Here’s what distinguishes a great software engineer from a good one



Programming is an art. It is the art of understanding and assessing the issue at hand and designing and developing a solution that’s efficient, flexible, and scalable. And just as the art of two artists isn’t the same, so the style and approach of two programmers also vary greatly. There are good and bad programmers, and then there are great programmers. According to stats, the productivity of excellent programmers is three times more than that of average or good programmers and ten times than that of a bad programmer! See the vast difference?

So, what do you think sets these masterminds apart from good and bad programmers? It is their small and intangible traits that have helped them emerge as the best players in the game. Let’s look at the seven traits that distinguish a great programmer from a good programmer!

  1. Optimistic Attitude

The foremost trait that defines a great programmer is a positive outlook on life. These are the people who believe in themselves and their abilities to develop quality products for their clients. They care about the client and aren’t afraid to go that extra mile to ensure that the end product is unique and effective. Great programmers always strive to deliver on time and never puts his/her ego before the suggestions and demands of the client. They know how to put a positive turn on everything.

  1. Top-notch Time And Task Management Skills

Another quality that sets excellent programmers apart from the crowd is their sense of time and a strong work ethic. They understand the fact that time is of the essence and they must deliver the product to the client within the stipulated time which, in turn, helps them gain customer loyalty. This, they achieve by maintaining a well-planned work schedule and setting clear goals for a particular project. Due to their exceptional time and task management skills, great programmers are extremely reliable.

  1. Excellent Communication Skills

To be able to develop a cutting-edge product, a programmer must possess excellent communication skills. He/she must understand the specific requirements of the client and communicate their proposed solution across to them in a lucid and simple manner. Not just that, great programmers must also be able to answer any and every query of the client and explain to them the relevant concepts to maintain absolute transparency. And if you are multilingual, it’s a win-win!

  1. Quick To Learn

Most of the best programmers in the world are brilliant self-learners. They read a lot to continually keep themselves updated with the latest technological innovations. Learning about new things and concepts excites them. Due to this reason, they know how to remain calm even in the face of a serious issue or bug in a code. They will try different methodologies and approaches until they finally reach the ideal solution. Persistence is the key here. This is precisely how great programmers learn – by taking on new challenges every day.

  1. Extensive Technical Experience

Being in the field for a long time and constantly experimenting with new technologies is what goes into the making of a great programmer. With every new technological tool and approach, the scope of expertise and knowledge base of a programmer both deepen and widen. An experienced developer comfortable in working with the latest work methodologies such as agile and also with task management software like instance, Toggl, Trello, Jira. This is what clients seek – a programmer with flexibility and a wide knowledge base.

  1. Team Player

Great programmers do not shy away from taking help of others. Also, when the situation demands, they can work well with others on their team. They know that sometimes they need to work in close collaboration with other developers and programmers to build a high-end product. If need be, these programmers are ever-ready to help their fellow mates, hence, their ‘greatness’.

Although these qualities may seem commonplace, they’re rare to find in real-world scenarios. Programmers with such a great sense of responsibility, work ethics, and flexibility are indeed difficult to find, but not impossible. The key is to train yourself to learn new things, follow a strict code of discipline, and develop good time and task management skills.

Are you ready to step up to the game?

Ruby and Ruby on Rails: How do they differ?



If you are a part of the programming world, you must have heard about Ruby and Ruby on Rails. Today we’re going to talk about the evolution of both Ruby and the Rails framework and the unique purpose they serve in the domain of Web development.


Ruby is an object-oriented programming language that dates way back to 1995. It was developed by Yukihiro Matsumoto. Although it is written in the C programming language, Ruby also contains certain characteristic features of other languages like Perl and Python. Ruby comes loaded with useful features and is extensively used for Web app development. With a simple and neat syntax (just like C and Perl), Ruby is easier to both understand and write, and is hence, a great language choice for beginners.

Despite fashioning a simple and elegant syntax, Ruby was not really a hit with programmers in the past. The real moment of fame for Ruby came with the development of the Rails framework that was built on the core aspects of Ruby. It allows for the smooth and convenient integration of high-level abstractions (for instance, metaprogramming) which further helps in developing a domain specific language.

