5 Machine Learning Techniques with Python

Are you interested in learning some machine-learning techniques with Python? Do you want to explore the amazing world of data science and artificial intelligence? If yes, then you are in the right place!

Imagine using the power of machine learning to train a computer to identify faces, forecast market prices, identify illnesses, or even create beautiful music. With Python as our reliable ally, we can open up this fascinating intelligence world. The possibilities are endless.

You might wonder, “Why Python?” In addition to being the preferred language for data scientists and top IT organizations globally, Python is a great choice for novice programmers and seasoned experts due to its elegance and simplicity. Python will therefore be your dependable travel companion, whether an experienced programmer or a novice taking your first steps into coding.

Data Science Course

In this blog, we will share five machine-learning algorithms in Python that you can use to solve real-world problems and have fun. 

Let’s get started!

What are the top Machine Learning techniques in Python?

Mastering Machine Learning with Python step-by-step

  • The Charm of Linear Regression

One of the most well-known supervised Python machine learning algorithms, it keeps track of continuous characteristics and makes predictions based on that information. By fitting the best line, it demonstrates a link between dependent and independent variables. The linear equation Y=a*X+b, sometimes called the regression line, depicts this best-fit line. 

In the given equation,

  • Y: dependent variable
  • a: slope
  • X: Independent variable.
  • b: Intercept

Imagine having the ability to predict future trends based on historical data. Linear regression is like having a crystal ball for predicting continuous numerical outcomes. It’s perfect for tasks like estimating sales, forecasting weather, or predicting your favorite sports team’s chances of winning the championship!

  • Enchanting Decision Trees

Decision trees are like magical flowcharts that help computers make decisions based on input features. They are incredibly versatile and can be used for classification and regression tasks. 

A decision tree is created by continually posing queries to the partition data. The decision tree algorithm’s objective is to improve predictability at each level of partitioning so that the model is constantly updated with knowledge about the dataset. 

It is a Supervised Machine Learning method. However, classification rather than regression is its primary use. The model uses a conditional statement to compare key attributes as it moves through the decision tree using a specific instance. Depending on the outcome, the more significant characteristics are nearer to the root as it descends to the tree’s left or right child branch. 

  • The Sorcery of Support Vector Machines

Support Vector Machines (SVM) are like magical wizards that can perform classification and regression tasks. They are excellent at drawing decision boundaries and are widely used in image recognition, text classification, and medical diagnosis.

One of Python’s most significant machine learning algorithms is supervised classification, or SVM, which draws a line dividing your data into several groups. We compute the vector to optimize the line in this ML algorithm. This will make sure that each group’s nearest point is also the one that is the farthest away from it. This is nearly always a linear vector, although it can be anything else.

  • Bewitching Naive Bayes

Naive Bayes is like a mystical potion that works wonders in text classification, spam filtering, and sentiment analysis. It’s based on the Bayes theorem and assumes that features are independent of each other (hence the “naive” part). But don’t let the simplicity fool you; it’s a potent technique!

A supervised machine learning method called Naive Bayes is utilized for categorization problems. One of the reasons it is sometimes known as a Naive Bayes Classifier is because of this. It is predicated on the idea that characteristics are unrelated and have no association. However, this algorithm is called “naive” because these presumptions are false.

The Bayes theorem, which is used in this procedure, states:

p(A|B) = p(A) . p(B|A) / p(B)

This is

  • p(A): Probability of event A
  • p(B): Probability of event B
  • p(A|B): Probability of event A given event B has already occurred 
  • p(B|A): Probability of event B given event A has already occurred
  • Enigmatic K-Nearest Neighbors

This Python machine-learning technique focuses mostly on classification but also includes regression. This approach for supervised learning compares distance using a typical Euclidean function while considering various centroids. It then evaluates the findings and assigns each point to a group to best position it concerning all nearby points. 

It categorizes fresh situations by employing a majority vote of k of its neighbors. The case it assigns to a class is the one its K closest neighbors share the most. It makes use of a distance function for this.

