Python

Python
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About The Python Training With ProICT Training

In 2014, Python was discovered to be typically the most popular language for teaching information technology courses to beginners at leading US colleges. Almost eight from ten Information Technology departments and 27 from the top 39 were discovered to be teaching Python in the opening level.

Because of the truth that it is among the easiest programming languages to understand, Python continues to be gaining recognition and can end up being the programming language preferred by both of these individuals and enterprises moving forward. Today, a lot of organizations are moving and transitioning to Python. Google, for example, has lots of engineers who’re using Python and the team is continually searching for those who have skills within the language. Python courses will acquaint the country’s students with this particular simple language. Such Python classes may also help India’s young individuals to enhance their employability quotient and job worthiness on the market.

About ProICT

Who are we? ProICT LLC is a registered online training provider found and led by the group of IT working professionals and experts. Our trainers are not only highly experienced and knowledgeable but also current IT working Professionals leading IT companies in USA, UK, Canada and other countries. We are ready to share our knowledge and years of working experience with other professionals to assist and guide them get ahead in career.

What is Python Programming?

Object-oriented programming can be done with Python, a PC language that is gaining attraction and carving a distinct segment by itself within the high-end computing space.  Python may be the language for online hackers, a forensic analyst and transmission testers. It is a pure object-oriented and minimalistic style, simple to learn with a simple syntax. Most Python programs run unchanged on all the leading computer platforms including Home Windows, Linux, Mac, etc.

The Python Standard Library is significant. The majority of the security, hacking and forensic tools are written in Python. Python may be the language that must be learned because of it Security professionals. Python continues to be among the premier, flexible, and useful open-source language that’s simple to learn, simple to use, and it has adequate libraries for data manipulation and analysis. This program covers both fundamental and advanced concepts of Python like writing Python scripts, sequence and file operations in Python, Machine Learning in Python, Web Scraping, etc.

 

Challenges in Python Programming

These challenges shouldn’t be attempted until you’re comfortable using Python, petite help will be presented using the solutions. You need to design, code and test as always.

Variable Length Banner

Right at the beginning of these tutorials, we authored what you’d most likely now say is a simple program to print a banner of someone’s name.

Mastermind

The gamer enters four figures, and also the computer informs the player the number of (although not which) from the four numbers are correct.

Average Calculator

Only to clarify, you aren’t developing a standard calculator, however, a program for calculating averages.

The consumer will be able to enter some figures, and also the program should print the typical of those numbers. You should use floating point number variables, or keep input inside a list.

Your program might be employed to calculate average temperatures for any week, or perhaps a batting average for any cricket team, amongst others. You can even expand this program to print the mean, median and mode averages.

Email Validator

When registering online, you sometimes have to provide a valid current email address. If your user enters an invalid current email address, the website should alert the consumer to their mistake, and never permit them to register until it’s remedied.

Write a course to allow the consumer know if the current email address they joined was valid or invalid.

Bingo!

You need to produce a program to show a bingo board beginning with ten at randomly selected figures

Password Reset Program

Students will be able to make use of this program to alter their password towards the school network.

Color Ripper tools

When creating websites, just one way of considering different colors is as simple as their ‘RGB’ values.

Who should enroll for this course?

Python is a straightforward programming language for novices to start. It’s newer than other programming languages, so it’s simpler to understand than a few of the older languages. The Python team fixed many of the things they found that suck in ancient languages, there’s lots of interest in Python programmers. And the average Python developer salary in America is $102,000 based on Indeed.com. Thi is just an indication you may perform some impressive things with Python from data science to building websites. These could lead you to path breaking mind-boggling salary you never even imagined. Some great sites built on Python are:

YouTube

Quora

Disqus

Instagram

Pinterest

Google

DropBox

Trulia

Reddit

Mozilla

NASA

Survey Monkey

So, why left behind, join ProICT Training and lead the world with your own product and site that just rocks.

