Placement talk with Anubhav Malik!

A place that gave me the right direction in my career!

 Anubhav Malik

His amazing experience and what he loved!

My experience with Coding Ninjas has been life-changing. I got the direction I needed from Coding Ninjas, and it has helped me come across a long way since my course ended. Learning from very experienced faculty is one thing, but even the TA support is fantastic.
The best part is if you join Coding Ninjas you just don’t stay a part of the learning process during the course but even after the course has ended the faculty is still willing to help you.

Interview experience

It consisted of 2 rounds where they asked about algorithms and Data Structures.

Advice to Current Students!

Don’t jump onto other technologies until you completely understand the one you started with. Hard work and consistency will help you go a long way.

How will you introduce Coding Ninjas to your friends?

Single decision to join Coding Ninjas and the ability to work has changed my life, it can change yours too.

Thank you for your constant support and guidance!

Crucial web designing practices to follow

Did you know that 94% of your all visitors of the website decide in the first 3 seconds if you’re a trustworthy, reliable and professional based on the design alone? That’s right, making a positive impression on the first time is very important. Your website is your virtual store-front. We would want customers to come back and enjoy their experience while using our website. Without a professional design that has been optimized for success in the global market, your marketing strategy will sink even before you get started.

We have listed a few important points below to help you get through the vital principles of web design:

Visual Hierarchy

Visual hierarchy is one of the most crucial elements through which even an amateur can create a tremendous and somewhat professional design. It is a method of organizing components according to their importance. Certain parts of your website are mattering than the others, and even if all the items on your menu are equally important, you know where you want the user to click first.

You can always start by setting an objective for your website. Rank elements according to your business objective and you’re halfway there.

Hick’s Law

Hick’s law mentioned that the time it takes for a person to make a decision increases every time you offer an additional option. This can happen in your daily life as well. Every time you visit a shopping store, the time you spend there increases if the store is offering you a lot of options. Similarly, if the visitor sees a lot of choice on your website, it will be easier for him to choose nothing.

To make their experience enjoyable, you have to eliminate choices. And if there is a massive amount of products list that you sell, then provide the visitors with good filter options. It will undoubtedly make them revisit your site and who knows, maybe you can earn a permanent customer too.

Responsive Design

With the evolution of the different screen sizes in the industry including mobiles, tablets, and laptops, it has become a really big issue for the designers to create a responsive web design. The experience of the visitor hugely depends on the device he is using to visit your website. And god forbid if the site is not displayed well to the customer, the majority of them will stop interacting with the website.

It might not come as a big deal to make the web design responsive for the designers, but for the customers, seamless experience is pretty much everything so omitting the particular can cause a considerable loss for the company growth.

High-Quality User Experience

User experience is something, that if it is done right, visitors will stay longer on your website and even revisit it later. It can be possible if you optimize options like fast-load options, eye-pleasing element, correct navigations, and mobile responsiveness.

The few aspects on which you should inevitably focus on to give your customers a seamless experience are:

  • User-focused design research can help you a lot to make the experience of your customers perfect.
  • Content that is relevant and valuable to the target customers can provide your website with substance and can be a significant component of high-quality UX.
  • Consistent communication can also play a huge role in bringing back more visitors. Making the user comfortable and providing them with useful information makes your website interactive and more popular than the others.

White space and clean design

The white area is also known as “negative space.” Knowing how to make the best use of negative spacing is what can create a great design. It is not merely just a negative area; the white space enables all the other elements to exist at all. Imagine a page with no white spaces, and there are items, graphics, and images just scrambling together. I can bet you won’t even bother to look at it and in a fraction of seconds you have already moved on to another website.

Enough spacing can do a great job if done correctly. Your website will look clean and can convey the exact message you are trying to communicate amidst the target customers.

To conclude, web design might look easy from the outside but knowing these minute detailing is what makes you a great designer. After going through this blog, you can decide for yourself if you want to be just another designer or a great one. We understand that it is a lot to take in. But we at coding ninjas are here to cover you with all the information that you will need to ace the web designing practices to follow.

The importance of Data Structure and Algorithms for interviews

Google is pushing a lot of online job offering portals to work radically, to see if there are expired jobs, and to evaluate the resumes and help candidates with suggesting the right options. As a programmer, you can make sure that your resume looks good by mentioning all the languages you are efficient in and all the relevant work experience you’ve had.