The Final Words

Although you now understand the fundamentals of five effective machine-learning strategies, remember that learning is a lifelong process. The subject of machine learning is constantly developing and is teeming with intriguing new developments. Embrace the thrill of staying curious, exploring new algorithms, and continuously enhancing your skills.

Your newly gained knowledge in Machine Learning with Python opens the doors to various professional prospects and exciting initiatives, from forecasting stock market trends to detecting diseases, from making tailored recommendations to transforming industries.

But let’s not lose sight of the fact that machine learning is about more than just models and algorithms; it’s about making a difference in the world. 

Early and mid-career professionals may gain a firm foundation in the dynamic field of data science and machine learning by enrolling in the “Certificate Program in Data Science and Machine Learning,” which is presented in collaboration with iHUB DivyaSampark (TIH) @ IIT Roorkee and Imarticus Learning. 

This in-depth 5-month data science course, created by acclaimed IIT professors, covers data mining, gives you Python-based machine learning tools, and allows you to use data-driven insights to spur organizational success. Enroll now to embark on a transformative journey of learning and upskilling with Imarticus Learning Machine Learning online course with Python.

Keep learning, keep growing, and keep reshaping the world with Python and Machine Learning!

The road to Python certification in 2022

The road to Python certification in 2022

Python is one of the fastest-growing programming languages globally and provides multiple job opportunities for developers. However, individuals seeking to enter into a data science field can also opt for a Python certification as this language is one of the easiest languages to learn. 

Also, due to its varied usage, it can be coupled with data science and machine learning for multifaceted learning, often meeting industry requirements. Before setting up a suitable Python course, individuals must know a few things to chalk out the Python certification path. 

  • Know Your Goals 

Before settling for a Python training program, it is essential to know the goals beforehand. Although most of the students want to settle for jobs, there might be varied interests due to the exquisite demands of data scientists in the job market. So, sketch a plan and draw a roadmap for the goal. 

 

  • Check the Curriculum  

 

After chalking out the proper plan, check the curriculum of the prospective course. This is particularly important as different courses are intended for different individuals. For example, a course that is meant to increase the job opportunity for individuals will have coursework that will need the industry standards. These types of courses will include SQL, Python, statistics, machine learning with Python, neural network and deep learning, and other topics.

 

  • Check Certification Credibility   

 

The credibility of a certificate is also important to note before buying a course. A proper python course should provide a certificate that can secure job assistance. Also, this certificate can be produced for employers so that job seekers can validate their knowledge and showcase their interest in pursuing a career in data analytics.  

 

  • Know the Eligibility 

 

Different courses have different eligibilities, and before settling for one, students must check it. For example, most PG programs in data science need basic eligibility with graduation and/or a certain degree of work experience. However, this might not be the same for all courses. 

 

  • Get the Learning Pathway

 

Each course has its own pathway. For instance, courses might have live instructor classes and in-class discussions. Then, it might follow up with self-placed learning and projects with assessments. Furthermore, it might also have a capstone project and provide placement preparation guidance. 

Why Python is the Fastest-growing Language?

As mentioned earlier, Python is undoubtedly one of the fastest-growing programming languages compared to JavaScript, ReactJS, and others. This makes it one of the best languages to learn for beginners. However, the best reasons behind it are – 

 

  • It is Easy to Learn 

 

Unlike other programming languages, it is pretty easy to learn. The syntax is simple, thus making it more accessible, and it also emphasizes natural language. Also, due to its simplicity and usage, the program can be executed much faster. 

 

  • Assistance From Top Corporate Companies 

 

A programming language goes faster when a top corporate giant backs it. For example, Python is heavily supported by Google, Amazon Web Services, and Facebook. Moreover, Google has created a portal dedicated to Python.

 

  • Supportive Community 

 

Since its launch 30 years back, Python has developed a supportive community. The developers have supported it due to its varied usage and simplicity. Also, with the growing demands of Python, online tutorials, books, research projects are available everywhere. 