Ruby on Rails

Ruby on Rails (RoR), better known as Rails, is a web application framework that was developed by David Heinemeier Hansson. While he started developing the Rails framework in 2003, it was made public only in 2004. Written in the Ruby programming language, the Rails framework is based on the MVC (model view controller) architecture. The specialty of the MVC architecture is that it allows data to be delineated from a UI to offer varying possible views of the data. Apart from this, the Rails framework also supports RESTful API. Essentially, Rails was developed to function as a support framework for web application development by facilitating seamless integration of Ruby with JavaScript, HTML, and CSS.

The Rails framework strictly abides by two fundamental concepts. The first one is the DRY (don’t repeat yourself) and the second one is the COC (convention over configuration). Don’t Repeat Yourself, as the name suggests, stresses on the fact that one should never have to repeat the same lines in a code again and again. COC ensures that a code is concise and readable as in it should not contain big configuration files. Instead, it allows you to use a set of default configuration files. Both these principles make sure that a code written on the Rails framework is clean, well-designed, and scalable.

How Is Ruby Different From Ruby On Rails?

Here are the basic differences between Ruby and the Rails framework:

  • Ruby is a programming language that was built on C. Ruby On Rails is a web application framework built on Ruby.
  • Ruby is mainly used to build and develop desktop applications. As mentioned before, RoR is used to develop Web-based applications.
  • While Ruby drew inspiration from languages like C, Perl, and Smalltalk, RoR took inspiration from PHP as well as Django and Laravel of Python.
  • At the core of Ruby lies the principle of user interface design whereas RoR upholds the principles of DRY and COC.
  • The syntax of Ruby is similar to that of C, Perl, and Python. The syntax of RoR is similar to Laravel in PHP, Django in Python, and Phoenix in Elixir.

To conclude, it can be said that both Ruby and Ruby On Rails have specific features that are best suited for particular domains of application development. However, it is advised that before breaking the ice with Ruby On Rails, it is essential to building a good foundational knowledge of Ruby. and if you’re ever stuck in between the two, carefully assess the requirements of your project at hand, and your dilemma will be solved!


A day in the life of a software engineer

a day

If you are aspiring to be a software engineer, at some point or the other you must have wondered about the question – how does a software engineer spend his/her day or rather, what constitutes a typical day for a software engineer?

First of all, let us break the myth that a software engineer enjoys a ‘typical’ day at work because when there are new issues cropping up by the minute, every day is a new challenge that you’ve to face head-on. Now that we’ve established that, let’s see how a software engineer spends his/her day.

7 AM: The day begins with exercise and coffee!

Getting up early and starting the day with some exercise ensures that your energy levels remain high throughout the day. Needless to say, software engineers require high levels of energy to be productive all day long. After exercise and the morning shower, it’s time to further boost the energy levels with coffee/juice and a healthy breakfast.

8 AM: Commute

This is the time when productive software engineers use to catch up on their daily work schedule by checking the mail for pending tasks, issues, meetings, and so on. Once he/she’s done catching up with everything they need to do throughout the day, they usually put their headphones on or play soothing tunes (yeah, you’re right! It’s almost always classic rock or soft metal or trance music!) on the car stereo and enjoy the ride to work. Since most software engineers have the ability to multitask, they can often find solutions while listening to music or at least chalk out the approach through which a particular issue can be solved.

9 AM – 10 AM: Strategize

The one hour after reaching office is a very crucial time of the day since this is the time to prioritize the day’s tasks and strategies as to how to approach each task. When it comes to pending tasks, usually a software engineer swears by the ‘cliffhanger’ wherein he/she makes a detailed note outlining his thinking process pertaining to that specific task. This helps one to start where they left off without hampering the flow.

10 AM: The actual work commences!

After the deliberating and strategizing, a software engineer gets into the problem-solving mindset and starts solving the priority issues first. It is important to coordinate with the product manager, team lead, and teammates to ensure that a project is complete in time and can run smoothly. After fixing the bugs and bottlenecks in code, it is essential to run and test them again for any possible errors. 10 AM to 1 PM is usually a very busy time for a software engineer since priority issues capture their complete attention during this window.