But, the pivotal process of selection starts during the interview. It may take up to an hour long of conversation and about three to four rounds. The communication depends upon the job role you have been offered and the perspective of the interviewer to check on the technical and non-technical areas.

No matter what route your programming interview is looking to take, the matter of fact is that you won’t be able to dodge the questions on Data Structure and Algorithms. The concepts that surround DS and Algo are extremely handy for a programmer, and that’s why every tech giant will check your knowledge of the same.

Let’s look at some more reasons why data structure and algorithms are so important for a programmer (and therefore for interviews):

Solve the problem more efficiently

While developing software, a developer uses data structure and algorithms internally. You can collect and organize the data and perform a specific operation with the help of data structure process. Most programmers try and create their own algorithms to solve the occurring problems, or they can also use the existing algorithms from someone who has already solved the problem. With the use of object-oriented programming principles, the API(Application Programming Interface) hides the implementation of data structures and algorithms. You might have access to the source code for solving an issue, but only a real programmer can understand the application programming interface and fix the problem with the help of a practical understanding of data structures and algorithms.

Use the right tool to solve the problem:

To systematically handle the data, there are a set of techniques provided by the data structures and algorithms. Without the knowledge of core concepts, the programmer might take longer than usual to solve a particular issue. To explain further, if the programmer needs to collect the candidate’s information from Linkedin, they should have proper learning about the data structures and the algorithms. If the programmer does not know the efficient techniques, then they may not be able to write the appropriate code to handle the data.

Data structure help to run the program more efficiently

The knowledge of data structure and algorithms can be beneficial to test the efficiency of both the freshers’ and the professionals’. Even we get the computer at lower prices with enough memory; if the programmer doesn’t handle the memory with a proper technique, there is a chance that the program might leak memory. The modern programming languages use garbage collection to manage memory. The program will start losing its memory only because of the lack of knowledge of the programmer about data structure and algorithms. Also, many languages might not require an understanding of the techniques and algorithms. But to write valid code, they should know how to handle the data.

Limited candidate evaluation time

Going through the candidate’s resume might help the interviewer know all the languages they are efficient in or about all the projects they have been working with. But it takes about a few hours to select a promising candidate finally. So, the interviewer mostly evaluates the candidate by their knowledge of data structures and algorithms. If the fellow is good with structures and techniques, it becomes effortless for him to learn new languages or the syntax of the updated programming languages.

Evidently, data structures and algorithms will be a large part of any F2F programming interview you sit for. And if just thinking about interviews gives you jitters, come over to Coding Ninjas. We have specially designed interview preparation courses that cover almost everything you can expect in interviews!

Mistakes to avoid as a fullstack developer!

 

Making mistakes is a part of life. But being a developer and then making common mistakes can affect your career in the long run. Eleanor Roosevelt, being the extraordinary lady she was, once said “Learn from the mistakes of others. You can’t live long enough to make them all yourself.” Similarly taking notes from others and avoiding the common mistakes at the beginning of your career can save a lot of your time and efforts. So, here is a list of the frequently made errors to give you an idea of the potential problems you might confront.

1. Improper naming conventions: This industry is becoming way more competitive than ever. We have thousands of resources and tools which are smart enough to catch mistakes and fix them. But when we try to catch up with speed, we usually develop the attitude to name the variables precisely like a, b, z, etc. Here is the point where the coding lacks readability. Even if we mention a comment below, that might not make any sense to multiple people who will be working on it later. Accordingly, it’s essential to use meaningful variable names, classes or ids so that you don’t have to put an extra effort into explaining the code.

2. Long lines of code: Try and keep the methods of your coding as short as you can. Long lines of code are not just hard to read but also going through all of it can make any person misinterpret the code. It’s much easier to write as well as test small units of code than the lengthy ones. Further, when your code gets passed on to someone else, they’ll know precisely what the method does. break down multiple operations into simple, smaller operations — this will massively enhance the readability of your code.

