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Tag: Python programming online training

7 simple hacks to speed up your data analysis in Python

Posted on by Imarticus Learning

Python is a high-level programming language with a built-in data structure with dynamic typing and data binding. It is general-purpose and straightforward to use the language used to create various computer programs. At Imarticus, we help you learn Python online through the PGA program.

Python creates various programs like developing websites, task automation, software, data analysis, and data visualization. Python is an easy-to-learn language; it is shared between accountants and scientists. It is also used to organize finance and numerous other day-to-day chores.

Python and data science go hand in hand with each other. The data analysts use this language to conduct complex statistical calculations, create data visualization, manipulate and analyze data. Python in web development is pervasive; it includes sending and receiving data processing data while communicating with the database. It also helps in the routing of URLs and ensuring security. 

Python is a dynamic language supporting structured and object-oriented programming. It is the language that focuses on readability, and it is the most accessible language that is why it attracts developers and thereby has a large developer community. 

Python helps in data analysis through the following steps:

  • Python helps to efficiently perform high computational tasks with libraries like Pandas and Numpy.
  • Libraries like beautiful soup and scraps help extract data from the net.
  • Python libraries like Matplotlib and Seaborn help in the analysis of pictographic representation and visualization of data.
  • The Scikit-learn library in Python makes complex mathematical calculations efficient and straightforward.
  • Python library such as OpenCV handles the operations on the image. 

Data Analysis With Tableau

With the PGA course at Imarticus, we help you learn Tableau, data visualization, and data analytics. This course will help you build interactive dashboards and publish them on online Tableau. 

Data analytics is the presentation of data with a blend of colors, dimensions, and labels to create a visualization for providing insight into business and making informed decisions. It is an unavoidable aspect of business analytics as it helps enterprises analyze trends and make decisions quickly and visually. For this visualization and data discovery, you need the Tableau tool.

For business intelligence and data visualization, you need Tableau as it is easy to learn, fast to use, and intuitive for consumer use. 

Data Analysis Using SQL

SQL is the database querying language that helps simultaneously interact with multiple people’s databases. One of the most flexible languages combines a learning curve with a complex depth to help users create tools and dashboards for data analytics.

SQL is famous for quick creation and interaction with the database, and it is also a simple language performing complex data analysis. This language uses many valuable tools such as excel popular python libraries like pandas combined with its internal logic to interact with the data sets. 

So, what are the ways to use SQL for data analytics? SQL uses its base infrastructure and easy-to-use dashboards and reporting tools for communication with complex instructions and fast manipulation of data. One of the other interesting properties of SQL is simple accessibility, strategic organization, and simple, manageable, and understandable interaction. 

Through the PGA program at Imarticus, we help you unfold many uses of SQL in data analytics, such as direct integration into other frameworks, additional functionality, and the ability to communicate effectively. SQL is the tool that acts as an intermediary between the usage and storage of complex data and the end-users, and for using this tool, you need to know Python.

All you Need to Know about Python and being a Certified Professional!

Posted on by Imarticus Learning

Programming has always been the core of computer science and Information Technology. Every year millions of programmers graduate with degrees to look for employment opportunities. Therefore, the demand for programmers has grown exponentially, and the trend will not be out anytime soon.

Python is one of the most familiarly used programming languages and was released by Python Software Foundation in 1991. In a fraction of years, it gained popularity and was started being used as a programming language in various disciplines.

Python Programming Defined:

Python is an interpreted, general-purpose, and high-level programming language developed by Guido Van Rossum. Today, companies use Python for GUI and CLI-based software development, web development (server-side), data science, machine learning, drone systems, AI, robotics, developing cyber-security tools, mathematics, system scripting, etc.

Python ranks second among other programming languages. Imarticus Learning has some fascinating advanced-level courses on Python and data science, covering Machine Learning and Artificial Intelligence using Python. With expertise in python programming, candidates can start learning advanced-level Python libraries and modules such as Pandas, SciPy, NumPy, Matplotlib, etc.

Python Programming Career Options:

Python programming coursesAfter a course in applied data science with python specialization, you can choose several career paths. Some are stated below:

Data Visualization with Python and Matplotlib: The profile is linked with extensive data analysis, which is a future for the IT industry.

Web Programming: As you know, python is a concise language; many things can help you build a career as a web programmer.

