applications in which Python is used

      • Discuss Python Scripts on UNIX/Windows

      • Variables

      • Operands and Expressions

      • Conditional Statements

      • Loops

      • Command Line Arguments

      • Writing to the screen

       

       

      • Define Python

      • Understand the need for Programming

      • Know why to choose Python over other languages

      • Setup Python environment

      • Understand Various Python concepts – Variables, Data Types Operators, Conditional Statements and Loops

      • Illustrate String formatting

      • Understand Command Line Parameters and Flow control

       

       

      • Creating “Hello World” code

      • Variables

      • Demonstrating Conditional Statements

      • Demonstrating Loops

       

       

      Day3- Theory

      Day4-coding practices

      Day5-coding practices

       

      Sequences and File Operations

      • Python files I/O Functions

      • Lists and related operations

      • Tuples and related operations

      • Strings and related operations

      • Sets and related operations

      • Dictionaries and related operations

       

      • Understand Operations performed on Files

      • Learn what Sequences are

      • Execute Sequence Operations

      • Understand Types of Sequences in Python: Lists, Tuples, Strings, Sets, Dictionaries

      • Tuple - properties, related operations, compared with a list

      • List - properties, related operations

      • Dictionary - properties, related operations

      • Set - properties, related operations

       

      Day6- Theory

      Day7-coding practices

      Day8-coding practices

      Deep Dive – Functions and OOPs

      • Functions

      • Function Parameters

      • Global variables

      • Variable scope and Returning Values

      • Lambda Functions

      • Object-Oriented Concepts

       

       

       

      • Define and call Functions

      • Understand why the return statement is used

      • Understand and execute Object-Oriented Concepts

      • 

       

      • Functions - syntax, arguments, keyword arguments, return values

      • Lambda - features, syntax, options, compared with the functions

       

      Day9- Theory

      Day10-coding practices

      Day11-coding practices

       

      Working with Modules and Handling Exceptions

       

      • Use Standard Libraries

      • Use Modules

      • Understand Exception Handling

      • Create User Defined Exceptions

       

       

       

       

       

      • Standard Libraries

      • Modules Used in Python (OS, Sys, Date and Time etc.)

      • The Import statements

      • Module search path

      • Package installation ways

      • Errors and Exception Handling

      • Handling multiple exceptions

       

       

      • Errors and exceptions - types of issues, remediation

      • Packages and module - modules, import options, sys path

       

      Day12- Theory & installation

      Day13-Theory & coding practices

      Day14-coding practices

      Introduction to NumPy & Pandas

      NumPy - arrays

      Operations on arrays

      Indexing slicing and iterating

      Reading and writing arrays on files

      Pandas - data structures & index operations

      Reading and Writing data from Excel/CSV formats into Pandas

       

       

       

      • Create arrays using NumPy

      • Use NumPy to perform mathematical operations on arrays

      • Read and write data from text/CSV files into arrays and vice-versa

      • Understand Pandas and employ it for data manipulation

      • Understand and use the data structures available in Pandas

      • Read and write data between files and

       

      • NumPy library- Installation, Creating NumPy array, operations performed on NumPy array

      • Pandas library- Installation, creating series and data frames, Importing and exporting data

       

      Day15- Theory & installation

      Day16-Theory & coding practices

      Day17-coding practices

      Data Visualisation

      matplotlib library

      Grids, axes, plots

      Markers, colours, fonts and styling

      Types of plots - bar graphs, pie charts, histograms

      Contour plots

       

       

      • Create simple plots like scatter plot, histogram, bar graph, pie chart using Matplotlib

      • Add different styles to the plot

      • Use the different forms of plots available in Matplotlib

       

      • Matplotlib - Installation, Using Scatterplot, histogram, bar graph, pie chart to show information, Styling of Plot

       

      Day18- Theory

      Day19-Theory & coding practices

      Day20-coding practices

      Data Manipulation

      Basic Functionalities of a data object

      Merging of Data objects

      Concatenation of data objects

      Types of Joins on data objects

      Exploring a Dataset

      Analyzing a dataset

       

       

       

      • Perform function manipulations on Data objects

      • Perform Concatenation, Merging and Joining on DataFrames

      • Iterate through DataFrames

      • Explore Datasets and extract insights from it

       

       

      • Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples(), GroupBy operations, Aggregation, Concatenation, Merging and joining

      Day21- Theory

      Day22- coding practices

      Day23-coding practices

      GUI Programming

      Ipywidgets package

      Numeric Widgets

      Boolean Widgets

      Selection Widgets

      String Widgets

      Date Picker

      Color Picker

      Container Widgets

      Creating a GUI Application

       

       

      • Learn ipywidgets package

      • Understand different widgets like Numeric Widgets, Boolean Widgets, Selection Widgets, String Widgets, Date Picker, Color Picker and Container Widgets

      • Create an application using ipywidgets package

       

       

      • Create GUI

       

      Day24- Theory

      Day25-coding practices

       

       

