Python Programming
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Python Programming Certification Course

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Learn Python programming from scratch through Edureka’s Python programming certification course. This Python Course will help you master important Python programming concepts such as data & file operations in Python, object-oriented concepts in Python & various Python libraries such as Pandas, Numpy, Matplotlib, and so on. This Python certification course is also a gateway towards your Data Science career.
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60 days of Cloud Lab access
Why should you take Python Programming course ?

Python is the future of AI and Machine Learning – Adrian Rosebrock, Author of 'Deep Learning for Computer Vision with Python'

A Senior Python Developer earns an average salary of $109,280 per year –

Instructor-led Python Programming live online classes

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04 th  Mar
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Goal: Give a brief idea of what Python is and touch on the basics. 

Learning Objectives: At the end of this Module, you should be able to:
  • 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

  • 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

  • Creating “Hello World” code
  • Variables
  • Demonstrating Conditional Statements
  • Demonstrating Loops
Goal: Learn different types of sequence structures, related operations, and their usage. Also learn diverse ways of opening, reading, and writing to files. 

Learning Objectives: At the end of this Module, you should be able to:
  • Understand Operations performed on Files
  • Learn what Sequences are
  • Execute Sequence Operations
  • Understand Types of Sequences in Python: Lists, Tuples, Strings, Sets, Dictionaries

  • 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

  • Tuple - properties, related operations, compared with a list
  • List - properties, related operations
  • Dictionary - properties, related operations
  • Set - properties, related operations
Goal: In this Module, you will learn how to create user-defined functions and different Object Oriented Concepts like Inheritance, Polymorphism, Overloading etc. 

Learning Objectives: At the end of this Module, you should be able to:
  • Define and call Functions
  • Understand why the return statement is used
  • Understand and execute Object-Oriented Concepts

  • Functions
  • Function Parameters
  • Global variables
  • Variable scope and Returning Values
  • Lambda Functions
  • Object-Oriented Concepts

  • Functions - syntax, arguments, keyword arguments, return values
  • Lambda - features, syntax, options, compared with the functions
Goal: In this Module, you will learn how to create generic python scripts, how to address errors/exceptions in code and finally how to extract/filter content using regex. 

Learning Objectives: At the end of this Module, you should be able to:
  • 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
Goal: This Module helps you get familiar with the basics of statistics, different types of measures and probability distributions, and the supporting libraries in Python that assist in these operations. 

Learning Objectives: At the end of this Module, you should be able to:
  • 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 programs

  • 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

  • NumPy library- Installation, Creating NumPy array, operations performed on NumPy array
  • Pandas library- Installation, creating series and data frames, Importing and exporting data
Goal: In this Module, you will learn in detail about data visualization. 

Learning Objectives: At the end of this Module, you should be able to:
  • 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 library
  • Grids, axes, plots
  • Markers, colours, fonts and styling
  • Types of plots - bar graphs, pie charts, histograms
  • Contour plots

  • Matplotlib - Installation, Using Scatterplot, histogram, bar graph, pie chart to show information, Styling of Plot
Goal: Through this Module, you will understand in detail about Data Manipulation. 

Learning Objectives: At the end of this Module, you should be able to:
  • Perform function manipulations on Data objects
  • Perform Concatenation, Merging and Joining on DataFrames
  • Iterate through DataFrames
  • Explore Datasets and extract insights from it

  • 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

  • Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples(), GroupBy operations, Aggregation, Concatenation, Merging and joining
This module is a combination of Live Instructor-Led Training and Self-paced learning. 

Goal: In this module, you will learn GUI programming using ipywidgets package. 

Learning Objectives: After completing this module, you should be able to:
  • 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

  • Ipywidgets package
  • Numeric Widgets
  • Boolean Widgets
  • Selection Widgets
  • String Widgets
  • Date Picker
  • Color Picker
  • Container Widgets
  • Creating a GUI Application

  • Create GUI

Self-paced Concept:
Network Programming and Multithreading 

Goal: In this module, you will learn how to connect your server with MySQL DB. In addition, learn about Socket programming. 

