Things students must learn about DevOps right in college

When you are in college, you need to learn a gazillion of things. Of all the things you can learn while in college, the most important ones are the things that not many are aware of. One such technology, or practice if you would like to put it that way, is DevOps. In this post, we are going to discuss the impact of DevOps and why students must spend some time learning about it:

DevOps is a set of processes carried out by selected tools that aim towards making Development and Operations team a whole. The reason behind the buzz created by DevOps is its ability to carry out projects much faster than primitive software development methods.

DevOps’ Wide Acceptance

The implementation survey of DevOps observed a boom in the year 2016 and it hasn’t stagnated since.

In 2016, 66 % of global organizations had adopted self-development, 19 per cent had not adopted DevOps, and 15 per cent had not yet decided.

As of 2017, 74 per cent of global organizations adopt DevOps, 16 per cent did not adopt DevOps, and 10 per cent were not decided.

1. Shorter Code Chunks, Faster Releases

When we have two directions of responses from two teams it is hard to say which direction to follow to have the best customer satisfaction and market exposure and whether or not is the application operational.

Development cycles are often extended due to communication lapses between teams. However, teams can release new versions of their app in shorter chunks of code. Hence minimising the impact of such communication pitfalls.

With joint development and operations efforts, the team is able to innovate and obliterate the errors of previous versions at a faster rate. This is important because it is what sets you apart in business.

2. Reduced implementation failure and recovery Time

Having a huge project divided into numerous short projects and spread among the team can reduce the chances of programming defects considerably. With shorter development cycles, DevOps promotes frequent code versions. This, in turn, makes it easy to detect code defects.

Teams can use their time to reduce the number of implementation failures using agile programming principles that require collaboration and standard programming. Recovery time is an important issue because you should expect some failure. Recovery happens at an explosive rate when both the teams shoot each other’s ideas and then get to fixing the application for the market.

A great example of such tools would be Puppet Enterprise. With Puppet enterprise, teams are able to reduce recovery time significantly and push new technical changes in a seamless manner. Not only this, this tool helps you to be consistent across various development, test, and production environments.

3. Increased association and coordination

Experimentation is a large part of DevOps and it cannot happen without resonance between both teams. DevOps has improved software development culture. The teams are happier and more efficient. Culture now focuses on performance rather than individual goals.

Development teams understand the world outside their cubicles and operations shares their fixes and problems with development more to the point than before as it no longer involves “passing” the application to the processes and waiting to see what is happening. Processes do not need to wait for a different team to solve a problem. Long-Awaited transparency is achieved due to DevOps as everyone is working towards common goals.

4. Accelerated and automated projects

Increased productivity boosts development and also decreases the chances of errors. There are ways to automate DevOps tasks. Continuous integration servers automate the code testing process, reducing the amount of manual work required. This means that software engineers can focus on completing tasks that can not be automated.

Speeding up tools are another chance to increase efficiency. For example:

The team has its hands over hardware resources due to presence of scalable infrastructures such as cloud-based platforms. Accelerated testing and deployment contribute in frequent releases and bug-fixes.

Codes can be compiled at a better speed using tools. One such tool is the Apache Ant. Launched by the Apache Software Foundation, this DevOps tool is used to build automation tools that are used to save time with built-in compiling, assembling, and testing tools.

Having an integrated environment can provide aid in avoiding delays as there’s one less team to wait for and it acts as a continuous delivery chain, much like an assembly line. It also spares us the pain of transferring data between different environments such as development, implementation, testing, etc.

5. Reduced human involvement and costs

All benefits of DevOps and its tools come hand in hand with reduced costs and requirements of IT staff. DevOps has lead in reducing human involvement by 35 per cent and 30 per cent less costs.

When it comes to quick automation and reducing human involvement, Gradle is one such tool that you can rely on. Development teams can use Gradle to build, automate, and deploy software in a fairly automated manner.

So, these were some of the important things that you must know about DevOps. Have any questions or wish to learn some more about DevOps? Feel free to get in touch with us.

Placement Talk with Stuti Juyal

Her amazing experience and what she loved!

My experience with Coding Ninjas has been wonderful. From being a student to being a TA to 2 batches and then being the Campus Ambassador and working with the Content team, the journey is enriched with wonderful experiences! Mentors that helped beyond imagination, one-stop solution to sparse and diverse material, a lot of dilemmas was resolved when I joined and gave me a good kickstart! A lot of memories made, I can surely say that Ninjas is home to me!

 Interview experience

It mainly focused on Data structures, Operating system, Object-Oriented Programming concepts.