1 PM: The much-needed break – lunch.

Contrary to the stereotype that software engineers are total nerds and introverts, they often look forward to lunch break and other short breaks between work so they can socialize with other people in the office. Networking guys! Software engineers are strong supporters of networking and hence, lunchtime is when you’ll get to see them enjoying humorous and engaging conversations with each other over delicious food.

2 PM – 5 PM: Coding, and coding some more!

Lunch break is usually followed by client calls and office meetings. After meetings, software engineers return to what they do best – code. Most of the afternoon goes in writing code, fixing minor bugs, and dealing with day-to-day client support queries. If these problems are sorted out for the day (a rarity indeed!), a software engineer makes it a point to stay updated with the latest technological updates and innovations in the IT sector by reading up on informative articles, watching educative YouTube videos and tutorials, and so on.

6 PM: Tend to emergency issues.

The day’s far from over and emergency issues can always emerge out of nowhere. Obviously, they need looking after. Getting on a call with the client or the onsite guy/girl to learn about the issue and immediately start working on it.

7 PM: Call it a day!

After almost nine hours of slogging with codes, bugs, client calls, and office meetings, it’s time to call it a day and return home. If you’re living with your family and kids, great! If not, you’ll probably be cracking your head on what you’ll be having for dinner. While returning back after a tiring day, software engineers again seek refuge in music to get out of the work mindset and ‘switch on’ their personal life.

8 -10 PM: Home sweet home.

This is the time for rest, catching up on that favorite Netflix show, or maybe spend some quality time with friends and family. Have a wholesome dinner and binge watch TV series or movies a little more.

11 PM: Off to bed!

Before going to bed, it’s necessary to check work emails and reply to important ones. Another productive day is over and it’s time to sleep for you need to get up rejuvenated the next day, ready to take on some new challenges!

So, that’s precisely how a software engineer spends a day. Although not every day is the same and not every software engineer spends his/her day exactly like this, but we hope this gives you a pretty much rough idea on how a day goes by in the life of a software engineer.


Coding will always be the most important job skill! Read to know why.


As the technology rapidly progresses towards advanced domains such as Artificial Intelligence, Machine Learning, and Deep Learning, coding keeps gaining more and more momentum. This fact is backed by statistics too. According to Glassdoor, coding skills made up eight of the top 25 jobs in America in 2016. Then again, Burning Glass found that out of the 26 million job postings in 2015, nearly seven million job openings were for the positions that require coding skills and also that jobs requiring coding skills pay more – extra $22,000/year – than jobs that don’t.

According to the 2016 report by Burning Glass, the top coding job roles are:

  • Information Technology (IT) professionals
  • Data Analysts
  • Artists and Designers
  • Engineers
  • Scientists

So, why exactly has coding become so important in the job sector today? Here are four reasons why!

Coding Is Everywhere

Coding is no longer limited to the tech world, but it has worked its way into other parallels of the industry such as finance, business, healthcare, and so on. Today, business and institutions across the various sectors of the industry are always looking for talented coders who can simplify and smoothen the functioning of an organization and drive innovation. Then there are the tech giants like Facebook, Google, and Apple where the demand for young and talented coders is always high. And do we even have to remind you of the fact that the professionals working for these companies are paid handsome salaries and perks?

Automation Cannot Rule Humans – Not Anytime Soon

While it is true that the rapidly spreading wave of automation is threatening a number of conventional jobs, coders have nothing to worry about. Although machines are capable of performing certain tasks independent of human control, first they need to be trained and taught to do so. And who does that? Coders, of course. Coders bear the responsibility of creating such algorithms and code that can be fed into the machines for them to learn from experience and behavior. Thus, no matter how greatly AI evolves, someone always has to be there to show it the right way.

There Always Something New To Solve

Problem-solving, that’s what coding is essentially about. Coders create functional code and algorithms to solve myriad problems to enhance the overall efficiency and functionality of a software. Once a particular problem is solved, it doesn’t mean that a coder can now rest – a new problem only lurks around the corner and crops up out of the blue. So, there are always going to be problems to solve. Moreover, building a software is an inclusive process – different teams are involved in the crafting out the various pieces that go into making a software, thus, turning the process of software development into an art.