3. Responsive web design: Getting access to online content has become so comfortable in the past few years with the evaluation of smartphones in various resolutions. This also raises the issue for web developers to create seamless navigation to web content from all types of devices. There are numerous tools and applications to create a responsive web layout. Every language has its tips and tricks, but if you want to use an independent platform, then Bootstrap(getbootstrap.com) is one of the best frameworks to work with. While working with Bootstrap patterns and practices, you will get a responsive web design without going through any trouble. Materialize(materializecss.com) is another frontend framework similar to bootstrap which can be used for making responsive designs.

4. Be familiar with the new updates: Being a developer always needs you to have the right eye for what is trending in the industry and what are the changes we should adapt for good. Still, go for the solution which you think can work better in the future by evaluating the current enhancements. You have to understand the required changes and work according to the traffic and competition in the industry. Remember the stakes are always high in software development and there is always a chance of improvement.

5. Using outdated practices: In this ever-growing industry, there is always a chance of cyber attack. The more you get into it, the more loopholes you might find. You have to be more wary of dealing with this particular issue as it may affect your whole organization in many ways and also making the revenue go down. It’s one of your primary responsibilities to do a fantastic job in programming so that you don’t have to deal with any negative case scenarios. And, that will make you stand out of the crowd of hundreds of programmers out there.

Now that you know the mistakes to avoid, you’re on your way to getting started in the right direction. come straight to coding ninjas where our exhaustive courses on fullstack development will ensure you’re always a step ahead!

Why Blockchain is totally worth the hype?

After the world got well acquainted with ‘Internet of Information’ and ‘Internet of Things’, ‘Internet of Transactions’ was introduced, known to us as Blockchain.

Blockchain, the industry that evolved with the introduction of Bitcoin, has developed into today’s one of the most ground-breaking technologies that hold the potential to change the entire dynamics of every industry in the world. To put it simply, Bitcoin is an essential peer to peer version electronic cash, but there are more sectors where this technology is expanding itself.

But what actually is Blockchain?

source

A blockchain is a distributed and secure database, which maintains a growing list of records, called blocks, stored on a decentralised platform. Each block is immutable and contains a time stamp and the link to the previous block. Each user can only edit the section of blockchain that he owns. This database is secured by cryptography, and a transaction can be initiated only with the private key of the sender and public key of the receiver.

say-what

Basically, a lot of complicated terms, when put together, make this technology.

To break the complexity of this, let’s first understand how cryptocurrency works.

Here’s a quick view on how any cryptocurrency works:

infographics0517-01-1.png

Let’s assume that A has to send some amount of this digital currency to B. A initiates a transaction which is sent out to a set of parties for validation. Once these parties validate the transaction, the said amount is sent to B, and a block is now added to the blockchain, with the time stamp of the transaction and this block cannot be changed, which offers the simple implication that no party can deny this transaction. Which makes this technology a platform safer than any potential third party.

The reason that the world is eager to see more of this technology is: It offers the fascinating possibility of entirely eliminating the involvement of any ‘middlemen’ from all sort of transactions and contracts. The system of involvement of third parties to ‘seal the deal” has been prevalent since forever. This being the 21st century, the involvement of these parties had to be challenged; and blockchain did it!

While blockchain is all set to revolutionise the industry of finance entirely, it is looking forward to expanding to every industry known to mankind- in healthcare to store patient’s records, a census tool for government, identity verification- you name it and blockchain will find an implementation there.

Imagine how much manpower can be saved by this great invention, and that is the sole idea behind technology anyway!

Placement talk with Tarun Singh!

A place which made me a better Coder!

Tarun Singh 

His amazing experience and what he loved!

It was a very enriching experience for me. As a person who had just started coding, coding ninjas played a considerable role in making sure that I wasn’t a beginner for much longer. The online lectures of Ankush sir and Nidhi mam provided me with exceptional clarity on concepts that I wanted to learn. Coding ninjas helped me be a better coder.

Interview experience

It consisted of 3 rounds. It focused on topics such as graphs and recursion.

Advice to Current Students!

Never feel bad about failing. Persistence is the key to becoming a better coder.

How will you introduce Coding Ninjas to your friends?

Speaking about my course. I think if you want in-depth knowledge and understanding of concepts of data structures, dynamic programming etc. this is the place to start. The experience here is unlike any other place.

Thank you for your constant support and guidance!

Essential tips for people starting their career in Data Science

 

Technology now is emerging at a pace which we have never seen before. So is the need to interpret data flowing from the technology. This indicates that the candidates who are working with analytics and data science have to continuously keep themselves up to date with the current events in the industry after getting a professional qualification.