 

  • Machine Learning, Big Data, and Cloud Computing 

 

These three disciplines are trending and are in vogue currently. Hence, as Python can be used in research and development, people often prefer it over other languages. 

So, sort your goals first, and then select a course that fits as per the necessity. But, as Python certification is one of the most popular degrees in the data science genre, this can provide you with substantial job opportunities and might lead you to rewarding careers like data scientist, machine learning architect, and artificial intelligence engineer. 

The 4-Step Guide To Refining Your Career: Learn How Python Is Used For Stock Market Predictions

The 4-Step Guide To Refining Your Career: Learn How Python Is Used For Stock Market Predictions

Python, a programming language developed by Guido Van Rossum in the late 1980s, has undergone tremendous growth, especially in recent years, due to its ease of use, variety of libraries, and attractive syntax. 

Global automation is increasing. So, there is always a demand for those knowledgeable in programming languages. Learning a programming language may increase the speed and sophistication of your algorithms.

You can hire a skilled programmer to handle the coding aspect of your plan, but doing so will be difficult later when you need to adjust it to the shifting market conditions.

What is Python?

Python is an interpreted, object-oriented, high-level, dynamically semantic programming language. It is particularly desirable for Rapid Application Development and as a scripting or glue language to tie existing components together due to its high-level built-in data structures, dynamic typing, and dynamic binding. Python’s straightforward syntax prioritizes readability and simplifies learning, lowering program maintenance costs. 

Python’s support for modules and packages promotes the modularity and reuse of code in programs. For all popular systems, the Python interpreter and the comprehensive standard library are freely distributable and accessible in source or binary form.

How is Python used for stock market predictions?

Attempting to anticipate the future value of company stock or other financial instruments traded on an exchange is known as a stock market prediction.

A stock price forecast that is accurate might result in a sizable profit. The Python programming language is a choice for financial traders, who use it to perform automated trading strategies. Python is an open-source language that has become very popular recently, especially among traders looking to automate their trading strategies.

Python is particularly popular among traders because it’s easy to learn and use and has a community of programmers who can help you with your projects.

The following factors make Python an attractive programming language for stock market predictions:

Financial institutions and banks widely use the language. Many financial institutions and banks use Python to perform automated trading strategies and manage their stock market investments. 

The language is easy to learn and use. The syntax of Python makes it easy for developers to write programs that perform complex calculations quickly and efficiently. In addition, many developers who have used other programming languages find that they can easily switch from one language to another without difficulty.

It’s free! You don’t need special licenses as long as you’re willing to download some free software from the Internet.

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Course Benefits For Learners:

  • Students can connect with their peers and business experts as part of this finance management course.
  • Students will understand critical topics, including investment banking, capital markets, risk, and fintech.
  • A capital markets certificate teaches students all they need to know about the financial sector and its operations.

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 Learn The Basics Of Python In Six Minutes

Learn The Basics Of Python In Six Minutes

Learning to program or begin with a new language is not easy: We’re sure your mind is racing with all of the new concepts you need to absorb, and the onslaught of knowledge might be daunting at times.

Python is currently one of the most popular—and well-paid—programming languages globally.

This guide will teach you the fundamentals of Python. This Python training is ideal if you are new to Python programming. You will be familiar with Python programming after finishing this guide.

Why learn Python? 

It’s a programming language that’s been around for almost 30 years, and millions of individuals worldwide use it. Python is simple to learn, making it an excellent choice for beginning programmers. It also increases your productivity when writing code, so this guide will assist you in wanting to get started with coding or enhancing your current skill set!

Python installation is relatively simple, and many Linux and UNIX systems now contain a modern Python. Some Windows machines (particularly those from HP) now come pre-installed with Python. 

Here we start with the basics of Python Programming:

Syntax

There are no required statement termination characters in Python. To begin a block, indent it, and to end it, dedent it. Statements that need an indentation level get followed by a colon (:). Comments are single-line strings that begin with the pound (#) sign; multi-line strings are for multi-line comments. The equals sign (“=”) to assign values (in actuality, objects with names), whereas the equality sign (“==”) test equality. Using the += and -= operators, you may increase or decrease numbers by the right-hand amount. This works with a variety of data kinds, including strings. 