Understanding Big Data

While the world raves about Big Data and its importance, how many of us really know how to leverage Big Data to its optimum potential? Big Data is one complicated and intricate web of data that can only be demystified by data scientists and data analysts, after which coders take up the job of turning the extracted information into something valuable – a functional code. With Big Data gaining more and more important by the day, the job of coding is becoming all the more relevant in the industry.

One of the best thing about possessing coding skills is that you can either get into a career that requires coding or you could also morph into other jobs that do not require the skill such as an entrepreneur or a designer. The only thing different about you will be that you’ll have an edge – coding skills – that’ll enable you to accomplish a host of tasks yourself including website building and designing, enhancing your products/services, and much more.

So, how about giving it a try?


5 critical tips to learn programming faster


In today’s tech job market, coding has emerged as one of the hottest and most popular skills. Aspiring youngsters from around the world are rapidly leaping into this field, attracted by the myriad opportunities and salaries that coding jobs promise. However, this only means that the competition is higher and tougher than ever. Thus, to get on top of the ladder and be hired by the magnates of the tech world, you must keep your coding game on point!

The key is to ace programming. You’ve got to be a fast, yet efficient learner. Here are tips that’ll help you learn programmer faster!

  1. Get Handsy – Learn While You Write

No matter what discipline you choose to pursue, learning is always better when accompanied by hands-on practice. Although while reading up on a particular coding concept, it may seem very easy to you, putting it to a real-world use case is an entirely different thing altogether. As a beginner, you’ll often find yourself stuck in situations where you can’t remember a specific detail of a particular syntax if you don’t practice by implementing what you’ve learned by writing your own code.

  1. Build A Strong Knowledge Base Of The Fundamentals

If your foundation is faulty, you’ll never be able to perfect your programming skills. So, it’s important to master the fundamental concepts of coding such as variables, errors & exceptions, queues & stacks, streams, callbacks, and then move on to more advanced concepts such as reactive programming, declarative programming, imperative programming, and so on.

  1. Practice Coding By Hand

Although it may sound like a medieval technique now that we are super reliant on computers, however, trust us when we say, writing code by hand is one of the best practices every aspiring programmer should incorporate in his/her learning routine. When you start coding on pen and paper, you’ll see that it requires a lot of precision and planning. Also, when you write the code by hand, you can always check for errors and correct it without even having to run it first. This habit might just become a boon for you later in life when you are going to sit for job interviews. Interviewers often ask candidates to write the codes on paper or a whiteboard.

You wouldn’t want to miss out on a job prospect just because you cannot code on paper, do you?

  1. Don’t Hold Back In Asking For Help

Every programmer needs help, and that’s why there’s a whole community of developers and programmers dedicated to helping fellow programmers in times of need. If you find a bug in your code, be sure that someone has already faced the same problem at some point in time. Reaching out to others and asking for help from them not only allows you to learn different ways to solve coding problems but also to expand your network. Platforms such as Stack Overflow, Reddit, Hacker News, and SitePoint, among others.

  1. Explore Online Resources

In the beginning, it is very natural to get stuck. You might find certain concepts much difficult to understand than others. But don’t worry! There’s plenty of helpful and informative stuff online. You can try out learning platforms such as Codeacademy, Codewars, edX, Coding Ninjas, Coursera, and Udacity, to name a few.

  1. Try Tweaking The Sample Code

If you want to become an expert programmer, just reading the sample code won’t suffice. You must play and experiment with it. Try making minor modifications to the sample code and run it. See how those small changes alter the functionality of your code. Doing this will help you understand what works best for a code.

These six tips will surely help you learn to code faster and more efficiently, while simultaneously allowing you to improve your programming skills. Be patient with yourself. Don’t give up at the slightest of failures. Instead, try to come up with better solutions with every new try. Don’t view programming as a task, view it as a fun challenge and you’ll see the entire learning process has become more exciting.

Happy coding!


Think like a programmer: Inside the mind of an expert programmer!


Have you ever wondered what goes on inside the mind of a developer or a computer programmer? How do they think and approach problems? Well, today’s post is precisely about that – the mindset of a programmer!