Learning data science can be challenging, but it is rewarding, too. Afterall, data scientist is ranked as one of the best job roles by Glassdoor since the past three years in a row. The need for highly skilled and smart people is going to rise with the rise of big data. Pursuing your career in data science without any guidance can be a bit confusing. Which tool to use? Which technique to use? The questions are endless.

Here are some tips which will help you if you’re about to start learning data science:

Choose the right role: Rather than recklessly jumping into a decision of which role to choose, take your time to understand the requirement of the role. From a data visualization expert to a machine learning expert or a data engineer, the role of a data scientist entails a varied amount of tasks. We would like to suggest a few things you can do beforehand:

• Find out the field that you’re close to from your past experiences or the most relevant role that you can excel.

• Talk to a professional who is in this field for a long time.

• Make someone your mentor from the industry to guide you and help you choose the right role for you.

Take courses: Now that you are all done with choosing the role, the next thing you do is to understand the role entirely. Since the demand for data scientists is highly increasing, there are a lot of courses out there to look forward. You have both, paid and free classes. Now, remember, while taking online courses to be sure if it has good reviews. You can also get help from your seniors to know which direction can be beneficial. Even when you take up the course, go through it actively. Engage in every coursework, assignment and all the discussions happening around the course.

Choose a language/tool: This might be the most commonly asked questions from a beginner that which language to choose and with which tool to stick. The answer is simple, go with the one that you are familiar with or if you don’t have had any experience with coding yet then go with the simple one. After all, tools are just a means for implementation; the primary thing is to understand the concept.

Join a peer group: After choosing a language to continue with the next thing you should do is join a peer group. Not only the group members help you study but also keep you motivated throughout. Starting your career in data science can be intimidating but having a bunch of people doing the same thing besides you can make it much easier.

Even if you don’t have such people around, you can always join a massive online course and talk to people online. Trust me; there are a lot of people in it.

Focus on practice and building applications: During the course try and have a practical approach towards the projects assigned rather than theoretical. To stay on the top of the skills, you have to keep yourself updated with all the new tools that are continually coming out. Start with easy projects first.

• You can start with the projects assigned to you in the course.

• Explore the projects which are already solved by the experts.

• Instead of following a theoretical approach, look for online tools that help you code as you learn.

Follow the right resources: It is essential for a data scientist to know that the skills sets that are applied to be a data scientist are constantly shifting. So to keep a pace with that, follow the most influential professionals of this field. Read their blogs, attend seminars and meetups arranged by data scientists. As it is one of the most searched topics nowadays, scientists are actively participating in updating their blogs and updating us with the recent happenings. Make sure you don’t follow the wrong resource as it harms your career.

Work on your communication skills: Working hard on your communication skills might not associate with the fact of being a data scientist. But actually, it is one of the most important aspects as you have to communicate with a lot of people from the industry and within the organization, as you are the one who will keep them in the loop of the growth of your company. And to do that you have to communicate effectively.

Like we said earlier, the demand for upskilled data scientists is only going to increase with time. So, if you are planning to explore the career, there couldn’t be a better time than now. And, you’re just in luck, because we at Coding Ninjas offer extensive course on data science. Let our course be all the guidance you need to succeed in the career of your choosing!

Why hire from Coding Ninjas?

“You can have the best strategy and the best building in the world, but if you don’t have the hearts and minds of the people who work with you, none of it comes to life”.–Renee West

The present workforce of a company says a lot about the future the company holds. Nowadays, companies are known to spend a lot on the talent acquisition, and the training of the new recruits, and it makes sense for the companies to invest so much, given the fact that this human resource is going to be the vision holders of their future.

Recruiting fresh talent as interns or as full-time employees has always been the hardest challenge for the recruiters and campus placement requires a lot of time, energy and investments. Most of the companies hunt for talent from campus to campus, picking out the finest ones from the crowd by an initial screening test, followed by a couple of interviews, which is grilling for the interviewee and exhausting for the interviewer- and this same process in colleges throughout the country, OVER AND OVER AGAIN!

And, this is how much a company puts in to acquire new talent on board!
So, why recruit from Coding Ninjas?

The answer is simple- TO SAVE ALL THAT EFFORT!