Learning Objectives: After completing this module, you should be able to:
  • Understand the concept of Database
  • Access MySQL DB
  • Create socket for sending short messages
  • Learn Multithreading concepts

  • MySQL DB access
  • Network programming
  • Multithreading

  • Database Creation
  • CRUD Operations
  • Network Creation
  • Multithreading
This module is Self Paced 

Goal: Throughout this Module, you will be designing Python Applications.   

Learning Objectives: At the end of this Module, you should be able to:
  • 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

  • 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
This module is Self Paced 

Goal: Throughout this Module, you will be designing Python Applications. 

Learning Objectives: At the end of this Module, you should be able to:
  • Perform Web Scraping using Python
  • Visualise Data on the browser using Bokeh
  • Use OpenCV to create a motion detection software

  • 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
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    This Python Programming Certification Course will cover both basic and advance concepts of Python like writing python scripts, sequence and file operations, object-oriented concepts & web scraping. On this journey, you will go through some of the important and widely used Python libraries like pandas, numpy, matplotlib, etc.
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. As of today, it is the most preferred language for Artificial Intelligence, Robotics, Web Development and DevOps.
After completing this course, you will be able to:
  • Write python scripts, unit test code
  • Programmatically download and analyse data
  • Learn techniques to deal with different types of data – ordinal, categorical, encoding
  • Learn data visualization
  • Using IPython notebooks, master the art of presenting step by step data analysis
The Python Programming Certification Course is a good fit for the below professionals:
  • Programmers, Developers, Technical Leads, Architects, Freshers
  • Data Scientists, Data Analysts
  • Statisticians and Analysts
  • Business Analysts
  • Project Managers
  • Business Intelligence Managers
There are no hard pre-requisites. However, basic understanding of Computer Programming terminologies is beneficial.

Edureka’s Python Programming Expert Certificate Holders work at 1000s of companies like

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You don’t have to worry about the System Requirements as you will be doing your practical on a Cloud LAB environment. This environment already contains all the necessary software that will be required to execute your practicals. 

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.

Case Study 1: 
Domain: Telecom
Statement: LifeTel Telecom is the latest entrant in the highly competitive Telecom market of Singapore.  It issues SIM to the verified users.  Till now verification was manual through the photocopy of the approved id card document. However, the government has recently introduced Social ID called Reference ID which is mapped to fingerprint of the user.
LifeTel should now verify user against the fingerprint and Reference ID

Case Study 2: 
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 3: 
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 4: 
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 5: 
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 6: 
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 7: 
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.

Instructor-led Live Sessions

24 Hours of Online Live Instructor-led Classes. Weekend class: 8  sessions of 3 hours each. Weekday class: 12 sessions of 2 hours each

Real-life Case Studies

Live project based on any of the selected use cases, involving the implementation of Python Programming.


Every class will be followed by practical assignments.

Lifetime Access

Lifetime access to the Learning Management System (LMS) which has class presentations, quizzes, installation guide & class recordings.

24 x 7 Expert Support

Lifetime access to our 24x7 online support team who will resolve all your technical queries, through a ticket based tracking system.


edureka! certifies you as 'Python Programming Expert' based on your project performance, reviewed by our expert panel.


Access to the global community forum for all our users that further facilitates learning through knowledge sharing.

Cloud Lab New

Cloud Lab has been provided to ensure you get real-time hands-on experience to practice your new skills on a pre-configured environment
"You will never miss a lecture at Edureka! 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."

Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.

Post-enrolment, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments. Moreover the access to our 24x7 support team will be granted instantly as well. You can start learning right away.

Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

You can give us a CALL at +91 90660 20867/1844 230 6362 (US Tollfree Number) OR email at

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
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