When you dive into the world of software development, you must possess one quality – the programmer mindset. In simple terms, to be a programmer, you’ve got to think and act like one. So, what exactly does the programmer mindset mean? Keep reading to know the secrets!

The Inquisitive Mindset

  1. What Seems To Be The Problem?

The brain of a programmer is somehow wired in a way that he/she is perpetually on the lookout of a problem to solve. Whenever programmers come across coding problems or issues, they’re like “So, what exactly seems to be the glitch here? I need to find out!” An expert programmer will always view a problem from many possible angles and try to delineate the issues one by one.

  1. How Do I Fix The Problem? How Can I Make It Better?

Once the problems are identified, a programmer then engages himself/herself in trying to find the best possible solutions to the problems. However, that’s not all – the end goal is to enhance the code and make it better by following the three-step rule:

  • Fix the problem – What will be the fastest solution to get the code to run smoothly?
  • Do it right – How to clean the code and turn it into a technically correct one?
  • Boost it – How to optimize the code?

The Learner’s Mindset

  1. Understanding The Code

Programming is not just about solving problems ceaselessly but also learning new things in the process. A programmer must always be open to learning. Before solving a coding problem, it is crucial to read the code carefully and understand its structure and functionalities. Only then will you be able to find the best possible solutions to specific problems and also tweak and optimize the code accordingly.

  1. Experimenting

Experimenting with new concepts and tools is a vital part of the learning process. When programmers learn a new concept, very often they experiment with the concept and try to see how it can enhance or ruin or tweak a code’s functionality. That’s how one gets to know what works best for a code and what doesn’t.

  1. Attention To Detail

When creating a code to serve a specific purpose, every little detail matters. In the most basic sense, a code is merely a set of instructions that are fed into the computer to get it to perform a certain task. One little mistake or a wrong move within a code can have a massive impact on it and can even ruin it. Thus, paying attention to detail is the mark of a great programmer.

An Artist’s Mindset

  1. Striving For Perfection

Software development is very similar to art. Just as an artist brings an image to life with his/her imagination, handwork, and colors, so a programmer, too, builds a code to bring life within a computer, which without code and software is nothing but a lifeless machine. An excellent programmer never stops at the moment when his/her program starts running smoothly; he/she tries to find out ways in which the program can be made even better. Naturally, this involves a lot of practice and perseverance to get it right and still find grounds to improve upon. A programmer’s craft is a pursuit of perfection.

  1. Passion

Until and unless a programmer is driven by a strong passion to find innovative solutions. This passion is what drives a programmer to write codes that are clean, readable, logical, and efficient. Creativity is a key skill here. A programmer uses his/her technical knowledge and the limited set of tools at his disposal to figure out how to solve problems and build a useful code, all the while learning new things. For a passionate programmer, coding isn’t just a task, it is also a fun hobby to indulge in.

Programmers are well aware of the fact that their profession and field of study is a dynamic one and that nobody is perfect – there’s always scope for improvement. Hence, they never hold back from asking help from their extended community or programmers and developers. Today, there are many platforms where programmers can connect with each other and share their knowledge with the community members, such as Stack Overflow, Reddit, CodeProject, and much more,  thereby enriching the developer community as a whole.

Yes, a programmer’s mind is that simple and creative at the same time! Do you think you have it in you to become a programming legend?

Coding Hacks for Non-Developers




Yes, coding is extremely exciting, but it is challenging too. It requires a certain degree of expertise in Computer Science and an air of flair in computer programming. But if you think that the benefits of coding are exclusively limited to tech geeks like software developers or coders, you are absolutely wrong! Everyone can benefit from coding by possessing a basic knowledge about coding concepts and programming languages. Whether you are a retailer or marketer, coding can prove to be of immense help to you.

So, listen up all you non-developers out there, here are some coding hacks to make your life easy!

  1. Code It Up!

The foremost coding hack has to be learning and grasping the coding lingo, that is, gaining a basic knowledge about the fundamental coding concepts. Begin small by learning coding terminologies such as tags, brackets, properties, variables, modules, class, errors, streams, and so on. Then move on to more advanced coding concepts like source code, style sheets, queues, stacks, linting, callbacks, task automation, and reactive programming, to name a few. Finally, dare to take up a programming language and master it like a pro!