Advice to Current Students!

I work on the 70-30 rule. It means 30% theory of Data structures and algorithm and 70% practice.
If you are a student at Coding Ninjas, always ask your doubts. Even a single piece of doubt in any concept can be really fatal. So, clear your doubts and make your concepts crystal clear. Your teachers and TAs are there to help you 24*7.
Practice makes a man perfect is just perfect in case of programming, so practice as much as possible.
Be consistent. Even 5 questions every day can prove to be a crucial step towards acing in interviews.
Do not copy and paste code just to improve your leaderboard ranks. If you want to look into the solution, try to grab a pen and paper and try to dry run each and every step.

This will just embed the processing of that code in your brain and you will know how to solve that question as well as similar questions.

How did you prepare for the interview?

Aptitude preparation+ Data structures and algorithm questions that I did in Coding ninjas. Also, I prepared everything written in my CV thoroughly.

How will you introduce Coding Ninjas to your friends?

Coding Ninjas is not just a Coding Bootcamp, it is beyond that! The role it played in my life is irreplaceable and I can never forget all the experiences Ninjas has given me. I will simply say that Coding Ninjas is by far the best place if you thrive for knowledge and are determined to turn yourself into a Coding beast!

Thank you for your constant support and guidance!

What does a day for students in Coding Ninjas’ Career Camp look like?

Coding Ninjas have been providing students with the skill sets and opportunities to land their dream tech jobs since time immemorial. With courses on all programming language fundamentals imaginable, paired with advanced material like machine learning and competitive programming courses, Coding Ninjas is a one-stop platform for all things tech. Whether you are a beginner in the world of programming or a seasoned veteran with a brilliant star rating on CodeChef, Coding Ninjas have something or the other for you to kickstart your process of bagging a dream job.

The Coding Ninjas Career camp is one such initiative, which can only be described as one-of-a-kind. A 6-month program to assist you in landing your dream tech job, the Career camp is for those who want guidance on placement preparation and interview prep, every step of the way. A carefully structured, meticulously curated, and industrially verified course, the Career camp has already started churning out future superstars in the world of tech.

Career Camp – The road to success

As a student, it is very hard to land a dream job without real hands-on experience. For a lot of students that are enrolled in the Coding Ninjas’ Career Camp program, this is the ultimate path to glory. With regular classes and webinars, students are prepared for the D-Day. Not only this, people are able to sharpen their concepts with video lectures, coding assignments, and regular webinars.

However, just building a great skill set might not be enough in many cases. Numerous aspects such as resume, a good GitHub profile, and whatnot is required to come across as a potential candidate in placements. With Coding Ninjas’ Career Camp, you can rest assured about these aspects as well. 

The ultimate Gameplan.

giphy

A 6-month intensive program from the most loved tech education company in India, guaranteed to bag you a dream tech job- sounds great, doesn’t it? Believe us, it is even better than it sounds! The Coding Ninjas Career camp has a meticulously devised gameplan to help students of all backgrounds succeed in their hunt for a dream job. 

  • With industry-verified content, delivered by alumni from IITs, and international universities like Stanford, the Career camp course contents are right up there with the best of the best. Online weekly pre-recorded lectures form the basis of the Career camp’s course contents, with multiple projects included to improve the practical skills of students.
  • Real-time doubt resolution is a reality, and no longer a farce. With Career camp, a teaching assistant per 10 students will be assigned to all enrolled students, with video calling facilities available at any time to resolve doubts. Add to that the exceptional faculty, alumni from IITs and other premier institutes, and you can’t really go wrong!
  • A lot of the placement and job process revolves around resume building and interview prep. Coding Ninjas Career camp has that part of the process covered as well, with specialized profile building training to help you stand out from the crowd. Mentors with a significant amount of experience in the industry guide students on what interviewers look for in candidates, and provide helpful tips on how to present yourself as the most worthy candidate for the job.

From building strong basics to making students ready for success, everything is worked upon at Coding Ninjas Career camp!

Steps to Glory. 

Once students enroll in the Coding Ninjas Career camp, the exact daily schedule is shared with them. However, to give an overview, there are daily online sessions from 10 AM to 6 PM, including coding assignments, video lectures, online interactions, and real-time webinars with mentors and industry professionals. Students are also assigned proper industrial projects to give them a hands-on experience on what the tech scene demands, and ensures that their learning is in sync with the current trends of the tech sector.

Not only this, but students will be provided with industry-level interview preparation, including topics like DBMS, Operating Systems, and Aptitude tests. Mock interviews from time to time are conducted by industry experts, in order to maximize the chances of students getting hired!