Data types: 

Python data structures include lists, tuples, and dictionaries. The sets library contains sets (but are built-in in Python 2.5 and later). Lists are one-dimensional arrays, and dictionaries are associative arrays (commonly known as hash tables). Tuples are immutable one-dimensional arrays (Python “arrays” can be of any type so that you can combine integers, texts, and so on). 

Strings

Its strings can contain either single or double quotation marks, and you can put one type of quotation mark inside another (for example, “He said ‘hello.'” is legitimate). Strings with many lines are in _triple, and double-quotes.

Flow control statements

If, for, and while are flow control statements. Instead of using if, there is no switch. Use to iterate over the members of a list. Use range(number>) to get a list of numbers you can iterate through.

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  • Students must understand the fundamentals of data analytics and machine learning and the most in-demand data science tools and methodologies.
  • Learners earn a tableau certification by participating in 25 real-world projects and case studies led by business partners.
  • Recent graduates and early-career workers should consider enrolling in data science and analytics programs since they are among the most in-demand talents in today’s industry.

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Learn Python Online: Things that non-programmers must know

Learn Python Online: Things that non-programmers must know

The developer of Python, Guido V Rossum, created it as a hobby project back in 1989. Today, Python has become one of the few official programming languages of Google due to its ease of use paired with efficiency. Python won the position of most popular programming language in 2020, as put forward by a joint survey of Google Trends and GitHub. In terms of programming language usage by global developers, Python has secured the third position in 2021, following JavaScript and HTML/CSS. Are you a non-programmer? Then Python can be your ideal starting point. And, here are a few things that you should know about this programming language.

Python: What is it?

It is an object-oriented, high-level programming language. It is a general-purpose, interactive programming language, the name of which is based on Rossum’s favorite TV series, “Monty Python’s Flying Circus.” The language is known for its versatility and simplicity, making it ideal for beginners and non-programmers.

What are the features of Python? 

Do you want to learn Python? Here are a few features to know about.

It can be integrated: 

Python can be integrated with an array of programming languages like C, C++, and Java.

Python is interpreted, and interactive:

Python can be processed by interpreters while they run it and a learner does not need to compile the program before execution. It is interactive because you can interact with the interpreter directly.

It is object-oriented:

Python is an object-oriented programming language and has code reusability. Designing an application with Python is easier with minimal coding.

Ideal beginner’s language

Python is characterized by the simplicity of structure, clear-cut syntaxes, and less number of keywords, thus making it simple to learn for any non-programmer. Furthermore, it is an open-source software freely accessible to all.

Why learn Python?

Tons of career opportunities:

The popularity of Python has contributed to the rising demand for Python programmers. Certification in data analytics can promise you an array of career choices.

Active community:

Program learning is not a solo sport. A massive community for providing the required learning support is vital to proper learning. Python has a considerable community backup which helps non-programmers in their learning.

Highly versatile:

It is a highly adaptable programming language that is used in multiple fields like web development, data science, software designing, and gaming. Python’s versatility is further enhanced by its ability to sync with a variety of other programming languages. Thus, it is a ‘cross-platform’ language.

Which fields use Python?

Python’s simplicity and ease of use have granted it access to a variety of fields like:

  • Web applications
  • 3D CAD-based applications
  • Software development
  • Auditory applications
  • Machine learning
  • Visual applications
  • Artificial intelligence

 Tips to keep in mind

Now that you know what Python is and what its features are, here are a few tips to keep in mind before opting for certification in data analytics:

  • Being consistent in code-making always helps to learn better. Are you making mistakes in coding? They are the stepping stones to your proper learning. So, code every day!
  • An interactive Python shell can be your ideal learning tool.
  • Opt for the pair programming technique, where you will pair with another developer. This way, you both will switch between writing codes and reviewing and problem-solving. Now, you can learn both sides of Python.
  • Opt for data analytics certification courses online, which can offer you the best possible resource to learn Python faster.