Learning these things will not only expand your knowledge base, but it will also help you perform specific tasks such as building your company websites and troubleshooting problems all by yourself!

  1. Explore The Source Code

While surfing websites and web pages, you must have noticed that whenever you right click on a web page or site, you can see the option “View Page Source.” Did you know that by further clicking on this, you can see the source code of any website or webpage?

You can use this to your advantage – by exploring the source code of other websites, you can see how different people are managing their website and designing their functionalities. By doing so, you can see your learnings materialize before your eyes in real-world use cases. Usually, the specific functions of the lines contained in the source code are given beside the code. You can carefully examine these to understand how to build a code to attain a specific function.

  1. HTML Is The Way To Go!

Not only is HTML one of the earliest coding languages but it is also much easier to master (as compared to other high-level languages today). And the best part is that today, you just have to go to the Internet and you’ll see an array of helpful and informative tutorials on HTML.

There’s absolutely no need to rush – take baby steps and learn HTML concepts one at a time. This will help you to gain clarity over a particular concept before you jump to the next, without crowding and overwhelming your learning and understanding abilities.

  1. Search Forums Are Your Friend

While writing a code, you might often find yourself getting stuck at places. Don’t be disheartened, for it’s completely natural. It takes a lot of time, patience, and hard work to attain perfection. In case you ever get stuck, let Google help you out. There are many, many search forums on the Internet and believe me, whatever problem you are facing, someone somewhere has faced it too. By seeking help on search forums, you can learn some of the best coding practices from the masters and simultaneously expand your network by connecting with new people.

  1. Practice Your Way To Perfection

This age-old advice never gets old. The more you experiment with coding, the better you get with time. The Internet is full of helpful resources and platforms where you can find both coding problems to solve as well as the best ways to solve them. You could also create an unpublished page on your website and experiment with various aspects of coding on it. For instance, copy another site’s source code on the page and try manipulating it or you could also write your own code. The best part about practicing like this is that you never have to worry about crashing your website or ruining its functionality.

Now, go on, utilize these hacks to make your life more convenient, and dare to create something innovative.

Happy coding!


Want to get started with a career in ML engineering? Here’s how!


While the concept of Machine Learning (ML) dates back to decades ago, it has come to the global spotlight only recently with the upsurge of Data Science and its related concepts like Artificial Intelligence, and Artificial Neural Networks. Today, magnates of the business and IT world such as IBM, Google, Facebook, and Amazon are leveraging ML technology in their products and services to foster innovation. This has created a huge demand for skilled and trained ML professionals both in the business and IT sphere. According to LinkedIn research, today, the number of ML engineers have increased by 9.8 times than it was five years ago.



So, folks, this is the time to make it big as a Machine Learning engineer! But before you do, you must first understand what it takes to make a successful ML engineer.

  1. Develop Coding Skills

Learning to code in a specific programming language is a must for becoming an ML engineer. So, you have to pick one programming language and master it before moving to another programming language. Python is currently one of the most favorite programming languages of developers around the globe. Apart from this, you could also try learning Java, Ruby, C, C++, Perl, and Scala.

  1. Online Courses

Once you master a programming language, you must develop data analysis skills. You have to learn Statistics, data structures and algorithms. Lucky for you that now there are numerous online platforms offering courses on data analysis and statistics. Here are some courses that you could opt for:

  • Intro to Descriptive Statistics (Udacity) – This course focuses on communicating information about datasets.
  • Intro to Inferential Statistics (Udacity) – This course focuses on data set analysis.
  • Getting and Cleaning Data (Johns Hopkins University) – It specializes in training students on how to optimize data sets.

