हीरो वह है, जो जीरो से निकला हो

यह तस्वीर है, कर्नाटक के छोटे से गाँव कडइकुडी (मैसूर) के एक गरीब किसान परिवार में पैदा हुये प्रताप की, इस 21 वर्षीय वैज्ञानिक ने फ्रांस से प्रतिमाह 16 लाख की तनख्वाह, 5 BHK फ्लैट और 2.5 करोड़ की कार ऑफर ठुकरा दिया और प्रधानमंत्री श्री नरेंद्र मोदी जी ने इन्हें DRDO में नियुक्त किया है।

प्रताप एक गरीब किसान परिवार से हैं, बचपन से ही इन्हें इलेक्ट्रॉनिक्स में काफी दिलचस्पी थी। 12 क्लास में जाते-जाते पास के सायबर कैफे में जाकर इन्होंने अंतरिक्ष, विमानों के बारे में काफी जानकारी इकठ्ठा कर ली । दुनियाँ भर के वैज्ञानिकों को अपनी टूटी-फूटी अंग्रेजी में मेल भेजते रहते थे कि मैं आपसे सीखना चाहता हूँ, पर कोई जवाब सामने से नहीं आता। इंजिनियरींग करना चाहते थे, लेकिन पैसे नहीं थे । इसलिये Bsc में एडमिशन ले लिया, पर उसे भी पैसों की वजह से पूरा नहीं कर पाये। पैसे न भर पाने की वजह से इन्हें होस्टल से बाहर निकाल दिया गया । यह सरकारी बस स्टैंड पर रहने सोने लगे, कपड़े वहीं के पब्लिक टॉयलेट में धोते रहे, इंटरनेट की मदद से कम्प्यूटर लैंग्वेजेस जैसे C, C++, java, Python सब सीखा और इलेक्ट्रोनिक्स कचरे से ड्रोन बनाना सीख लिया।

भारत कुमार लिखते हैं कि 80 बार असफल होने के बाद आखिरकार वह ड्रोन बनाने में सफल रहे। उस ड्रोन को लेकर वह IIT Delhi में हो रहे एक प्रतिस्पर्धा में चले गये और वहाँ जाकर "द्वितीय पुरस्कार" प्राप्त किया वहाँ उन्हें किसी ने जापान में होने वाले ड्रोन कॉम्पटिशन में भाग लेने को कहा ।

उसके लिये उन्हें अपने प्रोजेक्ट को चेन्नई के एक प्रोफसेर से अप्रूव करवाना आवश्यक था। दिल्ली से वह पहली बार चेन्नई चले गये। काफी मुश्किल से अप्रूवल मिल गया। जापान जाने के लिये 60000 रूपयों की जरूरत थी। मैसूर के ही एक भले इंसान ने उनकी मदद की। प्रताप ने अपनी माता जी का मंगलसूत्र बेच दिया और जापान चले गये।

जब जापान पहूंचे तो सिर्फ 1400 रूपये बचे थे। इसलिये जिस स्थान तक उन्हें जाना था, उसके लिये बुलेट ट्रेन ना लेकर सादी ट्रेन पकड़ी। 16 स्टॉप पर ट्रेन बदली उसके बाद 8 किलोमीटर तक पैदल चलकर हॉल तक पहुंचे।

प्रतिस्पर्घा स्थल पर उनकी ही तरह 127 देशों से लोग भाग लेने आये हुये थे। बड़ी-बड़ी यूनिवर्सिटी के बच्चे भाग ले रहे थे। नतीजे घोषित हुये, ग्रेड अनुसार नतीजे बताये जा रहे थे। प्रताप का नाम किसी ग्रेड में नहीं आया तो वह निराश हो गये।

अंत में टॉप टेन की घोषणा होने लगी। प्रताप वहाँ से जाने की तैयारी कर रहे थे।

10 वें नंबर के विजेता की घोषणा हुई ... 9 वें नंबर की हुई ... 8 वें नंबर की हुई ... 7..6..5..4..3..2 की हुई, और अंत में पहला पुरस्कार मिला हमारे भारत के प्रताप को ।