Conclusion

Are you looking for data analytics certification courses online? If yes, then you must check out the one offered by Imarticus Learning. With a fully online learning mode, this course is ideal for future data science experts and is backed by case studies, real-life business projects, and mentorship sessions.

Python certification: Do not use print for Debugging anymore

About Python Language

Want to learn how to make your work productive and easy even though it is time-consuming? Python programming is a high-level programming language used by big organizations around the world such as NASA, National Security Agency, Bit Torrent, Netflix, and more to conduct data analysis and automate tasks. It is used widely by software developers to build their website effectively in alignment with the domain because of its features like object-oriented language which helps to break down tasks and gain clarity.

Before we delve into the features and benefits of Python programming, let us understand briefly what is meant by the programming language. 

Continue reading “Python certification: Do not use print for Debugging anymore”

Python Training: Eliminate the skill gap in the modern workforce

There is a well-known skill gap in the present-day workforce. Many job roles remain unfilled because employers can’t find workers with the necessary skills. However, one skill can bridge this gap by 2022: Python training. 

Python is a universal language that you can use for various purposes, from data science to web development. This blog post will discuss why Python is so popular and how you can get started with Python training today! 

Python’s popularity in the tech industry

Python is becoming the third most-requested language on Stack Overflow and LinkedIn. Due to its versatility, ease of use, and popularity among data scientists for machine learning tasks. Many people who are just starting with programming languages choose Python because it has a simple syntax and is easy to learn. 

There are several reasons for Python’s popularity in the tech industry.

  • Python is easy to learn.

One of the main reasons Python has become so popular in recent years is that it’s relatively easy for beginners. It has a simple syntax and fewer lines than other languages such as Java or C++, making learning how to code more accessible for new programmers who want to get started coding quickly without having too much experience.

  • Python is versatile.

Python has many different uses, and you can use it for web development to machine learning. You’ll find that most people know how to code using this language because it allows them the flexibility they need when working on projects in any industry.

  • Python is open-source

One of the best things about using an open-source language like Python is that anyone can contribute to it or make changes if they see something wrong with how something works. It means there’s always a community willing to help each other out when needed, making coding less intimidating than ever before! 

The benefits of learning Python for both personal and professional development

 Python continued to be one of the most popular programming languages in 2021. The demand for Python developers is to grow exponentially in the next few years, with an Increase market share that will only widen further.

Many enterprises utilize Machine Learning (ML) and Artificial Intelligence (AI), which require vast amounts of data to be processed. Python has emerged as the leading language for data science and machine learning projects mainly because of its readability, comprehensibility, and ease of use. 

Professionals and students alike must learn this powerful programming language to bridge the skill gap in the modern workforce. There has never been a good time to start learning Python with its growing popularity than now. Don’t miss out on this opportunity!

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Why Should You Learn Python For Data Analytics and Artificial Intelligence?

2022 has seen a huge increase in both the number of data science applicants and also future aspirants all around the world. In India alone, LinkedIn, the global job search leader, announced a 25% spike in data science professionals as compared to 2021, and that is a huge number by a number of standards.

But one of the most common questions that ponders the mind of data science aspirants most often is why they should learn Python to get an edge in this profession?

Thus if you are planning for a career in data analytics and artificial intelligence in the future, and too have this question in your mind, in this article, we will answer exactly that.

Let’s get started.

Why Is Python Important for Data Science?

At the present moment, there are more than 35 different programming languages that are actively used by developers and coders all around the world. But among all of these, Python is undeniably one of the most versatile and well equipped, especially in the field of data science.

The reason behind this is simple; if you take a look at some of the most common tasks that are executed by a data scientist on an everyday basis, starting from data extraction and ELT (Extraction, Loading, and Transformation) all of them require a solid knowledge of Python coding and operation.