After data exploration, it’s time to dive into the world of Machine Learning. One of the best ways to learn and master the discipline is to enroll in online courses. There are numerous informative and helpful online courses offered by reputed universities as well as trusted online platforms:

  • Feature Engineering for Machine (Udemy)
  • Deep Learning Specialization (Coursera)
  • Cognizance: Machine Learning Course (Coding Ninjas)
  • Machine Learning (Stanford)
  • Learning from Data (Caltech)
  • Practical Machine Learning (Johns Hopkins University)
  1. Get A Certification

While formal education and degrees (graduate/postgraduate in CS or engineering) are necessary, getting relevant certifications or accreditations will provide you an edge over your competitors when you apply for that dream ML job. You can boost your chances of getting hired by choosing among these excellent certification programs:

  • Artificial Intelligence Graduate Certificate (Stanford).
  • Certificate in Machine Learning (University of Washington).
  • A Certification of Professional Achievement in Data Science (Columbia University).
  • CSCI E-81 Machine Learning and Data Mining certification (Harvard).
  1. Get Handsy – Work On Machine Learning Projects

Haven’t you heard, ‘Practice makes a man perfect?’ Machine Learning is no exception to this age-old rule. Working on your own ML projects is a great way to hone your skills and understand both your strengths and weaknesses. You can try out tools such as Scikit-learn, Awesome Machine Learning, and PredictionIO, to explore and create basic ML projects. GitHub is a great place to look for ideas for ML projects.

  1. Take Up Challenges

There are various online platforms that host ML challenges including Kaggle, RAMP, AutoML Challenge, Innoplexus Online Hackathon, and MLflow, to name a few. Make it a point to participate in these challenges and competitions. You will not only learn better but you will also gain experience and become a faster and more focused coder.

  1. Get Hands-On Training With Machine Learning Internships

Although you can learn a great deal from online courses and ML competitions, they aren’t enough to teach you about the business-specific ML skills. This can only be gained through ML internships where you’ll get to solve real business cases with ML tools. Internships will not only help you get the experience you need to get started in the industry, but they will also allow you to understand what kind of approach you need to take for the real world.
These six steps should be enough to transform you from a rookie to an ML pro, provided you are diligent and dedicated towards it. Learning something new is always challenging, however, just remember – “To begin, begin.”

Dynamic programming and everything you need to know about it


If you are trying to make it big as a coder, you’ve probably been advised by coding Gurus (more times than you can count) that mastering Dynamic Programming (DP) is a must. Don’t cower already, it’s not rocket science! It just needs a little patience and dedication on your part to learn and master Dynamic Programming.


And that’s precisely why we’re here to guide you through the concept of DP!


First, let’s start with the fundamental question.


What Is Dynamic Programming?


Developed by Richard Bellman way back in the 1950s, Dynamic Programming is a combination of computer programming and mathematical optimization aimed to avoid repetitions. Essentially, DP focuses on breaking down an optimization problem into smaller fragments of simpler sub-problems and stores the solution of all the subproblems. Thus, by remembering the partial results of these subproblems, Dynamic Programming can help avoid coders and programmers to avoid repetitions within their code. Unlike the naive approach that takes up a significant amount of time, DP allows you to solve an array of programming problems in O(n2) or O(n3) time.


Still confused? Jonathan Paulson answer will definitely demystify Dynamic Programming for you with this Quora answer.


Now, let’s talk about another crucial aspect of DP – Patterns!


When talking about DP, it is essential that you learn to recognize the common patterns of coding problems so that you can leverage those patterns to solve other similar problems. Let’s take the example of a coin change problem:


You have n types of coin denominations bearing values C1 < C2 < … < Cn (all integers). Assume C(1) = 1 to make changes for any amount of money (M). Create an algorithm to get the minimal number of coins that make change for an amount of money M.

So, what approach should you take in solving this problem? In four simple steps, we’ll show you how!


  1. Problem & Subproblem


When a problem is given to you, first you have to check whether or not it is suitable for dynamic programming. And how do you do that? By seeing if it is possible to break down the problem into smaller subproblems.


If you see the coin problem closely, you’ll find that it is quite similar to Fibonacci. Here, you can see that a subproblem is capable of making changes for a smaller value. So, by determining the minimal number of coins needed for all the values < M (1, 2, 3, … M – 1), we can find the answer for M simply by determining the best possible combination of them. In this light, we find that the solutions for subproblems of this problem can help to find the solution for the primary problem and hence, dynamic programming is worth a shot here.