Coding Ninjas has been mentoring the most excellent lot of students from various colleges for years! The training provided here, at Coding Ninjas is aimed to shape programmers who can think, explore and execute.

They are evaluated at every step, they are guided at every level, and they are taught to challenge themselves at every step. The students here are grilled at every stage to ensure that they fit in well to the industry standards.

So, the company gets to choose from the finest of the fresh talent out there!

Instead of choosing selected colleges to hire from, the company gets to choose the selected ones from a broader set of colleges!

And let’s not forget the cost cutting in the talent acquisition department! 😉

So, this is safe to establish now that Coding Ninjas is a one-stop platform between the recruiters and the talent!

You can explore more about the courses on our website.

Data Science and all that it encompasses

To understand what all does data science encompass, we’ll have to dive a bit deeper from the surface. First of all, let’s keep some of the facts clear that Data Science is not a part of academia nor it is mostly statistics/analytics. The major part of being a data scientist is to extract information from the data, analyze it, and if a problem arises, you build a tool accordingly and solve it. It mainly includes a little programming skill, some statistical readiness, some visualization techniques and of course a major sense of how a business works.

It is a kind of investigation in which the Data Scientist peeks into the data transmitted in the past, analyses it and then comes up with a tool/model to rid of the problem permanently.

So, here are a few things you have to do if you are thinking to enter the world of data, statistics, and information:

Data cleaning: Typically when you start gathering data and extract all the information you can get, there can be a huge amount of data that is not usable at all. It means, even if you keep all of the correct information with you, it creates a lot of mess. This is the part where you have to sort all the information in such a manner that the resulting combination makes sense. Fixing them and making sure that the problem will be fixed automatically in the future is what the Data Scientist usually does.

Data Analysis: This is not the part where you prepare tables or charts to analyze the situation or the problem. This is where visualization takes place. This is the creative part where you get a chance to show your abilities to detect why the particular problem is arising or how can you prepare a model to solve it universally. Since Data Science is one of the most discussed topics nowadays, people are always trying to find newer solutions to business issues. You will be playing a major role in making decisions more scientific and helping business achieve effective operation.

Modeling: After you have extracted and analyzed all the data, now is the time to evaluate and tweak models. However, there are a lot of tools introduced in the market to solve regular issues faced by business organizations. Still, there is a huge possibility of a problem to arise that only a Data Scientist can foresee. We can say that this step is one of the most complicated one until now but here is the point where Data Scientists can go back to all the data they have put together and work on new features to create an out of the box model. Besides having powerful algorithms to solve any issue, there are times when nothing works. Only a Data Scientist can keep working on it to find out new solutions.

Working with Data Science

Working with Data Science might sound really interesting, but there are certain qualities that you should possess to work in this industry. You should have proper knowledge of statistics and mathematics including various databases and the use of different tools accordingly. A proper skill set of data munging, data cleansing and data transformation is needed. Finally, visualization comes through which you definitely need to have to be a good Data Scientist.

Below is the list of a few Data Science tools you must know from the very beginning:

R Programming: R is a statistical programming language that comes with an array of features specific to data scientists. It is one of the strongest and most prominent languages when it comes to data analytics and machine learning.

SQL: SQL, short for structured query language, is a structured programming for working with relational database management systems. SQL follows a certain format of rows and columns that depict a huge amount of data. While many of the operations are shifting to the NoSQL databases, SQL still manages to be one of the widely used tools for data manipulation and interpretation. SQL is extensively used by database administrators and developers alike.

Python: Python is an object-oriented programming language that is extremely high-level and versatile. Its use cases include a variety of applications, especially in the domain of machine learning and data science. Python comes with a huge set of readymade libraries which makes it a promising choice for data scientists.

Hadoop: Hadoop is used to process huge amounts of data and is one of the most powerful tools for that. Being open-sourced, Hadoop has an extremely vast and active community of developers. It helps you store, computer, deploy real-time analytics among things on big data through its ecosystem of tools.

SAS: SAS is one of the most powerful business analytics and intelligence tools. It is a software suite useful for extracting, analyzing, and reporting data to derive valuable business insights from it. SAS includes a whole set of tools required for working across different steps in converting raw data into actionable insights.

