The Python course enables you to master Python programming for Big Data. Our live and interactive course also helps you become an expert in integrating Python with machine learning, Hadoop, Pig and Hive.
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. This Python Certification Course will cover both basic and advance concepts of Python like writing python scripts, sequence and file operations in python, Machine Learning in Python, Web Scraping, Map Reduce in Python, Hadoop Streaming, Python UDF for Pig and Hive. You will also go through important and most widely used packages like pydoop, pandas, scikit, numpy scipy etc.
There is no specific pre-requisite for the course however exposure to core Java and mathematical aptitude will be beneficial. MAT SOFT will provide you complementary self paced courses covering essentials of Hadoop, R and Mahout to brush up the fundamentals required for the course.
In this module, you will understand what Python is and why it is so popular. You will also learn how to set up Python environment, flow control and will write your first Python program.
Topics Covered: Python Overview, About Interpreted Languages, Advantages/Disadvantages of Python, pydoc. Starting Python, Interpreter PATH, Using the Interpreter, Running a Python Script, Python Scripts on UNIX/Windows, Python Editors and IDEs. Using Variables, Keywords, Built-in Functions, Strings, Different Literals, Math Operators and Expressions, Writing to the Screen, String Formatting, Command Line Parameters and Flow Control.
In this module, you will learn different types of sequences in Python, the power of dictionary and how to use files in Python.
Topics Covered: Lists, Tuples, Indexing and Slicing, Iterating through a Sequence, Functions for all Sequences, Using Enumerate(), Operators and Keywords for Sequences, The xrange() function, List Comprehensions, Generator Expressions, Dictionaries and Sets.
In this module, you will understand how to use and create functions, sorting different elements, Lambda function, error handling techniques and using modules in Python.
Topics Covered: Functions, Function Parameters, Global Variables, Variable Scope and Returning Values. Sorting, Alternate Keys, Lambda Functions, Sorting Collections of Collections, Sorting Dictionaries, Sorting Lists in Place. Errors and Exception Handling, Handling Multiple Exceptions, The Standard Exception Hierarchy, Using Modules, The Import Statement, Module Search Path, Package Installation Ways.
In this module, we understand the Object Oriented Programming world in Python, use of standard libraries and regular expressions.
Topics Covered: The Sys Module, Interpreter Information, STDIO, Launching External Programs, Paths, Directories and Filenames, Walking Directory Trees, Math Function, Random Numbers, Dates and Times, Zipped Archives, Introduction to Python Classes, Defining Classes, Initializers, Instance Methods, Properties, Class Methods and Data, Static Methods, Private Methods and Inheritance, Module Aliases and Regular Expressions.
In this module, you will learn how to debug, how to use databases and how a project skeleton looks like in Python.
Topics Covered: Debugging, Dealing with Errors, Using Unit Tests. Project Skeleton, Required Packages, Creating the Skeleton, Project Directory, Final Directory Structure, Testing your Setup, Using the Skeleton, Creating a Database with SQLite 3, CRUD Operations, Creating a Database Object.
This module will help you understand what Machine Learning is, why Python is preferred for it and some important packages used for scientific computing.
Topics Covered: Introduction to Machine Learning, Areas of Implementation of Machine Learning, Why Python, Major Classes of Learning Algorithms, Supervised vs Unsupervised Learning, Learning NumPy, Learning Scipy, Basic plotting using Matplotlib. In this module we will also build a small Machine Learning application and discuss the different steps involved while building an application.
In this module, you will learn in detail about Supervised and Unsupervised learning and examples for each category.
Topics Covered: Classification Problem, Classifying with k-Nearest Neighbours (kNN) Algorithm, General Approach to kNN, Building the Classifier from Scratch, Testing the Classifier, Measuring the Performance of the Classifier. Clustering Problem, What is K-Means Clustering, Clustering with k-Means in Python and an Application Example. Introduction to Pandas, Creating Data Frames, Grouping, Sorting, Plotting Data, Creating Functions, Converting Different Formats, Combining Data from Various Formats, Slicing/Dicing Operations.
In this module, you will understand how to use Python in Hadoop MapReduce as well as in PIG and HIVE.
Topics Covered: PIG and HIVE Basics, Streaming Feature in Hadoop, Map Reduce Job Run using Python, Writing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and MRjob Basics.
In this module, we will discuss about the powerful web scraping using Python and a real world project.
Topics Covered: Web Scraping, Introduction to Beautifulsoup Package, How to Scrape Webpages. A real world project showing scrapping data from Google finance and IMDB.
Yes, One can always use Windows to work on assignments. The initial 5 modules require R set-up which can be easily installed on your windows system. To work on Hadoop on your Windows, the simplest way is to install VMware Player on your Windows Machine. VMPlayer is a software using which you can run another operating system on your Windows. So, by using a VMPlayer and run an Ubuntu/Cloudera OS you can work on the R+Hadoop or Mahout environment and run the assignments. System Requirements to run VMplayer: RAM: 3 to 4 GB. Processor: i3 or above. A 64-bit system is recommended to run the Mahout libraries. To set-up the same, detailed step-wise installation guides are provided in the LMS. Our 24*7 team support will guide you to get the set-up ready.
We will help you to setup the required environment for practicals. The set-up will comprise: - R programming IDE set-up - Setting up Hadoop - Performing R+Hadoop Integration - Installing Mahout The detailed step-wise installation guides are provided in the LMS for you. In case you come across any doubt, the 24*7 support team will promptly assist you.
You will never lose any lecture. You can choose either of the two options: 1. View the class presentation and recordings that are available for online viewing through the LMS. 2. You can attend the missed session, in any other live batch. Please note, access to the course material will be available for lifetime once you have enrolled into the course.
All our instructors are working professionals from the Industry and have at least 10-12 yrs of relevant experience in various domains. They are subject matter experts and are trained by MAT SOFT for providing online training so that participants get a great learning experience.
MAT SOFT is the largest online education company and lots of recruitment firms contacts us for our students profiles from time to time. Since there is a big demand for this skill, we help our certified students get connected to prospective employers. We also help our customers prepare their resumes, work on real life projects and provide assistance for interview preparation. Having said that, please understand that we don't guarantee any placements however if you go through the course diligently and complete the project you will have a very good hands on experience to work on a Live project.
Yes, this can be done. Moreover, this ensures that when you will start with your batch, the concepts explained during the classes will not be totally new to you.
Requesting for a support session is a very simple process. As soon as you join the course, the contact number and email-id of the support team will be available in your LMS. Just a phone call or email will solve the purpose.
You can go through the sample class recording and it would give you a clear insight about how the classes are conducted, quality of instructors and interactiveness in a class.
At the end of your course, you will work on a real time Project. You will receive a Problem Statement along with a data-set to work.
Once you are successfully through the project (Reviewed by an expert), you will be awarded a certificate with a performance-based grading.
If your project is not approved in 1st attempt, you can take extra assistance for any of your doubts to understand the concepts better and reattempt the Project free of cost.
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