The Coding Ninjas Career camp, a one-stop-shop for securing your dream job, offers you each and every avenue for you to reach out and grab that tech job at Microsoft you always wanted. The best part about it? You don’t have to pay a penny until you get placed! It doesn’t get any better than this, does it?

All the very best to all aspiring students! 

Books every aspiring Data Scientist should read

Are you intrigued by the world of data science? Data science is in vogue now and is one of the hottest career paths for many students. However, tackling data science on your own can be quite daunting. It covers several topics like Statistics, probability, applied mathematics, machine learning, etc. However, there are many books that an aspiring data scientist can read. Reading these books can help an aspiring data scientist to not only get a basic overview of the subject but also to master it with enough practice. Here are seven books every aspiring data scientist should read:

1. Think Stats: Probability and Statistics for Programmers by Allen B. Downey

 

Think Stats

Aspiring data scientists need to learn about statistics. How can you integrate statistics with programming? This book gives you an overview of statistics, especially for data science. You will go through the core concepts of statistics and probability, which will help you in data analysis. The book uses data sets taken from the National Institute of Health. It has several examples of python code. The best thing about this book is that the language is very lucid, and it demonstrates real-world examples.

  1. Python data science handbook by Jake VanderPlas

Python Data Science Handbook

Since Python is such an essential language for data science, an aspiring data scientist needs to have a comprehensive knowledge of Python. This book teaches how to use Python for data science. It starts at the beginner level, but slowly, it progresses into more advanced levels. It covers a lot of topics like visualization methods, Numpy, data manipulation with Pandas, and also, Machine learning.

  1. R for Data Science by Garrett Grolemund and Hadley Wickham

R for data science

While you might keep your chief focus on Python, you should also have a working knowledge of R, another language used by data scientists. If Python does not have a specific library, R can provide you with it. This book can be used as a guide to help you perform data science projects on R. It covers several topics from R workflow, data visualization to data modelling.

  1. Machine Learning Yearning by Andrew Ng

Machine Learning Yearning

Machine learning is the future of the tech world. Machine learning has emerged quite recently in the data science field, but it has become quite popular in a short period of time. This book teaches data scientists how they could structure Machine Learning projects. It shows you how and when you should use Machine Learning and all the complexities that it brings.

  1. Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville

Deep Learning

If you want to enter the field of deep learning, then this can be your go-to book. This book teaches how applied mathematics can be used for Machine Learning and also emphasizes on Deep Learning. It shows the mathematics present behind certain deep learning concepts like regularisation, convolutional networks, recurrent and recursive nets, etc. While being mostly theoretical, it also sheds light on the practical implementations of these techniques.

6. Storytelling With Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic

Storytelling with Data

Data visualization is a necessary part of data science. However, it is also a bit difficult. Data visualization creates narratives that can reach out to a wider audience. The use of unnecessary data can obstruct clear communication. This book teaches you how to get rid of the unnecessary data and create a proper narrative that touches the audience on a personal level. It shows you the art of storytelling using metrics.

  1. Ethics and Data Science by DJ Patil, Hilary Mason, and Mike Loukides

Ethics and Data Science

As data scientists, you have to be aware of the ethical limits of collecting data and data analysis. In recent years, there have been several concerns put forward regarding machine bias, privacy, and data protection. This book helps you to understand the ethical principles in data science. It is a great book that gives suggestions to build ethics into the data science culture.

Read these books and set up your path as a data scientist. Happy reading!

It sometimes becomes difficult to understand through books. Don’t worry, we have a full fledged course on data science.
Here is the link – : Data Science Course

Outdated programming language not to learn in 2019

“A good programming language is conceptual thinking about programming.”

Probably these words of the famous American computer scientist Alan Perlis has led to the development of various programming languages. Programming has made sure that the computer functions as to what humans want it to perform, ever since the introduction of computers to the physical realm. You see programming is thus, so powerful to enhance the human-computer interaction in our day to day lives. And so, whatever that strikes the mind of the developer is turned into action by the enormous amount of intricately designed code that is written by them.

CheerySeparateGoldeneye-size_restricted

But, in this era of a dynamically changing environment, stability is not an option even with the programming languages. Regular updates, better plugin facilities, better environment to code in and definitely improvements can prove to be a golden ticket for some while can cost disparity in the usage of some other. The programming language that was once over-hyped, fails to please the developers as they find some better options and have no motivation left to work in it. Evolution and constant scope of improvements my friend is a big game-changer for programming languages too.