Pre-requisite:

A dedication and interest are all you need to get started. But a programming background will always help. Although you don’t need to know C to start it but knowing it would always help you. As far degrees are concerned,  knowledge is valued more than degrees. So, learn to be a professional python developer which will help to build a career


  • About the Tutorial
  • Audience
  • Prerequisites
  • Disclaimer & Copyright
  • Table of Contents

1. OVERVIEW

  • History of Python
  • Python Features

2. ENVIRONMENT3

  • Local Environment Setup
  • Getting Python
  • Installing Python
  • Setting up PATH
  • Setting path at Unix/Linux
  • Setting path at Windows
  • Python Environment Variables
  • Running Python

3. BASIC SYNTAX

  • First Python Program
  • Python Identifiers
  • Python Keywords
  • Lines and Indentation
  • Multi-Line Statements
  • Quotation in Python
  • Comments in Python
    • Using Blank Lines
    • Waiting for the User
    • Multiple Statements on a Single Line
    • Multiple Statement Groups as Suites
    • Command Line Arguments
    • Accessing Command-Line Arguments
    • Parsing Command-Line Arguments
    • getopt.getopt method
    • Exception getopt.GetoptError:

    4. VARIABLE TYPES

    • Assigning Values to Variables
    • Multiple Assignment
    • Standard Data Types
    • Python Numbers
    • Python Strings
    • Python Lists
    • Python Tuples
    • Python Dictionary
    • Data Type Conversion

    5 BASIC OPERATORS

    • Types of Operators
    • Python Arithmetic Operators
    • Python Comparison Operators
    • Python Assignment Operators
    • Python Bitwise Operators
    • Python Logical Operators
      • Python Membership Operators
      • Python Identity Operators
      • Python Operators Precedence

      6. DECISION MAKING

      • If Statement
      • If…else Statement
      • The elif Statement
      • Single Statement Suites

      7. LOOPS

      • While Loop
      • The Infinite Loop
      • Using else Statement with Loops
      • Single Statement Suites
      • For Loop
      • Iterating by Sequence Index
      • Using else Statement with Loops
      • Nested Loops
      • Loop Control Statements
      • Break Statement
      • Continue Statement
      • Pass Statement

      8. NUMBERS

      • Number Type Conversion
      • Random Number Functions
      • Trigonometric Functions
      • Mathematical Constants

        9. STRINGS

        • Accessing Values in Strings
        • Updating Strings
        • Escape Characters
        • String Special Operators
        • String Formatting Operator
        • Triple Quotes
        • Unicode String
        • Built-in String Methods

        10. LISTS

        • Python Lists
        • Accessing Values in Lists
        • Updating Lists
        • Deleting List Elements
        • Basic List Operations
        • Indexing, Slicing, and Matrixes
        • Built-in List Functions and Methods

        11. TUPLES

        • Accessing Values in Tuples
        • Updating Tuples
        • Deleting Tuple Elements
        • Basic Tuples Operations
        • Indexing, Slicing, and Matrixes
        • No Enclosing Delimiters:
        • Built-in Tuple Functions
        • Accessing Values in Dictionary
        • Updating Dictionary
        • Delete Dictionary Elements
        • Properties of Dictionary Keys
        • Built-in Dictionary Functions and Methods

        13. DATE AND TIME

        • What is Tick?
        • What is TimeTuple?
        • Getting Current Time
        • Getting Formatted Time
        • Getting Calendar for a Month
        • The time Module
        • The calendar Module
        • Other Modules and Functions

        14. FUNCTIONS

        • Defining a Function
        • Calling a Function
        • Passing by Reference Versus Passing by Value
        • Function Arguments
        • Required Arguments
        • Keyword Arguments
        • Default Arguments
        • Variable Length Arguments
        • The Anonymous Functions
        • The return Statement
        • Scope of Variables
          • Global vs. Local variables:

          15. MODULES

          • The import Statement
          • The from
          • . import Statement
            • The from
            • . import * Statement:
              • Locating Modules:
              • The PYTHONPATH Variable
              • Namespaces and Scoping
              • The dir( ) Function
              • The globals() and locals() Functions
              • The reload() Function
              • Packages in Python