अमेरिकी झंडा जो सदैव वहाँ ऊपर रहता था, वह थोड़ा नीचे आया, और सबसे ऊपर तिरंगा लहराने लगा। प्रताप की आँखें आँसू से भर गयीं, वह रोने लगे। उन्हें 10 हजार डॉलर (सात लाख से ज्यादा) का पुरस्कार मिला। तुरंत बाद फ्रांस ने इन्हें जॉब ऑफर की। मोदी जी की जानकारी में प्रताप की यह उपलब्धि आयी। उन्होंने प्रताप को मिलने बुलाया तथा पुरस्कृत किया। उनके राज्य में भी सम्मानित किया गया। अब वह 600 से ज्यादा ड्रोन्स बना चुके है। मोदी जी ने DRDO से बात करके प्रताप को DRDO में नियुक्ति दिलवाई। आज प्रताप DRDO के एक वैज्ञानिक हैं।

इसलिये हीरो वह है, जो जीरो से निकला हो। प्रताप जैसे लोगों को प्रेरणा का स्त्रोत आज के विद्यार्थियों को बनाना चाहिये, ना कि टिकटॉक जैसे किसी एप्प पर काल्पनिक दुनिया में जीने वाले किसी रंगबिरंगे बाल वाले जोकर को।

Is it okay to be an Average Student?

Before you start reading this topic, we want you to ask a few questions to yourself…..

• How do you feel when you see on Facebook or any other social media about one of your friend’s big achievement in studies or career?
• How do you feel when you read something about some legends Steve Jobs, Bill Gates, Mark Zuckerberg, who did something exceptionally well in their life?
• How did you feel when you got average marks in your exams or when you couldn’t qualify an entrance or you couldn’t win a competition which was really important for you?
• How do you feel when your parents expect a lot of things from you and you also have a lot of dreams but in reality, you are living a normal lifestyle?

In most of the above cases, an average student compares themselves with others. They feel inferior, they think a lot about their mediocrity and sometimes they feel like a looser. Social media keep telling us that it’s not okay to be an average student.

Now come to the topic and let’s discuss in our culture today how students are divided into three different categories based on their academic performance.

• The first category belongs to low performer students. They do whatever they want to do in their life.
• The second category belongs to great performer students who do exceptionally well in their studies, job, career and they also get a lot of attention from everyone. People expect a lot of things from a great performer.
• The third and last is the average student category who lies between both of the above categories or for some people they are called as mediocre students.

When it comes to successful people, in most of the cases best students get a great job, great lifestyle and get a lot of attention and respect from others. Worst students or low performers in most of the cases start doing business because they have no option left for their career. They don’t have fear of failure so for money, in desperation, they also do exceptionally well in their life. Average students live a decent or normal lifestyle and somewhere keep going on with better opportunities. Parents have expectations from them, they compare themselves with others, and in whole life, and they try to make their life a bit better than average. Somewhere they have fear of failure and most of the time they avoid to take a risk in their life. They accept the situations and get comfortable with the things whatever they have.

All the above categories we have considered based on the marks of the students and their performance in studies. Now here we need to understand that we all are born with different aptitudes and every student has different capability to grasp the things. We can better understand and categories students through the Bell curve. People who are working in the corporate sector may have knowledge about the Bell curve or normal distribution for performance rating and appraisal. It’s easy to understand the bell curve and differentiate students’ performance through the curve.

If there are n number of students in a class then we can represent their performance for how good they are in studies through the horizontal axis of the Bell curve. We can categories students based on their academic performance through this curve. This curve is very thin at both ends, where left side represents there is less number of the student whose performance is very low, the right side is also thin which represent there are very few students whose performance is exceptionally good. Majority of the students fall in the category of average or we can say in the middle of the curve. Their performance is neither too bad nor too good. We can apply this curve to the categories of students.

Now the question is…Is it okay to tag a student an average student, poor student or a great student in studies considering only the academic learning or marks in their examination?