Here are some programming languages that are considered as an outdated programming language:

 

  • Objective-C: An object-oriented programming language came into existence in 1984 that added messaging types small talks to C-language. It was the main programming l the design of IOS, macOS, IPadOS that was provided by Apple until they brought forward a revolutionary SWIFT in 2014. Swift was mainly developed and introduced for increasing the popularity of IOS apps among the Apple Users and increase the relative popularity of Application development among mobile app developers. Swift prevails to have an efficient throughput and has replaced Objective-C for nearly half a decade!
  • CoffeeScript: This deliciously made programming language was used for compiling the javascript code that added syntactic sugar to the JS code in a practice to make it more transient in terms of time complexity and more robust and user-friendly. With the deployment of Javascript’s ES6 version, the dooming of this programming language came and the language that was most sought after at some period of time came to deprecation. 
  • Perl: Belonging to a family of two high-level languages, general-purpose, interpreted, dynamic programming language, PERL was developed in 1987 and was extensively used by developers working in Facebook. With the emerging competitors in the market like Python and Ruby, Perl lost its charm and the language which was once considered to be the top programming language lost the battle to these languages. 
  • LUA: LUA was a light-weight, high-level, multi-paradigm programming language that was cross-platform because the interpreter of the compiled bytecode was written in ANSI-C and was mainly used for gaming and web server applications. Did you know the famous entertaining Angry bird was written in LUA?  Yet it had to give up on its fate and since the introduction of R, LUA’s annexation came down or remained stagnant until falling completely! 
  • Rust: This language came up with the aim of replacing our classic C/C++ but it turned the other way around. Rust is a multi-paradigm programming language designed by Graydon Hoare at Mozilla research. Its popularity as per the survey conducted by Stack overflow remained towards the positive side, the critics started complaining about the ambiguous syntax and time complexity which was far from efficient. Restricting programmers of what they can or cannot use, Rust doesn’t have decent inheritance and exceptions, making it simple yet interfering with the availability of programming paradigms among the programmers. No doubt, Rust’s popularity started declining from the year 2018.
  • Erlang: Erlang was a programming language that was developed for the purpose of instant messaging and telecommunications and it was also used in the development of the famous Whatsapp and facebook messenger. Strange that the language lost its fame!! Creation of Armstrong, Mike Williams and Robert Virding in 1986 while working in Ericcson Communication, the language did provide us with the two major methods of instant messaging and took social media to a new height, yet gave up with its popularity gradually decreasing as its utility was mainly constraint to the telecommunication industry.

It was the best of all times, it was the worst of all times.” and so happened with these programming languages, they came, they prevailed and then they were succeeded by the advanced ones. The dynamics of popularity in the market doesn’t confine itself to fashion or music, rather Technology as well. Programming languages have also seen their raze! Ultimately, agility is the latest way of expressing ideas and making them stand-apart

These languages might prove to be obsolete because of their declining popularity and better replacements, but they did conquer sometime back. But, since it is a progressing world and better versions keep on coming, leaving behind old, this post tries to give you a subtle idea of why these languages became outdated and how they were taken over by others! So, if you are planning to start your exploring the programming world, our suggestion would suggest you look for different parameters to build your application and strong foundation in any programming language and then decide the one you want to go ahead! At Coding Ninjas, we provide courses that are updated as per the latest industrial demands and provide you with a platform to stand out from the rest. We sincerely hope that our courses help you to be on the right track of success and be one of the Ninjas of Coding!

From Novice To Expert: Roadmap to become an expert in Machine Learning

There is no denying that machine learning is the future. With the advent of Big Data, the machine learning boom has taken the tech industry by storm. However, machine learning is not very easy. You have to invest a lot of time to become an expert in machine learning. The best way to approach machine learning is by a step-by-step guide. It will help you deal with the subject slowly without getting too overwhelmed by it. Here are a few ways which can make you a machine learning expert:

  1. Understanding the basics

Before diving into machine learning, you need to know what you are getting into. Just knowing a few basics will not help – you have to be aware of the finer details in machine learning. Learn what analytics, Big Data, Artificial Intelligence, Data Science are and how they are related to one another. 

  1. Learning basic statistics

pasted image 0 (9)

When you research on the basics of machine learning, you will often come across many statistical applications. So, what should be your next step? Brush up your statistics. You don’t have to be an expert in statistics, but you need to learn a few topics in statistics. It will be essential in machine learning. A few topics you should work on are sampling, data structures, linear and multiple regression, logistic regression, probability, etc.

