5 AI and ML startups hiring in 2018


Elon Musk had once stated that “AI will be the best or worst thing ever for humanity.

And today, we’re witnessing the many, many, marvels of Artificial Intelligence that are ruling our lives. From the IT sector to banking and fintech, from healthcare to education, from e-commerce to the business sector – AI has penetrated every major industry across the globe. The pace at which AI is escalating is simply stunning. Since 2000, the number of AI startups has increased by 14 times, and since 2013, the number of jobs demanding AI skills has grown by 4.5 times! Furthermore, Statista maintains that between 2017-22, the global market revenue of AI will grow by tenfold.

Moving on to the Indian AI startup scene, it can be safely said that the market is booming at an impressive pace. According to Inc42 Data Labs 2017 report, the AI startup sector saw a 100% increase in 2017 as compared to 2016 (with respect to deals attained and closed). Bengaluru takes the limelight here – nearly $88 million was obtained from over 58 deals in the AI sector.

Here are AI startups in India that have made their mark in 2018!

  1. Niki.ai

Niki.ai is a Bengaluru-based startup founded by four ambitious alumni of IIT Kharagpur. It is essentially an AI-powered personal shopping assistant that helps users shop for products and services online by leveraging Natural Language Processing (NLP) technology. The services offered by Niki.ai span across twenty differentiated categories such as travel, entertainment, shopping, and much more.

It has partnered with many reputed brands including HDFC, BookMyShow, OYO, Redbus, Ola, and Uber, to name a few. Furthermore, it has obtained funding from business moguls like Ratan Tata and Ronnie Screwvala.

  1. Absentia VR

Another Bengaluru-based AI startup, Absentia VR is the creator of Norah AI – a revolutionary, state-of-the-art, AI-empowered workflow that allows for both game creation and incorporation of game elements for enhanced story weaving and texturing. At its core, Norah has AI, Deep Learning, and Neural Network.

It was founded in 2015 by three college dropouts from BITS Pilani with an aim to create the first unique AI gaming experience in India. Like Niki.ai, Absentia too has obtained funding from renowned investors including V. Balakrishnan, Girish Paranjpe, Astarc Ventures, Exfinity Venture Partners, and 50K Ventures.

  1. Innefu Labs

Innefu Labs is a Delhi-based AI startup that provides cybersecurity solutions including multi-factor authentication, biometric authentication, and Big Data analytics to both predict as well as prevent cyber threats. Rising cyber threats are a serious issue for companies today and to address this, Innefu has developed its patented security solution – AuthShield that leverages image and speech-based authentication system. AuthShield works something like this – if a user wishes to access an application/system, he/she first needs to click a selfie from the phone and speak a few words. The image and speech are then matched and verified with the user’s features by a 3D modeling pattern and if it matches, access is granted.

Innefu caters to the security needs of clients spanning across diverse industries such as the Indian Army, intelligence agencies, police departments, e-commerce, IT/ITES, telecom, BFSI, and BPOs, among others.

  1. NetraDyne

NetraDyne is a one-of-a-kind commercial vehicle technology provider headquartered in Bengaluru and San Diego. Its IoT-based product, Driveri combines AI and Deep Learning to identify and determine the causality of unfortunate accidents on the road by providing commercial fleets with real-time and meaningful data. With the data at their disposal, commercial fleets can detect risky driving and the possibility of unforeseen incidents and prevent it from happening by applying their resources promptly. The aim is to enhance commercial fleet safety.

In June 2016, NetraDyne obtained $16 million in funding from Reliance Industries Ltd. (RIL).

  1. Staqu

Staqu is a Gurgaon-based AI startup specializing in advanced image and video analysis, speech recognition, facial recognition, text processing, and language and text-independent speaker identification engine.

The core focus areas of Staqu include Deep Learning, NLP, Computer Vision, and image processing. Combining these innovative technologies together, Staqu aims to enhance a user’s mobile experience. The AI startup has developed a pioneering contextual content recommendation engine designed to provide in-platform and cross-platform recommendation facilities to smartphone companies while giving the users complete control of the platform too. Apart from a smart recommendation engine, Staqu also provides a robust security framework with fully-customizable facial and speech recognition features.

These are only five among the numerous AI startups that are rapidly transforming the AI scenario in India. As such innovative startups continue to rise and shine, it can be safely said that India’s future looks bright with AI!


An introduction to chatbots


If you are an active user of social media and messenger apps, you must be familiar with chatbots.

That’s precisely our topic of discussion today – Chatbots!