We need to understand that every student has their own strength and weakness and the fact is we all are average at something, poor at something and exceptionally good at something. Students who are exceptionally good in studies are below average in most of the other things. It’s a universal fact that everything comes at some cost. Consistency, time and energy these three things are very important to be exceptionally good. In most of the cases celebrities, brilliant entrepreneurs or extraordinary student’s life is messed up in other things. We can take the example of Apple’s co-founder Steve Jobs. We all admire him and some of us have a dream to become like him. But behind his success story, there is a dark side. Steve managed to have less friends, he had several issues in his own family, his health was also compromised and he admitted this too in his last statement.

Why it’s okay to be an average student?

It’s true that an average student does not get recognition like great performers and our daily life is filled with information about great performers coming from the extremes of the Bell curve. All of the students cannot be exceptional and none of the magazines is going to make a list of average people or their lifestyle. Most of us reside in the middle of the above curve but we cannot ignore the beauty of simplicity which can be only found in average people. Average people love simple things like family, friends, and the roof over the head. Extraordinary people have too much pressure from society and they work endlessly to fulfil the expectations of others. Today our culture also makes us believe that everyone needs to do extraordinary things in their life and being average has become a new definition of a failure person. If you think in-depth if everyone will become extraordinary then no one will be an extraordinary person so being average is just a state of mind nothing else.

Some people are born mediocre, some people achieve mediocrity, and some people have mediocrity thrust upon them.

-Joseph Heller

So don’t we try to become extraordinary?

Definitely, we all should try to do the best in our life as much as we can. Being an average student is not a sin but pursuing mediocrity is also not a good thing and we need to understand that life is not about running in a rat race. Most of us believe that life is only worthwhile if you are a great person or exceptional at something, but we need to see the other side as well. You will always feel like a failure if you put efforts continuously being more successful than everybody else. You will always find someone else doing something better than you, you will always compare yourself with others, you will have constant pressure, stress, anxiety and these all things may lead you at a dark place in your life. The pleasure of being an average student, average people is also amazing. You cherish the moments in your life, you help someone in need, you do something you care about and you live a healthy lifestyle. In the end, ask one question to yourself…

Is it really bad to be happy with small things?

Average people or students are also great. It’s just, they don’t get noticed and recognition.

कैसे पता चलेगा कि मेरी कुंडलिनी जागृत है?

जब ध्यान साधना के दौरान आपको निम्न लक्षण नज़र आने लगे तो समझ ले की आपकी कुण्डलिनी शक्ती जागृत हो रही है ।

1) जब आपको दिव्य दर्शन, सुगन्ध, स्वाद, श्रवण और किसी के आपको छूने की अनुभुति हो ।

2) जब आपको परमात्मा की तरफ से सन्देश मिलने लगे ।

3) जब मूलाधार चक्र मे स्पंदन होने लगे ।

4) जब आपके रौंगटे खड़े होने लगे ।

5) जब गहन साधना के दौरान आपकी श्वास चलते चलते रूक जाये ।

6) जब आपको अपनी रीढ की हड्डी मे नीचे से ऊपर तक सिरहन होने लगे ।

7) जब आप अकारण ही आनंदित रहने लगे ।

8) जब स्वतः ही आपके मुख से ओम का उच्चारण होने लगे ।

9) जब आपकी आँखे भूमध्य मे थिर होकर शाम्भवी मुद्रा लगने लगे

10) जब आपको शरीर के विभिन्न भागो मे विधुत के झटके लगने की अनुभूति होने लगे ।

11) जब ध्यान के दौरान आपकी बंद पलके जोर लगाने पर भी ना खुले ।

12) जब सभी संदेह दूर हो जाये और आपको सभी अध्यात्मिक ग्रंथों का मर्म समझ आने लगे ।

13) जब ध्यान के दौरान आपको अपना शरीर हवा से भी हल्का महसूस होने लगे ।

14) जब संकट काल व मुसीबत के समय मे भी आपका मन व्यग्र या विचलित ना हो ।

15) जब आप किसी भी कठिन कार्य को बिना थके घंटो तक करते चले जाये ।

16) जब आपको हर समय एक खुमारी या नशे जैसी स्थिति रहने लगे और होश भी पुरा रहे ।

17) जब आप की कही बाते सत्य सिद्ध होने लगे ।

तब जाने की आप की सोई शक्ती जाग रही है ।

5 Techniques to improve your Programming Skills

The ever-evolving technical sphere has forced developers to up skill themselves in order to stay in demand in the job market. If you do not work on upgrading your programming skills, there are chances that you are out-of-demand in next 2 years.