  1. Learning a programming language

While researching machine learning, you will learn about the different programming languages which support machine learning. When you learn these programming languages, you become familiar with many applications of machine learning like data preparation, data cleaning, quality analysis, data manipulation, and data visualization.

  1. Taking up an Exploratory Data Analysis project

pasted image 0 (10)

Exploratory Data Analysis means analyzing data sets and then explaining or showing that summary presented by that data set, mostly in a visual format. In this project, charts, diagrams, or other visual representations can be used to display the data. A few topics that need to be covered here are Single variable explorations, visualization, pair-wise, and multi-variable explorations.

  1. Creating unsupervised learning models

pasted image 0 (11)

Unsupervised learning model is a machine learning technique where you do not need to supervise the model. It will discover information on its own and work on it. For example, if you give the basic parameters of several countries like population, income distribution, demographics, etc., unsupervised learning models can help you find out which countries are most similar. It uses unsupervised machine learning algorithms. It can be grouped into two kinds of problems: Clustering and Association. Two Unsupervised learning algorithms are k-means for clustering problems or the Apriori algorithm for association rule learning problems.

  1. Creating supervised learning models

Supervised learning models are a kind of learning where you teach and train the machine to use labelled data to arrive at the right conclusion. After training the machine with the labelled data, you have to provide some training examples to see if it produces the right outcome. For example, if you provide the specific descriptions of an apple (Red, Rounded) and a banana (Yellow, long curving cylinder) to the machine, then it can separate the two fruits and put them in their respective categories. Logistic regression and Classification trees are a few topics you need to cover here.

  1. Understanding Big Data Technologies

The machine learning models being used today were there in the past too. However, we can make full use of them now because nowadays, we have access to large amounts of data. Big data systems stores and control the vast amounts of data that are used in machine learning. So, if you are making your way to be an expert in machine learning, you should research and understand Big Data Technologies.

  1. Exploring Deep Learning Models

pasted image 0 (12)

Top tech companies like Google and Apple are working with deep learning models to make Google Assistant and Siri better. Deep learning models help machines listen, write, read, and speak. Even vehicle tests are now conducted using deep learning models. Learn about topics like Artificial Neural Networks, Natural Language Processing, etc. Start by making your model differentiate between a fruit and a flower. That’s a great start and will set a pattern for future learning.

  1. Completing a data project

Finally, find a data project and work on it. You can search for a data project on the internet. Work on it and showcase your skills. There’s nothing for fulfilling and educative as the proper application of machine-learning.

Benefits of Machine Learning

Machine learning is one of the most innovative technologies which is being used by top companies like Amazon, Apple, and Google. Now, the question is: what are the benefits of Machine learning? Here are a few benefits of machine learning:

  • Identifying trends and patterns

Machine learning can review large sets of data and identify trends and patterns based on it. For example, Amazon can direct notifications to buyers based on their purchasing and browsing history of a user.

  • Constant Improvement 

Machine learning algorithms improve over time. With the increase of data input, machine learning will be more accurate and help in making better predictions.

  • No human intervention 

With machine learning, machine algorithms learn by themselves and improve themselves automatically. So, you don’t have to invest all your time in it.

  • Different kinds of data 

Machine Learning algorithms can handle multi-dimensional and multi-variety data easily and is thus, very efficient in handling large data sets.

  • Many Applications

The applications of machine learning are expanding. From being used software like Siri to even driverless vehicle testing, machine learning is becoming the future in many industries. It is also being included in healthcare industries. Machine learning applications are far and wide.

Job Prospects of Machine Learning

Machine Learning is one of the hottest careers in the market right now. Top tech firms like Amazon, Google, and Apple, are integrating machine learning with their software. According to Gartner, AI will be creating 2.3 million jobs in 2020. These jobs will require research and developing algorithms. Machine learning scientists will have to extract patterns from Big Data too. Some hot career positions are:

  • Machine Learning Engineer
  • Machine Learning Analyst
  • Data Sciences Lead
  • Machine Learning Scientist
  • NLP Data Scientist 

Machine learning is going to be difficult, but in the end, it will be a fulfilling ride. If you wish for expert guidance, you can take help from the Coding Ninjas machine learning course.

Cracking Google Summer of Code 101

Google, one of the world’s leaders when it comes to technology, hosts a global program every year to instill the values of better programming, collaboration, and development in university students and organizations. Dubbed the Google Sum

Cracking Google Summer of Code 101

Summer of Code, it is aimed at getting the concepts of open source deep into the minds of the creative thinkers of tomorrow. With immense exposure and attractive incentives for GSoC scholars, it represents an opportunity to learn, grow, and contribute.