              16. FILES I/O

              • Printing to the Screen
              • Reading Keyboard Input
              • The raw_input Function
              • The input Function
              • Opening and Closing Files
              • The open Function
              • The file Object Attributes
              • The close() Method
              • Reading and Writing Files
              • The write() Method
              • The read() Method
              • File Positions

              Renaming and Deleting Files

            • The rename() Method
            • The remove() Method
            • Directories in Python
            • The mkdir() Method
            • The chdir() Method
            • The getcwd() Method
            • The rmdir() Method
            • File and Directory Related Methods

            17. EXCEPTIONS

            • What is Exception?
            • Handling an Exception
            • The except Clause with No Exceptions
            • The except Clause with Multiple Exceptions
            • The try-finally Clause
            • Argument of an Exception
            • Raising an Exception
            • User-Defined Exceptions

            18. CLASSES AND OBJECTS

            • Overview of OOP Terminology
            • Creating Classes
            • Creating Instance Objects
            • Accessing Attributes
            • Built-In Class Attributes
            • Destroying Objects (Garbage Collection)
            • Class Inheritance

About the Python Certification Course

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. 
 
Proict's Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds. 
 
Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.
 
Proict’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master the concepts like Python machine learning, scripts, and sequence.
 

Why Learn Python?

It's continued to be a favourite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half   with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger. 

It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.

It has evolved as the most preferred Language for Data Analytics and the increasing search trends on Python also indicates that it is the " Next Big Thing " and a must for Professionals in the Data Analytics domain.

Read more on Top 10 reasons to learn Python

What are the objectives of our Python Certification Course?

After completing this Data Science Certification training, you will be able to:

 

  • Programmatically download and analyze data
  • Learn techniques to deal with different types of data – ordinal, categorical, encoding
  • Learn data visualization
  • Using I python notebooks, master the art of presenting step by step data analysis
  • Gain insight into the 'Roles' played by a Machine Learning Engineer
  • Describe Machine Learning
  • Work with real-time data
  • Learn tools and techniques for predictive modeling
  • Discuss Machine Learning algorithms and their implementation
  • Validate Machine Learning algorithms
  • Explain Time Series and its related concepts
  • Perform Text Mining and Sentimental analysis
  • Gain expertise to handle business in future, living the present

Who should go for this Python Data Science Certification Course?

Proict’s Data Science certification course in Python is a good fit for the below professionals:

 

  • Programmers, Developers, Technical Leads, Architects
  • Developers aspiring to be a ‘Machine Learning Engineer'
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Machine Learning (ML) Techniques
  • Information Architects who want to gain expertise in Predictive Analytics
  • 'Python' professionals who want to design automatic predictive models

What are the prerequisites for this Python Course?

The pre-requisites for Proict's Python course include the basic understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, you will be provided with complimentary “Python Statistics for Data Science” as a self-paced course once you enroll for the course.

How will I execute practical’s in Edureka's Python Certification Course?

You will do your Assignments/Case Studies using Jupyter Notebook that is already installed on your Cloud Lab environment whose access details will be available on your LMS. You will be accessing your Cloud Lab environment from a browser. For any doubt, the 24*7 support team will promptly assist you.

What is CloudLab?

CloudLab is a cloud-based Jupyter Notebook which is pre-installed with Python packages on the cloud-lab environment. It is offered by Edureka as a part of Python Certification Course where you can execute all the in-class demos and work on real-life projects in a fluent manner.
 
You’ll be able to access the CloudLab via your browser which requires minimal hardware configuration. In case, you get stuck in any step, our support ninja team is ready to assist 24x7.

Which case studies will be a part of this Python Certification Course ?