Developing Games: If you are passionate about gaming and wish to develop games as a career someday, you need to put in efforts to learn Python and how to develop games.

Analyzing Data with Python and Pandas: This allows you to pivot into data science.

Why Python for Data Science?

The first benefit of data science using python is its simplicity. While data scientists come from a computer science background or know other programming languages, many belong to backgrounds with statistics, mathematics, and other technical fields. They may lack coding experience when they enter the field of data science. Python is easy to follow and write, making it a simple programable language to start and learn quickly.

There are numerous free resources available online let you learn Python and get help from communities. Python is an open-source language and is beneficial for data scientists looking to learn a new language because there is no up-front cost involved. This also means that many data scientists are already using Python, so there is a strong community for better guidance.

Python is especially popular among data scientists. There are many python tutorials and python classes where the world comes together to share knowledge and connect. Countless libraries like Pandas, NumPy, and Matplotlib available in Python for data cleaning, data visualization, data analysis, and machine learning make tasks easy.

Build Career in Data Science with Imarticus Learning:

Python programming course

Imarticus Learning offers some best data science courses in India, ideal for fresh graduates, professionals, and executives. If you wish to fast-track your Data Science career with guaranteed placement opportunities, Imarticus learning is the place you need to head for right away!

Industry experts design the programs to help you learn real-world data science applications and build robust models to generate valuable business data. Students go through rigorous exercises, hands-on projects, boot camps, hackathon, and personalized Capstone project, which prepares them to start a career in Data Analytics. Send an inquiry through the Live Chat Support System and request virtual guidance to commence the transforming journey!

Python for beginners – What is Python And Why Is It Used?

Posted on by Imarticus Learning

Python for beginners – What is Python And Why Is It Used?

Python is arguably the most extensively used programming language in the world, which has so many applications and advantages. In this article, we will cover why Python is so popular and why it is used, even though there are multiple other programming languages, which are almost as versatile and powerful as this popular high-level language.

The Dutch programmer, Guido van Rossum started working on what would be later known as Python during the late 1980s. Python 2.0, the version that actually took off and made its place as one of the most important programming languages in computing history was later released in 2000 with multiple empowering features for programmers and developers.

Python 3.0 was released in 2008 with much better support and functions, which made this and the later revisions or versions of Python 3.0 the most popular and preferred installments of this interpreted language. 

Python is one of the most highly used languages due to it being quite friendly and easy to learn for amateur programmers and budding developers. Python can also be stated as one of the most accessible languages due to its simplified version of syntax and its simple approach through natural language.

Python for data science codes is easy to use and write, and future developers find it comfortable to learn this language. Hence, Python is extensively used in daily applications in various fields and it is executed rapidly as compared to other languages. 

What is Python?

Python is an open-source high-level programming language that was initially released as Python 0.9.0 in the year of 1991. Being created with the vision such that it is easy to read, it was truly a high-level interpreter language which was a blessing to computing and IT and could be used for all kinds of purposes. Python follows an object-focused process to assist coders to use simple and logical codes for various kinds of projects.

Python is highly appreciated due to its code readability and it allows developers to take a simple yet capable approach to work on various projects. Python is a truly high-level language as developers truly prefer Python and a huge variety of complex programs are written with the help of this popular programming language. Python is highly preferred in the fields of data science as it helps developers create data models and environments for processing and working with data or advanced analytics.

Why is Python used?

Python was written in C, which with the initial default implementation known as CPython. Python is an interpreted language and like how interpreters function, when a program is written with Python, the source code is converted into an intermediate language, which in turn converts the result into the native language of the system where the program will be run.

Interpreters are computer programs, which directly execute what is written with the help of programming languages. Interpreters like Python don’t require to be compiled into a machine language before being run or executed. Interpreted languages like Python fundamentally use a few processing models for running programs or scripts:

  • Python parses the source codes and performs its behavior without any indirect approach.
  • Python translates source codes into very effective intermediate language conversions, which assist in the immediate executions of scripts.
  • Python efficiently stores precompiled codes and scripts created by compilers inside interpreter systems. 

Python is preferred by budding developers and students due to it being extensively used in mainstream applications and development. It is open-source and is easy to learn, and thus, it is a great idea to invest some time and resources into this highly used programming language. It is highly in demand and individuals skilled in Python or having expertise in this interpreted language are always required by organizations and companies.