Getting accepted into GSoC, however, is one of the toughest nuts to crack. Let us take a deeper dive into how GSoC actually works.

Turning the gears at GSoC

Every year, organizations and firms all over the world partner up with Google to be a part of the Google Summer of Code, which usually takes place in the summer vacation times of major universities all over the world. Organizations post their projects, bio, and requirements for all students to see and decide which one to go for. These projects range from developing mini-games for a website and building web apps to delving into the deep world of machine learning and artificial intelligence.

To get selected by an organization, there is only one mantra- to contribute. Contribute here means to play a part in the organization codebase as much as possible. This can be by fixing the simplest of bugs, or helping the organization upscale projects critical to their operations. The procedure is a bit different than what students would typically consider as ‘coding’, but don’t worry, we’ll dwell on that more in the coming sections.

Once you get selected by the organization of your choice, you have the entirety of your summer vacations (3 months) to work for them, 6-8 hours a day, learn, code, develop, and strive to contribute to the organizations. The incentives and stipends are ridiculous, to say the least, and the tag of being a GSoC scholar adds some much-needed sheen to your resume!

Let’s get down to business, now. How to actually get into the GSoC program?

Getting in

Now comes the important part- getting accepted to the Google Summer of Code. It is difficult, but not impossible. Let’s get started with GitHub.

GitHub is basically a repository of open source code and projects posted by developers and organizations to work and collaborate with each other. All organizations listed in the GSoC program will have their industrial code available in GitHub. 

Getting into GSoC involves a few basic steps. Here’s what you need to do in order to crack the GSoC-

  • After you pick an organization, follow them on GitHub, and pick a project or application. View the issues posted related to that project, make a copy of the project on your own account, and start working on it.
  • After you make whatever changes you want to your own copy, open up a pull request. This is a fancy term for asking the organization to accept your changes and integrate them with their own source code. This is basically what a contribution is called. You get more accreditation if you report some issues, too. 

The final step- drafting the proposal

This right here is your Hail Mary, this is what will make or break your fate. Once you have everything it takes for you to believe that you’re the best person to continue contributing to the organization, you have to convince the firm about the same. Conveying that sentiment in a well drafted proposal is key to getting accepted. 

Here’s some crucial tips to nailing your proposal

  1. Use technical jargon in the right places. Don’t sound too pretentious while describing your contributions, and include a proper timeline highlighting all efforts.
  2. Make sure that your proposal highlights the project that you intend to work on, and how you wish to proceed. This is your only chance to impress the higher-ups at the organization, so don’t let it go to waste!
  3. Also develop a “motivations” section, which highlights your interest and curiosity in the organization’s projects, what it does, and how you intend to carry forward that passion.

That’s about it! With a pile of effective and valuable contributions, an eloquently-drafted proposal, and a will to succeed is all it takes to make your way into the GSoC. Cracking the GSoC 101 now concludes- don’t wait, fire up GitHub, start contributing, and set off on the journey towards GSoC stardom!

Here’s how CodingNinjas helps students land their dream jobs

The world of IT and technology is without a doubt a competitive one. Computer and software engineers struggle to find jobs every year, because of the sheer amount of competition in the field. Software development and coding, which are the primary areas of work for software engineers, are certainly required by almost all businesses and firms, but the demand of engineers is way more than the supply.

What can a budding software engineer do to make him/herself stand out? Coding Ninjas brings to them an absolute abundance of courses to help them ace job interviews, learn programming from the ground up, learn how to code, and understand all the algorithms used in programming. With courses available for the latest trends in tech such as machine learning as well, Coding Ninjas are doing their bit to help students land their dream jobs in this competitive tech world.

Improving your programming fundamentals

For students who have just begun their journey towards becoming a computer or software engineer, the first step is getting the fundamentals of programming right. It is usually said that the hardest part of the journey is taking the first step, and Coding Ninjas is helping millions of software developer aspirants take this step. With their introductory courses for different languages like C++, JAVA with DS, Python with DS, and Algorithms, Coding Ninjas aim to quell all the fears of becoming a programmer that linger in the students’ minds. Here are some of the courses that make students ready for the ultimate challenge:

Competitive programming course: It is important for students to have participated and performed well in coding competitions. Not only for the resume, but also for the development of their own skillsets and confidence. With this course, we help students ace the coding competitions.