Tableau: Tableau is by far the most powerful data visualization tool. With analytical and reporting capabilities, Tableau is for you even if you don’t have a lot of technical knowledge.

Those were the basics of everything that comes under the umbrella of Data Science — including most of the important tools used in the industry. Also, did you know that Data Science is branded as the sexiest job of the 21st century? Yup.

So, if you feel data science is your calling and all you’re lacking is good supervision, let’s tell you — we’ve got you covered. Come over to Coding Ninjas where our online course on Data Science takes care of everything you need in order to start on the correct track!

Node.js vs. Python for backend development

It is time; at last, to discuss the fact about the two most deliberated and used backend programming languages — Node.js and Python. As they both play a crucial role in the same area of development sometimes it becomes confusing for the programmers to choose with which language to start with. Well, we are here to solve that one for you. Let’s start with understanding the pattern both languages use to make things easy for the client as well as the server.

What is Node.js?

Node.js is an open source runtime environment to write server side applications that is based on JavaScript and runs on the V8 engine. It uses a non-blocking, event-driven I/O model. It allows programmers to create real-time applications and was designed with push-based architecture in mind. Node.js is mostly preferred because of the fact that the language works on JavaScript- an already extensive tool but also the efficiency that allows you to build highly scalable web applications. It can be run on OS X, Microsoft Windows, and Linux operating systems.

Pros of Node.js

· It ensures the use of the same language both on the client and server side.

· Faster web page loading time

· Uses a single threaded model with event looping. This type of event mechanism benefits the server to respond in a non-blocking way.

· There is no buffering in Node,js as applications output the data in pieces.

· Easy to monitor.

· The Node.js developer’s community is a very active and huge group of developers who are constantly contributing to develop the particular language.

We are grateful to the JavaScript developer’s community for their input because we have the access to a ton of ready solutions/codes.

Cons of Node.js

· Debugging

· The fact that it is very similar to JavaScript, so the developers who are already working with JavaScript finds it a bit of a overwork.

· Node.js’ API changes frequently which makes it unstable. Sometimes programmers have to change the existing code to make it friendly with the updated version of Node.js.

· It still doesn’t support multi-threaded programming yet. Heavy computations might lead to decrease the level of performance.

What is Python?

Python is an object oriented, high level programming language with active semantics. The interesting fact about Python is, it works as a glue language to connect existing components together. It supports modules and packages, which encourages program modularity and code reuse.

It supports multiple programming patterns, including object-oriented programming, functional programming, or procedural styles. Unlike Node.js, Python cannot translate to computer-readable code before its runtime.

Pros of Python

· Python gets the job done in fewer lines of codes than other similar programming languages.

· It can give the same output as PHP but much faster.

· Developers have access to high functionalities and extensive library support.

· Python offers a very easy maintenance as any kind of errors can be resolved within minutes.

· As it has been around for a really long time, programmers have the access to high functionalities and extensive library support.

Cons of python

  • Since python is interpreted, it often results in slow performance. This problem can be avoided if high speed is not the actual requirement of the project.
  • Python has design restrictions. Although this is easy for programmers while coding, it still can raise runtime errors.
  • Python database access layers are underdeveloped as compared to mostly used Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC). Accordingly it is less used in huge enterprises.
  • This particular language can take some time to catch up if some of the developers on your team aren’t familiar with it.

Here are a few points for you to actually understand the difference between the two languages for backend development:

· Right at this moment Node.js is the ideal language to perform real time web applications and on the other hand Python is not suitable for real-time environment.

· Node.js is best suited for smaller projects with a lesser memory while Python is one of the best options for developing larger projects.

· Node.js uses JavaScript as its base language and Python uses PyPy as interpreter.

· For asynchronous programming, Node.js is preferred as Python is not exactly the best option for it.

· As Node.js is pure JavaScript, its basic remain simple for the programming team. Here Python takes over Node.js as the developers need to write lesser lines of code and can get the exact result.

· Also Node.js lacks the clean coding standards while Python is subtle in its way and can do the same thing PHP code can.

· Node.js supports callback while Python doesn’t which makes it way simpler.

This should help you make a well informed choice. And now that you’re on track with what both of these languages entail, let’s present to you the Python and Node.JS courses offered at Coding Ninjas. These courses start from ground zero and ensure that you’re on the correct path for the rest of your career!