In the past two years, the entire experience customer service has scaled up a notch, thanks to chatbots. These interactive bots are now used by almost every major company like Facebook, Apple, Google, and Microsoft, to help customers interact with their brand on a personal level and know more about their products and services. In other words, chatbots have paved the way for a more personalized online experience.

According to Gartner, by 2020 nearly 85% of the customer interactions will be handled without any human assistance. How? Chatbots, of course!

Now, let’s get to the fundamental question:

What is a Chatbot?

To put it in the simplest of terms, a chatbot is a program or software that can communicate with you (and other humans too!).

But wait, don’t be mistaken. Although a chatbot is designed to communicate with humans, it is unfair and even unjustified to think that a chatbot can communicate with you exactly as a human would! For no matter how advanced a bot is, it is what it is – a bot. So, it’s better you don’t harbor any unrealistic expectations from a chatbot!

Chatbots are basically of two types:

Scripted (rule-based)

Scripted chatbots are bots whose behavior and functionality is determined according to a specific set of rules. Hence, any conversation with scripted chatbots will follow a predetermined course for they will know only how to answer according to the way they’ve been programmed. So, when you communicate with such a chatbot, its answers and options (voice, text, touch) will depend on its innate design and preset responses.

Intelligent (AI-powered)

Intelligent chatbots, as the name suggests, are intelligent. Being AI-powered, these chatbots are designed to learn and adapt from behavioral experiences. So, the more you interact with them, the smarter the bots become. For instance, if you wish to have the recipe of chocolate cake, the intelligent chatbot will surf the Internet and find all the best possible resources for a chocolate cake recipe for you! Unlike scripted chatbots, intelligent chatbots can accept any free form of input (text, speech, or image) and respond accordingly.

However, one thing to keep in mind is that both of these chatbot variants have their own limitations as the technology is still largely in its infancy.

History: The beginning of chatbots

The first breakthrough in this arena dates back to 1950 when Alan Turing and Joseph Weizenbaum imagined computers talking like humans and with that in mind, they developed the Turing Test – a test designed to distinguish a human from a machine.

However, it was only in 1966 that Weizenbaum programmed the first chatbot named ELIZA that could imitate the language and behavior of a psychotherapist. Another chatbot named PARRY came into the scene in 1972 and interaction with both ELIZA and PARRY had to be done in the form of texts. Voice operated chatbot came much later in 1988 with Rollo Carpenter’s Jabberwacky project.

Fast forward to the present day and we have some of the most developed and intelligent chatbots such as U-Report, Heston Bot, Nerdy Bot, ENO, and to name a few.

What does the future look like for chatbots?

The future of chatbots certainly seems bright now for people are now showing more inclination towards messenger apps than social networking apps.


So, businesses are naturally shifting to the messenger and chatbot domain than investing their time and resources on social media platforms. Chatbots now present a huge and emerging business opportunity for any and every individual who’s willing to leverage its potential.

Now the question is, are you ready to cash this opportunity?

Difference between a programming language and a scripting language


Often people use the terms scripting language and programming language synonymously, but these two terms have more difference than you know of. Although all scripting languages are programming languages, all programming languages are not scripting languages.

Earlier, programming languages were written to build products such as PowerPoint, Internet Explorer, Microsoft Excel, and Microsoft Word, to name a few. However, as time passed, there arose a need to upgrade the programming languages to incorporate additional functionalities and provide an enhanced programming interface. Thus, scripting languages came into being. The primary difference between a scripting language and a programming language is in their execution – programming languages use a compiler to convert the high-level programming languages into machine language, on the other hand, scripting languages use an interpreter. While a compiler compiles a code in a complete chunk, an interpreter compiles a code line by line.

Let us now look at some of the major differences between a programming language and a scripting language.


A programming language is essentially a formal language that combines a set of instructions that can be fed into the computer to generate a specific output. A scripting language is a programming language that supports scripts which are programs written exclusively for a special runtime environment to automate the execution of a specific action/function.


Programming languages are compiled into a more compact design that does not require to be interpreted by another language or application. Scripting languages are written in one language and interpreted within another program, for instance, JavaScript has to be incorporated within HTML which will then be interpreted by the Internet browser. Thus, programming languages run independently of a parent program, but scripting languages run inside another program.


Programming languages are designed to facilitate a full-fledged code and software development whereas scripting languages are specifically designed to make coding faster and much simpler.


Coding with programming languages is relatively difficult as many lines of code are required for a single function. Creating a code function with a scripting language is easier as it requires only a few short and specific lines to be written. Thus, writing a  full-fledged code with programming languages usually take a longer time to develop as more lines need to be written while coding with a scripting language requires less time as smaller chunks need to be written.