Along with this, another important reason why Python is so often relied upon as the go-to programming language for data science professionals is the fact that it comes with a suite of different packages, starting from SciPy, NumPy and pandas, which make complicated and time-consuming tasks easier, more efficient and effortless.

For instance, Matplotlib, which is one of the leading Python packages, is often used by data science professionals when they want to include visualizations or any sort of graphics in their simulations.

If all of this is not enough good reason, as to why you should learn Python

Learn Python ProgrammingTo get an edge for your career in artificial intelligence, here are some of the biggest advantages of the standalone programming language in itself.

Advantages of Python

Easy to Learn

If you are a beginner at coding and you are looking for a programming language that is easy and fast to learn, then Python should be your choice.

The programming language has been around since the late 1980s and has thus undergone several developments and improvements in the last couple of years, which has made the current version extremely user and beginner friendly to learn and execute.

Since data science is such a fast-paced career, where developments are literally happening overnight, the need for a language that is easy and fast to learn is a no-brainer, thus making Python one of the most obvious choices.

Scalable

When you would have spent a considerable amount of time coding, one of the first things you will realize is the fact that Python as a programming language is immensely scalable. Compared to programming languages like Matlab and Stata, which are industry leaders in their own might, Python makes it very simple and straightforward for anyone to scale. The language comes inbuilt with a suite of features that allows you to have multiple approaches and perspectives to solve the same problem, along with having a wide range of flexibility to try out new things as and when they are developed.

Learn Python ProgrammingThe scalability aspect of Python is the second reason why companies prefer their data science professionals to know Python. Scalability is immensely important in both data science and artificial intelligence, mainly because of the fact that new discoveries are being made on the regular.

Conclusion

Thus, if you want to give your career in data science an edge, now is the time to start enrolling for an Artificial Intelligence Training that comes packed with a course in Python.

We offer analytics and artificial intelligence courses at our centers in Mumbai, Thane, Pune, Jaipur, Delhi, Gurgaon and Bangalore.

5 steps to master python for artificial intelligence

Python is among the most-used programming languages on the globe. Developed in 1991, Python has been useful for new-age technologies also. Python is helpful for new-age technologies like AI (Artificial Intelligence) and machine learning. AI algorithms can be developed easily with Python as compared to other programming languages.

Most of the companies and AI experts find Python easy than other programming languages. Python has left behind some popular programming languages like C and Java when it comes to AI. Read on to know five steps to master Python for AI.

 

  • Learn the basic concepts of AI

 

Before you start making AI algorithms with Python, you should know basic AI terminologies. You should know different types of learning methods for AI algorithms, agents, environment, and other basic things about AI. You do not need to know everything about AI initially. Learning AI with Python is the perfect way to become an expert. However, you need to know the basic AI terminologies beforehand.

Getting your concepts cleared is of utmost importance. You cannot become an AI expert if you don’t know much about the basics. Knowing the basic concepts of AI and its importance is as important as knowing the complex concepts.

 

  • Learn the syntax of Python

 

For every programming language, you first learn its syntax. The syntax can be referred to as the code writing style which is different for each language. Python is chosen by AI experts because it has a simple syntax and involves less coding. You need a way of writing code in Python first to master it in the future. It won’t take much time to learn the syntax of Python. You can join an online Python course to learn quickly.

 

  • Join an online course for AI with Python

 

You need to go for an online course for AI with Python to master it quickly. An industry-oriented course can help you in learning Python for building smart AI algorithms. Imarticus Learning is a reliable source that can provide you with artificial intelligence and machine learning certification. With a globally-recognized artificial intelligence and machine learning certification, you can also get a job as an AI expert. 

Best Python programming course for Artificial IntelligenceImarticus provides an artificial intelligence course that helps you earn a job. The Certification in AI & ML gives you a chance to learn according to the curriculum of IIT Guwahati. You can learn from a premier institute of the nation from your couch with Imarticus Learning.