Aptitude preparation course: Aptitude questions are asked in almost every company’s placement test. The normal course curriculum is not designed to prepare students for aptitude tests, though. Because of this, a number of students are taken by surprise in the real exam. To overcome this, we have prepared this course with one of the best instructors, Dr. Arun Sharma.

Web Development with Node.JS: In this course, we teach students to build web apps using NodeJS. Because of how easily it teaches the students to turn himself into a developer from programmer, it is quite popular.

Data Science & ML course: Jobs in analytics and data science have been all the rage in recent times. The quality of jobs that being offered, too, are really nice. To equip students with the right skillsets for becoming a great data analyst/scientist, we have left no stone unturned in this course.

Interview preparation course: For many students, cracking interviews is not a cakewalk. With all the hardwork they put in for the earlier rounds, it is quite frustration to not go through this last door. However, we have created this course to make interview preparation easy for the students.

Machine learning course: Considering the latest advancements in technology, we have devised a full-fledged course on Machine Learning for students. In this course, we aim to simplify concepts of supervised, unsupervised, and other important concepts of machine learning for our students.

With Coding Ninjas’ courses, one can easily learn how to begin their journey towards becoming a competitive programmer, understand how to solve problems and convert solutions into working code, learn and understand algorithms, and ultimately build their own projects in order to give their resume an edge. Worried about not being able to reach the optimal solution of problems? Coding Ninjas is here to take you there, step by step! At Coding Ninjas, we make sure that our students learn the emerging technologies. For example, our students are very interested in the blockchain. This technology is used to process and record cryptocurrency transactions.

Help for interview and job preparation

Interviewing, job search. Flat design vector illustration.

A significant part of being a competitive software developer is being able to clear technical and interview rounds of recruiters as well. This represents a challenge that is much different from coding in an environment since interviews generally take place using a pen, paper, and the student’s imagination. With Coding Ninjas’ interview preparation courses, budding software engineers can improve their chances of getting selected by their dream companies, manifold. 

Right from preparing the students on how to clear the online coding rounds, to make them competent enough to tackle the one-on-one interview rounds, Coding Ninjas are thorough with the entire recruitment process, and guide the students effectively. 

One important part about tackling recruitments is aptitude tests, which many students forget about. Worry not, Coding Ninjas is here to the rescue! The aptitude training course offered guides students on how to make it through the aptitude rounds of top recruiters. This has an added advantage of getting students ready for non-technical placements as well, thus broadening their choices when it comes to a job. Couple this with the competitive programming and interview preparation course, and students will be fully equipped to land their dream jobs by the time they finish with their courses. 

Acing in coding competitions in very important for students to bag a good placement offer these days. However, it takes a lot of practice and experience for students to do well in these coding competitions. We have developed a pool of various other competitive programming courses that are really helpful for the students. Take a look at our online competitive coding course and be sure to be blown away by how easily it simplifies your life with it.  

A testament to the success of Coding Ninjas

sucess-illustration

Helping students think, create, and innovate is the motto of Coding Ninjas. Their efforts over the years have led to students securing jobs in tech giants like Microsoft and Google. With around 5000 placements in tech giants, and having trained over 15000 students, Coding Ninjas are one of the best around when it comes to getting students ready to step into the corporate technology world. Over 20000 hours of content ensure that keen learners never run out of something to gain knowledge about. Let’s take a look at some of the successful placement among our students: 

Pranav Malik: Not to brag, but here’s what Pranav Malik had to say after bagging an amazing internship offer from Goldman Sachs: “The best thing I like about courses in Coding Ninjas is their content and faculty.” Pranav had enrolled in the competitive programming and machine learning course with Coding Ninjas. 

Arushi Garg: One of our most delightful students from the competitive course, Arushi Garg bagged an internship with Microsoft. According to Arushi, one of the biggest challenges was competitive coding. However, she was able to overcome with the Coding Ninjas competitive course in due time. Because of how well DS was taught in the course, she was able to answer questions from DS in the internship interview.  

Astha Kumari: At Coding Ninjas, we have always appreciated the spirit of never giving up. Astha was placed at Amazon India from our own placement cell. Since then, she has been an inspiration for a number of our students. With the help of our incredible courses and the mentorship that comes with it, we were able to sharpen her technical as well as interview skills. 

Ujjawal Pabreja: As Ujjawal bagged a placement at Sprinklr, him as well as his mentors were all over it! Like most successful students, Ujjawal too was enrolled in the competitive coding course. Ujjawal believes that the topic-wise distribution in the course had a significant role in his success. To bag this placement, Ujjawal had to go through a tough process that asked for a good command over DBMS, OS, and OOPS. 