       Everyone knows that learning and practicing is the key to improving programming skills. Every programmer does that but unfortunately, only a few succeed. Here, we are disclosing some bullet-proof techniques to bring you on the path of learning and improving so as to build a long-lasting career in the IT industry.

1. Start a home project

       The best way to brush up your skills is to start a home project, just for fun. As a developer, you need to go through the whole SDLC process and what can be better than starting a fresh project from scratch. Start with a simple project and take it to the next level once the previous goal is completed. This will not only improve your technical skills but also help you enhance your analytical powers, decision-making, and critical thinking.

2. Participate in competitions

       Another best way to check on your skills is to compete in hackathons, coding contests, and quizzes. This way, you get to know your weaknesses and can better work on the skills that you lack. Participation in contests also improves your team-player, communication, and presentation skills.

3. Get up-to-date with the latest technologies

       How would you up skill yourself if you are not aware of what is new in the industry? So, keep yourself updated with the latest technologies emerging every now and then. Here are some tips to help you update yourself -

·         Subscribe to tech-related magazines, blogs, and newsletters

·         Keep your software updated

·         Regularly browse through the internet for the latest news from the technical sphere

·         Re-read the programming books in their latest editions

4. Contribute to GitHub-like repository

       For boosting up your up skilling process, what you can do is to contribute your software code to GitHub or other such websites. Here, you get to encounter different types of real-world problem and get a chance to provide solutions. Through contribution, you not only earn a name in the software developer community but learn a lot about how the software industry works.

5. Work on a freelance project

       Yes, working on a freelancing project is another effective method to help you improve your programming skills. When working on such projects, you deal with a real client and have a lot of scope to explore new horizons with the use of cutting-edge technologies. This helps you broaden your skill set along with earning some extra money.

Basic Terms Every Beginner Programmer Must Know

Programming is evolving with every passing day and we are becoming more and more dependent on it. Because of that a lot of entrepreneurs, as well as job opportunities, are emerging in this field. According to a recent research, Millions of people learn programming every year. If you are a beginner programmer this article is for you as these are the top 15 terms you would come across during your learning curve.

1. Variable:

Variable is a scalar location paired with an identifier, basically it is an address to a memory location where we store any data and identifier being the type of data that is integer, String, Character, Array type, object type and much more. They are the building blocks of any program or software because they help in providing the dynamic approach.

2. Data types:

The data type in simple language is the classification of data which helps in telling the compiler or the interpreter what the programmer intends to use the data and what type of data will be stored in the Variables and accordingly allocates the size. Data types may vary from language to language but some of them are int (Integer Type), char (Character Type), Boolean (True-False Type) and many more.

3. Constants:

Constant is quite similar to a variable the only difference being is its value is constant that is unchangeable throughout the code which is not the case with variables as they may vary from their initialization values. There are various specific realizations of the general notion of a constant, with subtle distinctions that are often overlooked. The most significant are: compile-time (statically-valued) constants, run-time (dynamically-valued) constants.

4. Pseudocode:

As a beginner you will hear this word quite often as this is considered as the best practice to reach a goal, it basically is the layout of the code in a simple mix of English language and your preferred programming language which covers all the important points of how the code will work and how it would be implemented.

5. Conditionals:

As you begin you will be introduced with the conditionals these are basically he conditional statements which tell program what to do in different cases, they play a major role in providing dynamic approach to a program and are present in a huge number in any big code as program should not work in a defined manner but should be interactive to be used by the users. One can find an example of if-else switch cases all around the net, it basic working includes if this choice is true to do this if not then do this.

For e.g.