  1. Identify The Formula


Once you’ve recognized that the problem can be broken down into subproblems, you must now determine how the subproblems can help in solving the primary problem by applying the relevant formula.


For the given coin change problem, let’s assume that F(m) indicates the minimum number of coins required to make M. So, we need to determine how to indicate F(m) using values less than M. Suppose C1 is needed, then F(m) = F(m – C1) + 1 to find out how many coins are required to make [m-C1].


As we do not know which value is exactly required (from C1 to Cn), we must iterate all the values. So, the formula will be as follows:


F(m) = min(F(m – Ci)) + 1, for i = 1 … n


The formula denotes that we need to iterate all the solutions for [m-Ci] to find the minimal value.


  1. Memoization


Memoization is pivotal in DP. Why so? If you merely implement the formula, you will find that to calculate F(m), the code will calculate a bunch of subproblems of F(m – Ci), whereas to calculate F(m – Ci), it will further calculate the sub-subproblem. The chain will continue and hence, the code might end up calculating many subproblems or sub-subproblems more than once. This is where memoization is helpful. Through memoization, you can store results of the subproblems/sub-subproblems so the next time you need to solve those, you can directly use the results.


To save the results of a subproblem, you must create an identifier for it. So, an array memory can be created as [m + 1]  and for the subproblem F(m – Ci), you can store the result to memory [m – Ci] for solving future problems.


  1. Implementation


Implementation becomes easier and more convenient when you break it down into smaller fragments. This allows you to follow the same to solve similar questions. Here’s how you should go about the implementation process:


  • Initialize memoization and define the array memory [m + 1].
  • See if the problem has been solved using the memory. If yes, revert to the result directly.
  • Now, implement the formula and save the result to memory.

While these four steps basically sum up the top-down approach, that is, we solve the primary problem by breaking it down into subproblems, there’s another approach to DP – bottom-up. Unlike the top-down approach, the bottom-up approach doesn’t use recursion but begins with subproblems and moves up towards the primary problem.

So, that’s Dynamic Programming simplified for you! Have any doubts? Drop them in the comments below!


Coding, programming, and the subtle difference between the two


In the world of computer programming, two words are often used interchangeably and almost synonymously – coding and programming. To most non-developers, these two words essentially bear the same connotation, that is, entering a set of instructions into a machine to make it perform certain commands. However, let us break this misconception for you.

Programming and Coding

While coding refers to the process of writing codes in a particular programming language, programming is a broader umbrella that refers to the entire process of feeding information into machines to enable them to perform specific tasks. In this respect, we can think of programming as the main recipe that requires a lot of ingredients and a step-by-step approach. Coding makes up one part of that approach, that is, the initial steps of the programming process.

The Differences


As we said before, coding is the process of writing code by converting one language into another whereas programming denotes the process of designing and developing a functional and executable program that can perform specific task or tasks. Also, coding aims to bridge the gap between humans and machines, programming ensures that the code is perfectly balanced, that is, the inputs (human instructions) and the outputs (machine) are in sync with each other.


Since coding forms the introduction part of programming, coders need to possess basic knowledge of the field. This is not the case with programmers. Programmers are required to possess high-level expertise in working with complex data structures, algorithms, databases along with the knowledge of programming languages like Python, Java, SQL, Ruby, Perl, C, and C++, to name a few.

Complexity Level

Coding is the initial step of programming involving addressing complex queries in a code. Programming, on the other hand, seeks to handle a variety of complex issues and queries. A coder builds a code based on the specific set of instructions he/she is given related to the implementation, debugging, QA, and testing. Thus, a coder’s job is pretty much set according to the instructions. Coding involves writing lines of codes, translating requirements, and implementing these into machine-readable inputs.

A programmer, however, has to create functional and logical programs as well as analyze and fix any possible problems that may ruin the functionality of the code. A programmer has to look for problems even where it may not exist for the aim is to deliver bug-free and efficient code. In this sense, programming can be considered as an advanced level of coding.

Knowing these subtle differences is extremely essential for the tech-savvy generation. If you choose to build a career in coding and programming, it is only natural that you will be expected to know the proper meanings of these concepts.

Now that you know the difference between coding and programming, it’s time to share this knowledge with your friends and family!