 

  • Know about Python libraries for AI

 

Python has many built-in libraries for AI which makes the task easy. A python library is a pre-existing chunk of code that can be used time and again for your AI projects. Python libraries save your time when working on AI projects. Some of the Python libraries used by AI professionals are NumPy, SimpleAI, SciPy, Matplotlib, etc. Make sure about the function and capability of each Python library for AI. It can save you time when designing AI algorithms.

 

  • Work on some AI projects with Python

 

Choose a Python course that allows you to work on AI projects. Working on AI projects can help you learn Python more quickly. You would not want to make mistakes as an AI employee. It is better to make mistakes beforehand and learn from them by working on AI projects. The AI course offered by Imarticus lets you work on around 25 industry-related projects.

Conclusion

Python is a simple programming language that is easy to use and learn. It is why many AI experts choose Python for boosting their productivity. You can learn about the role of Python in AI via the online course offered by Imarticus. Start your artificial intelligence course right away!

Python Developer Salary And Certification Guide To Get You To The Top!

Python is one of the most popular and widely used programming languages across the globe. The use cases of Python have broadened from SEO and web development to AI, IoT, Fintech, machine learning, and data analytics. Today, with the support of a collection of software libraries, Python enjoys the reputation as an advanced programming language that can be used for general purposes.

Python training supports a variety of programming paradigms which makes it a user-friendly programming language that can be scaled for larger applications.

Python Certification coursePython sits at the fourth position in the TIOBE index, which tracks the popularity of computer programming languages. Diverse use cases and popularity make Python a favorite choice of many fields. This brings good compensation benefits as well.

The salary of Python programmers varies depending on the field they are working for.

Python Developer Salary

Given the diverse use cases of Python, companies are actively looking to hire Python talents. No wonder python developer tops the searches on the leading job portals. The job could vary from application developer to data scientist, web developer, or DevOps engineers.

The increasing demand for professionals is also reflecting in the compensation packages offered. The shortage of talents has pushed things in favor of the jobseekers. This is a good time to negotiate on the salary package. The average salary for different roles in India and the international job market are as follows:

Job Role Annual Salary
India International
Data Scientist ₹708,012 91,838 USD
DevOps Engineer ₹10,00,000 93,931 USD
Software Developer ₹10,00,000 118,950 USD
Senior Software Engineer ₹10,00,000 129,000 USD

 

Why You Should Learn Python Language

As discussed earlier, Python is becoming a popular programming language widely from web development, desktop apps, network servers, back-end APIs, etc. Its use case in artificial intelligence makes it an even more attractive career option today. Here are the top reasons to enroll in a Python programming certification course today.

  • Technology giants are on the lookout for Python professionals to help them develop several applications. Being the programming language used in many applications, Python skills are one of the most valued resources in these companies. The top names among the Python employers are Google, Facebook, Instagram, NASA, YouTube, Reddit, Quora, IBM, Mozilla, Dropbox, Yahoo, Uber. Getting trained in Python increases your chances to become a part of these big names.
  • There is a need gap in the job market. The need for Python professionals is increasing as it finds its application across many fields. However, there is a serious lack of talent. Python-trained professionals can get into futuristic fields as well – the likes of AI, robotics, big data analytics, and machine learning.
  • Having a certification increases your chances of getting hired. So, if you are interested in a Python Programming career, you should enroll in a Python programming certification course. Many reputed certifications train you with projects and case studies to help you deal with real-life problems.Python Certiication courses
  • Flexible syntax and a broad array of libraries make Python ideal for beginners looking to build their careers in this field. The “CodinGame 2020 Developer Survey Report” says that Python tops the preference of 10 K developers with 84 percent among them favoring it.

Python is growing very fast in terms of popularity. It is climbing up the list of popular programming languages, pushing its competitors down the list. It has successfully grabbed the second position in popular platforms like Github. It is just a matter of time for Python to secure the top position.

All these have increased the demand for Python-certified professionals. So, if you are aspiring to a Python programming career, there is no better time than this to start it.

Related Article:

https://imarticus.org/python-coding-tips-for-beginners/