// pseudo code

if ( ThisArticle ==”Awesome”) 

print (“comment what you liked”) 

else

print (“comment the feedback”)

6. Loops or iterations:

Suppose we want a block of code to repeat for number of times or till when a condition is matched, to write the same line again and again would not only make are code bigger and bulky but will also make it unreadable for this situations we are provided with loops, they repeat a specific block of code until some condition is reached. Most used iterations are for loop, while loop, do while loop.

7. Functions / Methods:

In programming, we often come across situations where we have to use a code which we have implemented before instead of writing that code again we could just move it under a name and call that name whenever we need that code to be implemented. This supports the modular approach which every programmer should adopt. Functions are an integrated part of any programming language and are quite useful and are recommended for usage.

8. Data Structures:

Data structures are the specialized way of organizing and storing data. Some basic data structures include arrays, and some more complex ones are record, tree, list, stack, queue and much more. Any data structure is designed to organize data to suit a specific purpose so that it can be accessed and worked with in appropriate ways. In computer programming, a data structure may be selected or designed to store data for the purpose of working on it with various algorithms.

9. Object:

An object can be a variable, a data structure, a function is basically a value in a memory referenced by an identifier. In high-level languages with multiple classes, objects may have initialized to refer to those classes which form a variable with a data type of that class and let us use all features of object-oriented programming to fullest. An important concept for objects is the design pattern. A design pattern provides a reusable template to address a common problem.

10. Scope:

For any variable, object defined there is scope which tells about the validity of their usability, the variables and objects are valid only inside a piece of code unless globally, scope is beneficial for memory management as it helps in freeing space as when code moves out of that block the memory interlinked with that block is released. Scopes are of two types local and global.

11. Algorithms:

An algorithm is a step by step overview of how to solve a class of problems. Algorithms can perform calculation, data processing and automated reasoning tasks. As an effective method, an algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function.

12. IDE:

IDE or the Integrated Development Environment is one of the most important components of a coder’s life as it provides essential comprehensive facilities to programmers for software development. Truthfully there are no best IDE choices would vary from one to other, so I provide you with the selection of best on basis of most popular choices.

An IDE normally consists of a source code editor, build automation tools, debugger but is not limited only to them. IDE is more than any of these features as it provides a power to connect all of them at one place, besides it, almost all best IDEs have intelligent code auto-completion which suggests what would be possible syntax you are trying to write at real-time.

13. API:

API stands for application programming Interface; it is a set of some predefined protocols and tools which helps in developing a good application software. In simple terms, API is a set of clearly defined methods which helps in communication between various components. An API is usually related to a software library. The API describes and prescribes the expected behaviour (a specification) while the library is an actual implementation of this set of rules. A single API can have multiple implementations (or none, being abstract) in the form of different libraries that share the same programming interface.

14. Modularity:

Modularity is the phenomenon of reusing the code or dividing the code in modules instead of writing it in one full block, this is considered as a good practice as this not only allows reusability of code but as well as lets making changes into some specific section of code without affecting other sections. Object-oriented programming is a way to support modularity by dividing works into classes.

15. Compiled and interpreted Languages:

Compiled languages are the programming languages which needs to be compiled before the usage i.e., your code needs to be built into a binary file application and that file is made to run and checked for error at the compile time, this error includes incorrect syntax, improper usage of statements and much more. Example of such languages: C. CPP, Java, Swift, etc. 

Interpreted languages are the programming languages which need not be compiled before execution rather they are interpreted on the host machine reading the code directly, and providing instructions to the system on how to execute the program. Example of such languages: PHP, Python, JS, etc.

Python vs R, which is good for Machine Learning..?

If you want to build a machine learning project and are stuck between choosing the right programming language to build it, you know you have come to the right place. This blog will not only help you understand the difference between the two languages namely: Python and R; but also help you know which language has an edge over one another in multiple aspects. So without wasting a single moment, let’s dive into it!

R and Python both have identical features and are highly popular tools among data scientists. Around 69% of developers use Python for machine learning, as compared to 24% of the developers using R. Both are open-source and therefore are free in the market. However, Python is structured to be a widely-used programming language while R is created for statistical analysis.

AI and data analysis are two territories where open source has become nearly the true permit for inventive new instruments. Both the Python and R dialects have created strong environments of open-source devices and libraries that help data scientists of any aptitude level, all the more effectively performing scientific work.