Programming languages are divided into five subcategories: First generation, Second generation, Third generation, Fourth generation, and Fifth generation. Scripting languages have only two subcategories: Server-side scripting languages and client-side scripting languages.

Conversion and hosting

Since programming languages use a compiler, it is a one-shot conversion. Scripting languages, on the other hand, demand line by line conversion. Programming languages are self-executable; they do not require a host. Scripting languages require a host.


Compiled programs run generally run faster than interpreted programs since compilers read and analyze the code at once and report errors (if any) collectively. An interpreter, however, reads and analyzes a code line by line and every time it detects an error, it stops to address them one by one.


C, C++, C#, Java, Basic, COBOL, and Pascal, are some examples of programming languages. JavaScript, Perl, PHP, Python, Ruby, Rexx, Ruby, GameMonkey, etc., are some of the most widely used scripting languages.


Overall, as we mentioned before, the execution process and environment are the primary differentiating factors between programming languages and scripting languages. Programming languages are used to develop applications and scripting languages are used to write code that can enhance and control application behavior.

So, now you know how programming languages differ from scripting languages, you’re ready to pick one for you. But again, you should keep in mind that the language you choose will depend entirely on your use-case and what you wish to accomplish with it. If you find yourself confused, don’t hesitate in visiting Coding Ninjas, where we have courses on programming languages including C++, Java, and scripting languages like Python, Ruby on Rails. We’ll ensure you reach all the way to the top, no matter where you start from!


Web-designing trends that have emerged (and won) in 2018


Web designing trends are always changing – old trends of yesterday make way for the emerging trends of today. And if you wish to be a successful web designer, you should try to keep up with the latest web design trends.

Here are some of the most popular web design trends that have emerged and gained traction in 2018!

  1. Animation

While it is a known fact that netizens display a greater affinity towards visual content, static images are outdated – animation and animated videos are the hottest buzzwords of the town.



With animated clips, animated images, and animated GIFs, you can attract the attention of your target audience while at the same time getting your POV across to them. Animated content makes your website look much more alive and interesting to the viewers.

  1. Chatbots


Lately, many online websites have begun to incorporate tiny pop-up windows on their landing page. These pop-up windows are called ‘chatbots’ that allow users to chat and communicate with the brand/company representative. So, whatever queries you may have, you can ask these chatbots and get an immediate response to your queries. Cool, isn’t it?


Chatbots are an excellent option to boost the real-time interaction with your customers and for online companies that have to answer customer queries on a daily basis. In such situations, you can program a chatbot to provide answers to certain commonly asked questions and for all other kinds of questions, the chatbot can be programmed to provide the next best assistance such as the details of how to get in a personal call with a company representative.

  1. Custom illustrations


We’re almost through 2018, and if you still think that incorporating stock images to your website is enough to engage your target audience with visual content, you are terribly mistaken.

It’s time to invest in custom illustrations!

People are not attracted to visual content blindly – they look for originality. Thus, if you customize your illustrations in accordance with your products and services, it creates a wonderful and unique experience for your viewers. And the great thing is that there are numerous apps and tools with which you can design brand-centric images and illustrations.

  1. Bold fonts


Fonts are one of the most underrated aspects of a website’s outlook, but if you are wise enough, you know that fonts cannot be ignored. Now, unique, bold, and neat fonts are apparently a big hit with the online audience.


By using a bold font in a neat layout design, you can draw more attention to the words on your web page. Web designers are, thus, increasingly resorting to Typography so as to impart the website’s textual content with more depth and gravity.

  1. Bold colors

What better than bold and vibrant colors to stand out in the crowd?



Web designers today are increasingly using bold and bright color combinations in websites to make them visually appealing. Bright yellows, fluorescents, purple, blue, and crimson, to name a few, have been some of the hottest color choices throughout the year. Add a dash of such colors to your text and voila – your website will be jazzed!

  1. Asymmetrical layouts

By now you must have understood that web design is all about innovation and unique presentation of content, be it textual or visual.



In the past, flat and symmetrical web design layouts were a hit. However, tables have turned now, and the recent shift is towards 3D and asymmetrical layouts. The reason behind this is that asymmetrical designs have a sense of unusual mystery to them which makes them unique and appealing to the onlooker’s eye.

  1. Floating navigation

Usually, websites have the navigation option fixed in one place on their landing page – the top corner. However, web designers are now experimenting with Floating Navigation, wherein the navigation bar is always accessible and visible, even if you are scrolling down across the page.



Not only is this innovative, but it’s also practical as you don’t have to keep scrolling up the page to access the navigation option.

Bottom line – all the emerging web design trends have one thing in common, that is, the end user (a viewer or a potential customer). The end goal here is to develop and incorporate such designs that make the web experience smooth and unique for the users.