Having an alumni network working at giants like Google, Samsung, Expedia, Microsoft, Adobe, and many more is a testament to the success of Coding Ninjas. If you are looking to step into the world of software development, and want to get yourself ready for your dream job, then Coding Ninjas is the one stop destination for you!

How to ace Dynamic Programming in competitions

Dynamic programming – the one thing that makes every participant in competitive programming scratch their heads. In general, most programming competitions will have one dynamic programming question. It can be referred to as the problem which is there for the win. Solve it correctly and you are likely to win the grand prize. 

Plus, it’s difficult and so, it is likely that many of your competitors will not be able to solve it. Dynamic programming (DP) is tricky – there’s no doubt about that. It has overlapping subproblems, each of which has to be solved just once. All of it sounds very challenging. However, there are a few tips you can follow to ace Dynamic Programming in competitions: 

Tutorials

pasted image 0 (6)

There are many online tutorials designed to teach you dynamic programming properly. When you are going through these tutorials, you will come across many new terms like iterative code, memoization, recursive code, etc. Research about them and see how they are implemented in the program. 

You can also go through a few suggestions and examples given in these tutorials. Even though you might find DP interesting, many overlapping subproblems may not be straightforward. For example, there are DP with Bitmasks, Digit DP, etc. Learn more about these complex programming parts too in different tutorials.

Breaking it up

When you are solving DP, you have to make up a mindset – to think in terms of globally optimal choices. Do not think locally. That’s the secret. When you come across DP, start breaking it down into simpler subproblems and then solve each of them once. Now, build up to the final solution by combining these solved subproblems.  

Noting it down

Start exploring the whole search space and make small inputs on paper. When you are solving the problem, these inputs can help you a lot in avoiding iterative. Iterating all the permutations will be extremely ineffective and time-consuming. Rather keep your notebook in hand and start noting down important points as you work through the DP. It will be more logical, less time-consuming and much more effective.

Mastering Recursion

pasted image 0 (7)

Recursion is a function that calls itself. Now, that’s the bare-bones definition of recursion. However, that’s not all of it. Recursion can also be a thought process. Try to use recursive thinking as a solution to different problems. One of the ways is to figure out the base cases first, even if they are not the simple ones. Try to study a functional language like Haskell, which will help you develop the thought process. When you start thinking recursively, you can easily master recursion.

Practice and Hard work

pasted image 0 (8)

There is no alternative to practising and hard work, especially when you are dealing with DP. So, visit different competitive programming sites and start practising DP. Start off with the easy ones, get your basics right and then move on to the difficult ones. Work hard on your recursive thinking. The more you practice, the better you will become at identifying a problem as DP and then breaking it down into simpler segments.

Believe in yourself

DP is difficult and tricky, but if you give up from the first, then you won’t be able to tackle it. First, you have to believe in yourself and know that you can engage with Dynamic Programming. Once you believe in yourself, you will be able to work hard and find solutions to difficult problems. It will also help you keep your mind cool and be confident when you finally tackle DP in competitive programming.
Make a schedule and keep a slot for practising DP everyday. You might require a guide to help you with DP and make you a true master in it. You can also opt for the Coding Ninjas Competitive Programming course to get expert advice and help with Dynamic Programming.

Placement talk with Kashish Chanana

Her amazing experience and what she loved!

My experience at Coding Ninjas has been great. Mentor support is also great.

 Interview experience

 DSA: It is essential to have data structures like trees, linked lists, graphs and hashmaps on tips. The interviewer will stress highly on these and ask about time and space complexities. General knowledge about how the data structures differ from one another and which one to use in what situation.

Operating System: My Interview had a lot of focus on the OS. The interviewer asked in detail about memory management, thrashing, multiprocessing, multiprogramming, schedulers etc.

OOPS: Several questions were asked about OOPS, including designing classes, polymorphism and inheritance.

Machine Learning: Since my CV had a lot of ML projects, I was interviewed a lot on ML concepts including CNNs and their working, accuracy, precision and recall, which algorithm to use in what situation etc.

Advice to Current Students!

It is vital to have a strong foundation in DSA. With that, it is equally important to concentrate on core subjects like OS, OOPS and DBMS. And be thorough with the projects on your CV 🙂

How will you introduce Coding Ninjas to your friends?

Coding Ninjas is the best place to strengthen your concepts in programming, and the course content is structured in a very proper way. Also, the environment will keep you motivated throughout. The TA support will help you whenever you are stuck.

Thank you for your constant support and guidance!