The differentiation between machine learning and data analysis is comparatively fluid, however, the primary thought is that machine learning organizes prescient exactness over model interpret ability, while data analysis underlines interpret ability and factual surmising. Python, being increasingly worried about prescient exactness, has built up positive notoriety in machine learning. R, as a language for a factual deduction and statically inference, has made its name in data analysis.

That doesn’t mean to categorize either of the languages into one class — Python can be utilized adequately as a data analysis instrument, and R has enough adaptability to accomplish some great work in machine learning. There is a vast number of bundles for the two dialects that look to reproduce the usefulness of the other. Python has libraries to help its ability for measurable induction and R has bundles to improve its predictive precision.

The following section will talk about the two languages in detail, that will significantly help you to choose the most appropriate programming language for your project.

Python

The Python programming language was created in the late 80s and assumes an essential job of driving the internal framework of Google.

Python includes enthusiastic designers and now it’s been applied in the broadly utilized uses of YouTube, Instagram, Quora, and Dropbox. Python has comprehensively been used over the IT business and grants basic exertion of coordinated effort inside development groups. Thus, if you need a versatile and multi-reason programming language with a supporting gigantic system of designers close by the extendable AI packages then Python is a top pick.

Advantages of Python

● General-purpose language — Python is viewed as a superior decision if your venture requests something other than measurements and statistics. For example — designing a functional website.

● Smooth Learning Curve — Python is anything but difficult to learn and effectively available which empowers you to locate the gifted designers on a quicker premise.

● The bulk of Important libraries — Python boasts of innumerable libraries for assembling and controlling the data. Take an event of Scikit-realize which includes devices for data mining and examination to help the unimaginable AI comfort using Python. Another group called Pandas gives engineers unrivalled structures and information assessment gadgets that help to decrease the improvement time. If your advancement group requests one of the significant functionalities of R, at that point RPy2 is the one to go for.

● Better Integration — Generally, in any designing condition, the Python incorporates superior to R. In this way, whether or not the designers endeavour to misuse a lower-level language like C, C++, or Java, it by and large gives better joining various segments together with Python wrapper. Also, a python-based stack is not hard to consolidate the rest of the job needing to be done by data researchers by bringing it effectively into creation.

● Boosts Productivity — The punctuation of Python is particularly understandable and like other programming dialects, anyway remarkably comparable to R. Along these lines, it ensures high productivity of the development groups.

 Disadvantages of Python:

The absence of a common repository and the absence of choices for some R libraries. Due to dynamic composing, in some cases, it is entangled to scan for certain capacities and to follow shortcomings associated with the erroneous task of various kinds of data to similar factors.

R Programming Language

R was created by statisticians and fundamentally for the analysts in which any engineer can foresee the equivalent by taking a gander at its syntax.

As the language contains scientific calculations associated with machine learning which is derived from statistics, choosing R becomes the right decision to one who needs to increase a superior comprehension of the fundamental subtleties and fabricate inventively. If your task is intensely founded on insights, at that point R can be considered as a brilliant decision for narrowing down your undertakings which requires a one-time jump into the datasets. For example — if you like to examine a corpus of content by deconstructing sections into words or expressions to recognize their examples then R is the best decision.

Advantages of R

● Suitable for Analysis — If the data examination or representation is at the core of your venture then R can be considered as the best decision as it permits fast prototyping and works with the datasets to configuration AI/machine learning models.

● The bulk of useful libraries and tools — Similar to Python, R contains different bundles that help to improve the presentation of the machine learning ventures. For example — Caret supports the AI capacities of the R with its uncommon arrangement of capacities which assists with making prescient models productively. R designers gain advantage from the propelled data analysis bundles which spread the pre-and post-demonstrating stages which are aimed at explicit assignments like model approval or information representation.

● Suitable for exploratory work — If you require any exploratory work in measurable models toward the starting phases of your undertaking then R makes it simpler to keep in touch with them as the engineers simply need to include a couple of lines of code.