This course comprises of 40 case studies that will enrich your learning experience. In addition, we also have 4 Projects that will enhance your implementation skills. Below are few case studies, which are part of this course:
 
Case Study 1: Maple Leaves Ltd is a start-up company which makes herbs from different types of plants and its leaves. Currently, the system they use to classify the trees which they import in a batch is quite manual. A laborer from his experience decides the leaf type and subtype of plant family. They have asked us to automate this process and remove any manual intervention from this process.
 
You have to classify the plant leaves by various classifiers from different metrics of the leaves and to choose the best classifier for future reference.
 
 
Case Study 2: BookRent is the largest online and offline book rental chain in India.  The company charges a fixed fee per month plus rental per book. So, the company makes more money when user rents more books. 
 
You as an ML expert and must model recommendation engine so that user gets a recommendation of books based on the behavior of similar users. This will ensure that users are renting books based on their individual taste. 
The company is still unprofitable and is looking to improve both revenue and profit. Compare the Error using two approaches – User Based Vs  Item Based
 
 
Case Study 3:  Handle missing values and fit a decision tree and compare its accuracy with random forest classifier.
 
Predict the survival of a horse based on various observed medical conditions. Load the data from ‘horses.csv’ and observe whether it contains missing values. Replace the missing values by the most frequent value in each column. Fit a decision tree classifier and observe the accuracy. Fit a random forest classifier and observe the accuracy.
 
Case Study 4:  Principal component analysis using scikit learn.
             
Load the digits dataset from sklearn and write a helper function to plot the image. Fit a logistic regression model and observe the accuracy.
Using scikit learn perform a PCA transformation such that the transformed dataset can explain 95% of the variance in the original dataset. Compare it with a model and also comment on the accuracy. Compute the confusion matrix and count the number of instances that have gone wrong. For each of the wrong sample, plot the digit along with the predicted and original label.
 
Case Study 5:  Read the datafile “letterCG.data” and set all the numerical attributes as features. Split the data in to train and test sets. 
 
Fit a sequence of AdaBoostClassifier with varying number of weak learners ranging from 1 to 16, keeping the max_depth as 1. Plot the accuracy on the test set against the number of weak learners, using decision tree classifier as the base classifier.
 

Which kind of projects will be a part of this Python Certification Course?

Project #1:

Industry: Social Media

Problem Statement: You as ML expert have to do analysis and modeling to predict the number of shares of an article given the input parameters.

Actions to be performed:

Load the corresponding dataset. Perform data wrangling, visualization of the data and detect the outliers, if any. Use the plotly library in Python to draw useful insights out of data. Perform regression modeling on the dataset as well as decision tree regressor to achieve your Learning Objectives. Also, use scaling processes, PCA along with boosting techniques to optimize your model to the fullest.

 

Project #2: 

Industry: FMCG

Problem Statement: You as an ML expert have to cluster the countries based on various sales data provided to you across years.

Actions to be performed:

You have to apply an unsupervised learning technique like K means or Hierarchical clustering so as to get the final solution. But before that, you have to bring the exports (in tons) of all countries down to the same scale across years. Plus, as this solution needs to be repeatable you will have to do PCA so as to get the principal components which explain the max variance.

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What if I miss a class?

You will never miss a lecture at proict! You can choose either of the two options:
  • View the recorded session of the class available in your LMS.
  • You can attend the missed session, in any other live batch.

Will I get placement assistance?

To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.

Can I attend a demo session before enrollment?

We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight into how are the classes conducted, quality of instructors and the level of interaction in a class.

Who are the instructors?

All the instructors at proict! are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by proict for providing an awesome learning experience to the participants.

What if I have more queries?

Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co

How do I avail EMI option as a method of payment?

You no longer need a credit history or a credit card to purchase this course. Using ZestMoney, we allow you to complete your payment with a EMI plan that best suits you. It's a simple 3 step procedure:
  • Fill your profile: Complete your profile with Aadhaar, PAN and employment details.
  • Verify your account: Get your account verified using netbanking, ekyc or uploading documents
  • Activate your loan: Setup automatic repayment using NACH to activate your loan