Python

lozingle_10032014
02
Nov

Python

Course Description

In future, Python course helps you to gain expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role. You will use libraries like Pandas, Numpy, Matplotlib, Scipy, Scikit, PySpark and master the concepts like Python machine learning, scripts, sequence, web scraping and big data analytics leveraging Apache Spark.

About Python

Python is one of those rare languages which can claim to be both simple and powerful. Features of Python : Simple, Easy to Learn, Free and Open Source, Portable, Object Oriented. That’s why industry is also dependent – Building real-world Artificial Intelligence applications with Python to intelligently interact with the world around you.

Practicals

100% Practical oriented training program

Discount with Hadoop

Enjoy 50% discount with Hadoop All in One training program

Use cases

Implement OOPs with real life problems

Life Time Portal Access

Stay updated! Life time practical tasks implemented portal access

Learning Path – Python

 

Total learning: 11 lessons Time: 7 week
  • Python  11 lessons 0/7

1. Who should go for this course?
Ans. Any candidate who wants to learn Python, and opt their career into data analysis using Python, Yes students can be of any background IT, Non- It.

2. If we are not coming for IT background, so should I go for this course?
Ans. Yes you can, because data science not only for developers it is also for Admin and Data analyst. And we will help you for the same.

3. If I miss a class so, back up classes will be provided or not?
Ans. If you miss a class, will give you Back up class in our up coming batch, within every 15th days, we will repeat a same topic in another batch which you attend.

4. What is the fee structure, should we pay in installments?
Ans. Yes, you will pay into two installment, first installment will be 60%. and remaining you have to pay after 20-30days depending of course. If you pay in one go, We also offer relaxation / discount.

5. Can you accept card as well for payment?
Ans. Yes we accept, Cards for online payment, Paytm, Cheque and Cash.

6. Have you guys given placement assistance?
Ans. Yes we give 100% placement assistance, but not guaranteed. We are helping you in various ways.
1. we will help to build your CV, will give you sample set of cv’s, help of their cv you will manage your CV.
2. We will update you for new openings in the market by call, email or whats-app.
3. we will forward your CV into companies. Because our trainees are coming from MNC’s like, HCL, TCS, IBM etc, so they are given their references.
4. we will make projects, because without any live project you will not get entry into the MNC’s
5. For fresher: If you want we also will give you internship .
6. We have R & D department, so with the help of R & D, you will learn more things and do it practicals as much as you can. Will give you Hands on knowledge.

7. What are the system requirement?
Ans: System Requirements – RAM: 4 GB; Processor: 64 bit processor is best for all types of courses, But our training will be cloud based so its not necessary, but 4gb ram would be enough for Hadoop & Data Science.

8. How many students will be in a Batch?
Ans. Our motto is given 100% attention of every students, and give one to one discussion as well, but according to our opinion & experience, its fruitful if you are having more than 10 students in a batch, the reason is you will heard new questions, new query, new answers and the last but not the least will learnt new things. But again, our motto is given attention to everybody and give you quality and more practical training for the same.

1. What is Python?
Ans. Python is an interpreted, interactive, object-oriented programming language. It incorporates modules, exceptions, dynamic typing, very high level dynamic data types, and classes. Python combines remarkable power with very clear syntax. It has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++. It is also usable as an extension language for applications that need a programmable interface. Finally, Python is portable: it runs on many Unix variants, on the Mac, and on Windows 2000 and later.

2. How stable is Python?
Ans. Very stable. New, stable releases have been coming out roughly every 6 to 18 months since 1991, and this seems likely to continue. Currently there are usually around 18 months between major releases.
The developers issue “bug fix” releases of older versions, so the stability of existing releases gradually improves. Bug fix releases, indicated by a third component of the version number (e.g. 2.7, 3.2), are managed for stability; only fixes for known problems are included in a bug fix release, and it’s guaranteed that interfaces will remain the same throughout a series of bug fix releases.

The latest stable releases can always be found on the Python download page. There are two recommended production-ready versions at this point in time, because at the moment there are two branches of stable releases: 2.x and 3.x. Python 3.x may be less useful than 2.x, since currently there is more third party software available for Python 2 than for Python 3. Python 2 code will generally not run unchanged in Python 3.

3. How many people are using Python?
Ans. There are probably tens of thousands of users, though it’s difficult to obtain an exact count.
Python is available for free download, so there are no sales figures, and it’s available from many different sites and packaged with many Linux distributions, so download statistics don’t tell the whole story either.

4. What new developments are expected for Python in the future?
Ans. See https://www.python.org/dev/peps/ for the Python Enhancement Proposals (PEPs). PEPs are design documents describing a suggested new feature for Python, providing a concise technical specification and a rationale. Look for a PEP titled “Python X.Y Release Schedule”, where X.Y is a version that hasn’t been publicly released yet.
New development is discussed on the python-dev mailing list.

5. Is it reasonable to propose incompatible changes to Python?
Ans. In general, no. There are already millions of lines of Python code around the world, so any change in the language that invalidates more than a very small fraction of existing programs has to be frowned upon. Even if you can provide a conversion program, there’s still the problem of updating all documentation; many books have been written about Python, and we don’t want to invalidate them all at a single stroke.
Providing a gradual upgrade path is necessary if a feature has to be changed. PEP 5 describes the procedure followed for introducing backward-incompatible changes while minimizing disruption for users.

6. Is Python a good language for beginning programmers?
Ans. Yes, It is still common to start students with a procedural and statically typed language such as C, or a subset of C++ or Java. Students may be better served by learning Python as their first language. Python has a very simple and consistent syntax and a large standard library and, most importantly, using Python in a beginning programming course lets students concentrate on important programming skills such as problem decomposition and data type design. With Python, students can be quickly introduced to basic concepts such as loops and procedures. They can probably even work with user-defined objects in their very first course.
For a student who has never programmed before, using a statically typed language seems unnatural. It presents additional complexity that the student must master and slows the pace of the course. The students are trying to learn to think like a computer, decompose problems, design consistent interfaces, and encapsulate data. While learning to use a statically typed language is important in the long term, it is not necessarily the best topic to address in the students’ first programming course.

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