Disadvantages of R: 

• Difficult to learn and easy to code badly. Weak typing is dangerous, functions have a fierce habit of returning an unexpected type of object.
• Specificity in comparison with other languages such as vector indexation begins with one instead of zero.
• The syntax for solving some problems is not all that obvious. Due to a large number of libraries, the documentation of some less popular ones cannot be considered complete.

Conclusion:

Concerning Machine Learning, both Python and R have their points of interest with the broad accessibility of bundles. When you ace both the dialects, you can make the better of the two universes because most of the basic errands related to one of these dialects are possible in both.

On the other hand, you can utilize Python for the beginning times of data aggression and afterward feed the information into R, which applies the all-around tried, upgraded measurable examination schedules incorporated with the language.

 

4 Ways to make extra money as a programmer

Programming is one of the most interesting career paths. There are plenty of jobs available for skilled programmers. But if you have a little extra time, you can make extra money as a programmer.

1. Freelancing

Freelancing is one of the best ways programmers can make money. Freelance project listing portals have plenty of projects to choose from. However, freelancing requires a lot of discipline and effort. You need to invest time in finding clients and projects. The biggest advantage is that you can start freelancing next to your permanent jobs.

2. Coding contests

There are dedicated platforms for developers to participate in contests and win real prize money. TechGig Code Gladiators is one of the biggest annual coding competitions with hundreds of thousands of participants. You get to work on real projects and network with like-minded people in this mega event.

3. Online courses

If you are an expert in any programming language, framework, or tool, you can also look at creating course content. Teaching people online is one of the best things that have emerged over the last few years. It benefits both, students and teachers. Experts having knowledge of JavaScript and Python have the highest demand on e-learning platforms.

4. YouTube/Podcast

Some developers like to share knowledge through audiovisual format. YouTube is the best way to share content. You can create videos about programming languages, frameworks, tools, and related content. If you don't like to be in front of the camera, you can record your content and start a podcast channel. Most podcasts are free to listen, but you can make money by charging sponsors. Many podcasters are on Patreon, a platform where people pay a monthly amount to support the work and unlock exclusive access to the content.

Strategies to overcome Programmer’s Block

          Have you ever been in a psychological situation when you are unable to write any code, the deadline of project seems out of reach, and whatever you code appears to be not right? This condition is called Programmer’s Block or Coder’s Block and it is quite normal among developers to go through this phase. Often, it goes away automatically in most of the cases, in a few hours.

          Unfortunately, many-a-times, a programmer does not have a few hours to spare on programmer’s block to pass. When working on a crucial project, a little delay even by a minute can be very costly. Thus, we need a way out of the programmer’s block as soon as possible. Well, worry not. We have come up with 4 proven strategies to resolve the problem and get you out of the mental block. Let’s start!

1.    Revisit your goals

    The major reason behind the programmer’s block is the loss of sight of what you are doing. You get confused of what you are doing and why. The best way to overcome this problem is to revisit the project documents and read the project goals again. This will clarify your vision about the project and help you give a fresh start to the work.

2.    Take a break

           Continuous work on screen can be tiring and cause you a coder’s block. If this kind of situation arises, what you can do is break the cycle. Stop programming, take a break, walk around, and get involved in a random conversation that is completely no-related to your work. This will calm your brain muscles down and help you recover the block sooner than expected.

3.    Fix your approach

          Applying a wrong approach is another big reason behind programmer’s block because a bad approach gets you stuck at places several times. You want to minimize resources while maximizing productivity but a wrong move can lead you to a no-productivity zone. Thus, if you find yourself stuck in such mental block, change your approach. Look at the problem from a fresh perspective and come up with a new approach. The best way is to break down your problem into manageable pieces and apply multiple approaches on different chunks to increase productivity.

4.    Ask for help

          Yes, sometimes you can get a programmer’s block because you do not know how to go ahead with your program. There is no shame in accepting that you are not the know-it-all. Turn your programmer’s block into an opportunity of learning something new. You can ask for help from colleagues, fellow team members, your project manager, and even the internet. There are several online communities and forums to help you resolve your problem. You just ask for help and people will surely like to help you. This thing is true in a case when you have a mental block because of some personal problem in life.