So, if you’ve always wished to start off creating sweet designs for users, why not start today? Visit us at CodingNinjas, where we offer web development courses that ensure you’re on the right track from the day one!

So, which among these are you going to use next?


Music to get you in the programming groove


If there’s anything that coders around the world love to do (apart from coding of course!), it is listening to music. While their brains are busy sketching lengthy and complex codes, music acts as a food for their soul. In fact, most coders would agree that music helps create a soothing environment which in turn boosts productivity. It’s fun too, isn’t it? Plugging in your headphones, cutting off from the world, and immersing yourself into the coding dimension?

So, without further ado, let’s check out the most popular and trending music numbers that’ll help get your creative juices flowing!

The Social Network Soundtrack

If you’ve witnessed the charm of this Academy Award-winning film, you probably know how awesome its musical score and soundtracks are! Needless to say, Trent Reznor and Atticus Ross did a wonderful job in creating the overall mood of tension and intensity with an amalgamation of electronics and bass. While all the soundtracks from the movie are commendable, make sure you listen to Hand Covers Bruise first!

Tron: Legacy Soundtrack

The musical score of the Tron franchise (both the 1982 version and the 2010 version) is a huge hit among developers. While the original 1982 classic featured an 80s rock vibe with a strong synthpop style, Tron: Legacy features some really slick music by Daft Punk. The way Daft Punk used orchestral elements with electronic pop and digital sounds, it’s just mindblowing!

Hackers Soundtrack

Another movie that made to the list is Hackers. The 1995 movie features some very interesting and unique electronic numbers by bands like The Prodigy and Leftfield. The moment you plug in your headphones and play these electronic beats, you’ll realize how your work pace is also gaining an upbeat rhythm.

Now, moving on from films to some of the most loved bands, here are some of the gems that you must listen to!


Probably every developer knows the name of this massively popular English Rock band. In fact, today, it has almost gained a cult following among the developer community, and rightly so. Radiohead has given us a number of great songs such as Kid A, In Rainbows, Paranoid Android, Creep, High and Dry, Reckoner, There There, Let Down, Karma Police, to name a few.

God is an Astronaut

God is an Astronaut is an Irish post-rock band that features a unique mix of electronic music,  space rock, and krautrock. Some of the most popular soundtracks of the band include Forever Lost, Frozen Twilight, Ascend to Oblivion, All Is Violent All Is Bright, Fireflies and Empty Skies, Far From Refuge, Beyond the Dying Light, Coda, and much more.  

Boards of Canada

If you’re really into electronic music, Boards of Canada is the ideal match for you! Featuring the Scottish brother duo, Boards of Canada shot to fame with their debut album Music Has the Right to Children (1998). Their music includes sound elements like hip-hop breakbeats and vintage synthesizers. Some of their best songs are Dayvan Cowboy, Aquarius, Dawn Chorus, Turquoise Hexagon Sun, Peacock Tail, Everything You Do Is A Balloon, Chromakey Dreamcoat, and Music Is Math.


Robert Card, a.k.a. Blackmill is a famous dubstep producer hailing from the UK. His music is more of a musical dubstep which is sure to capture your attention if you are a fan of the dubstep genre. Let It Be, Spirit of Life, Miracle, Evil Beauty, Lucid Truth, Fortune Soul, Rain, The Drift, and Sarajevo are a few popular hits by Blackmill.


Nujabes music, the brainchild of Jun Seba, is a mix of hip-hop and jazz. The instrumental beats and the blend of jazz with hip-hop will surely transport you to another dimension. The music is best known for creating a nostalgic and atmospheric mood. Here are some of the best songs by Nujabes – Gone Are The Days, F.I.L.O., Flowers, City Lights, Eclipse, Lady Brown, Imaginary Folklore, and World End Rhapsody.

So, are you ready to get rocking at work while listening to these sick beats?


Top AI trends of 2018 that are going to have a huge impact


Lately, the term ‘Artificial Intelligence’ has been making headlines, and rightly so. Artificial Intelligence (AI), that was previously thought to be the stuff science fiction was made of, is now a living, breathing reality of the present-day world. Even though AI is at its infancy, the marvels that it has helped in creating today is helping to make our lives much more convenient and comfortable. Think about smart homes, smart personal assistants, online recommendation engines, self-driving cars, and so much more – all of this has been made possible through AI.