      Network Programming and Multithreading 

       

      MySQL DB access

      Network programming

      Multithreading

       

       

       

      • Understand the concept of Database

      • Access MySQL DB

      • Create socket for sending short messages

      • Learn Multithreading concepts

       

       

      • Database Creation

      • CRUD Operations

      • Network Creation

      • Multithreading

       

      Day26- Theory

      Day27-coding practices

       

      Developing Web Maps and Representing information using Plots

       

      Use of Folium Library

      Use of Pandas Library

      Flowchart of Web Map application

      Developing Web Map using Folium and Pandas

      Reading information from Dataset and represent it using Plots

       

       

      • Design a Web Map using Folium and Pandas for displaying Volcanoes in USA and Population in different countries in a Single map Represent information from Dataset with the help of Plots

       

       

      Day28- Theory

      Day29-coding practices

      Day30-coding practices

       

       

       

      Computer vision using OpenCV and Visualisation using Bokeh

      Beautiful Soup Library

      Requests Library

      Scrap all hyperlinks from a webpage, using Beautiful Soup & Requests

      Plotting charts using Bokeh

      Plotting scatterplots using Bokeh

      Image Editing using OpenCV

      Face detection using OpenCV

      Motion Detection and Capturing Video

       

      • Perform Web Scraping using Python

      • Visualise Data on the browser using Bokeh

      • Use OpenCV to create a motion detection software

       

       

      Day32- Theory

      Day33- Theory

      Day34-algorithms practices

       

       

      Introduction to Machine Learning with Python

      Python Revision (numpy, Pandas, scikit learn, matplotlib)• 

      • What is Machine Learning?

      • Machine Learning Use-Cases

      • Machine Learning Process Flow

      • Machine Learning Categories

      • Linear regression

      • Gradient descent

       

       

       

      • Essential Python Revision

      • Necessary Machine Learning Python libraries

      • Define Machine Learning

      • Discuss Machine Learning Use cases

      • List the categories of Machine Learning

      • Illustrate Supervised Learning Algorithms

      • Identify and recognize machine learning algorithms around us

      • Understand the various elements of machine learning algorithm like parameters, hyper parameters, loss function and optimization.

       

       

      • Linear Regression – Using Boston Dataset

      Last 11 Days participants will guided in the projects

      Case Study 1

      Domain: Marketing

      Statement: Bank of Portugal runs a marketing campaign to offer loans to clients.  Loan is offered to only clients with particular professions. 

      List of successful campaigns (with client data) is given in attached dataset. 

      You have to come up with a program which reads the file and builds a set of unique profession list and given, input profession of client – system tells whether the client is eligible to be approached for marketing campaign.

       

      Case Study 2

      Domain: E-Commerce

      Statement: GoodsKart—largest e-commerce company in Indonesia with revenue of $2B+ acquired another ecommerce company FairDeal.  FairDeal has its own IT system to maintain records of customer, sales etc.

      For ease of maintenance and cost savings GoodsKart is integrating customer databases of both the organizations, hence customer data of FairDeal has to be converted in GoodsKart Customer Format.

       

      Case Study 3

      Domain: Education

      Statement: You are a data analyst with University of California, USA

      University has data of Math, Physics and Data Structure score of sophomore students. This data is stored in different files. 

      University has hired a data science company to do analysis of scores and find if there is any correlation of score with age, ethnicity etc. Before the data is given to the company you have to do data wrangling.

       

      Case Study 4

      Domain: Retail

      Statement: BigMart is one of the biggest retailer in Europe and has operations across multiple countries. 

      You are a data analyst in IT team of BigMart. Invoice and SKU wise Sales Data for Year 2011 is shared with you. You need to be prepared meaningful charts to show case the various sales trends for 2011 to top management. 

       

      Case Study 5

      Domain: Human Resource

      Statement: SFO Public Department - referred to as SFO has captured all the salary data of its employees from year 2011-2014.  Now we are in year 2015 and the organization is facing some financial crisis. As a first step HR wants to rationalize employee cost to save payroll budget.

      You have to do data manipulation and analysis on the salary data to answer specific questions for cost savings.

       

      Case Study 6

      Domain: Government

      Statement: You are a data analyst in SanFrancisco(SFO) City IT Department.  SFO Police has shared crime data for year 2016.  Data contains various incidents which have happened throughout the year, along with the geolocation of the crime.

      You need to prepare effective webmaps to analyze and present the data.  SFO Commissioner of Police will reassign the forces based on the density of various crime

Course Name: Python with Machine Learning


Student

8,500

6000

14,500

Professional

9,500

6,500

16,000


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2. After successful payment our team member will contact you within 3 hours.

Certification:

All participants will get ISO certified Certificate of the course from Teach Tech Services in association with iSmriti, IIT Kanpur

This certificate is globally accepted.

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JALANDHAR (LPU CMAPUS)

Address :Jalandhar - Delhi G.T. Road, Phagwara, Punjab 144411

Phone : +91-9023647226

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