As AI technology continues to develop and progress, it is giving rise to numerous possibilities and innovations that were, in the past, beyond our imagination. Furthermore, with AI we’re witnessing the rise of many interlinked technologies such as Machine Learning (ML), Cognitive Computing, Natural Language Processing (NLP), Neural Network, and Robotics, to name a few. Coupled with these technologies, AI is transforming the face of every major industry today, from business and technology to education and healthcare. In fact, Statista maintains that between 2017-22, the global revenue of the AI market is estimated to increase by ten times.

Seeing as AI is here to stay, here are four AI trends to look out for in 2018!

Machine Learning

Machine Learning is all about enabling computers to learn from data and improve specific functions without relying on human commands or assistance. One of the greatest contributions of ML has been automation. For instance, smart homes and virtual assistants are the best examples of home automation. The smart devices, such as a smart thermostat or a smart TV, learn from your behavior and preference patterns and adjust the home temperature or play your favorite movies based on those patterns.

However, automation is not just confined to the boundaries of your home. The financial sector is now heavily relying on automation to automate the redundant and mechanical tasks, thereby freeing up the valuable time of employees. Also, ML plays a big role in helping companies in the banking and finance sector to detect and prevent fraud. These advanced ML models are designed to learn from historical data and trace and identify any anomalies, thereby alerting both companies and customers of potentially fraudulent activities.   

AI and ML are also creating a huge wave of change in the healthcare sector. Smart machines that function on advanced algorithms are helping improve the overall workflow and data management in hospitals. Innovative ML applications are helping in the accurate prediction of life-threatening diseases, drug discovery, personalized treatment (remote monitoring and wearables), gene-sequencing, and much more. Moreover, Robotic Surgery is making it possible for doctors to perform even critical operations without causing much wear and tear to the patient.

Natural Language Processing

Natural Language Processing (NLP) is a branch of AI that aims to teach computers to analyze, interpret, understand, and manipulate human languages so as to facilitate a smooth interaction between computers and humans.

NLP is gaining traction rapidly with the various NLP applications ruling our lives today such as chatbots and virtual assistants. The inclusion of chatbots on various online platforms has taken customer service to a whole other level. The chatbots are designed to handle and answer to all kinds of customer queries and assist them. Then we have the smart personal assistants like Alexa, Siri, and Cortana that can not only interact with you but also perform various functions for you including playing your favorite songs, giving you weather updates, shopping online, and so much more! This is not only fun but also a great way to get your tasks done efficiently.

Sentiment Analysis

Today, business is not just about profit maximization but it is primarily about optimizing customer satisfaction. Putting an increased importance on enhancing the overall customer satisfaction, companies across the globe are leveraging sentiment analysis to analyze and understand the behavior and preference patterns of their customer segments. Using sentiment analysis, computers are able to understand the intent of the customers behind their comments, feedback, queries, compliments, and grievances. This allows brands to address the specific needs and woes of their clientele base and create better products/services that are more likely to gel with their tastes.

Lately, researchers have also begun to experiment with sentiment analysis and the impact it could have on the healthcare industry. For instance, virtual private assistants (VPAs) could assist patients and provide them with a more personalized healthcare routine. Then again, emotion-sensing wearables could monitor and track the mental health of patients and intimate the physician in case there’s any fluctuation in the health stats of a patient.

Smart Cities

As the global population continues to escalate by the minute, cities around the world are faced with the problem of providing the basic resources to their citizens including water, electricity, housing spaces, clean air, healthcare services, and quality transportation, among others. In the light of this increasing burden on the rapidly growing urban spaces, governments of various countries are striving to make a shift towards ‘Smart Cities.’ These smart cities are designed to address the rising urban challenges with the help of AI, IoT, and Big Data. For instance, using Big Data and smart cams together, governments can get real-time inputs (images and videos) about traffic and accidents in various parts of the city, thereby helping the administration to better manage traffic issues and provide emergency services promptly in and across the city.

The concept of smart cities is already a big hit and is being iterated across many countries in the world today.

With all that being said, one this is for sure – AI is here to stay. As AI technology continues to progress as we speak, there’s definitely much more to come in the future.


3 Essential tips for writing a Computer Science research paper/project


If learning and gaining knowledge are pivotal to a student’s career, writing good research projects is yet another fundamental part of the student life. And whether you like it or not, you just have to (or have had to) write research projects at some point in your student life.

To put it in simple terms, a research project, as the name suggests, is to conduct an expansive research on an already established research with an aim to discover new things or to see old things in a newfound light. And while research projects are conducted on every discipline (be it History, or Geography, or English, and so on), Computer Science research projects stand entirely apart from the crowd. Why so? Because Computer Science is a rapidly and ever-evolving discipline that requires a student to conduct research in keeping with the old as well as the emerging trends in the field.

But don’t worry, writing a good Computer Science research project is no rocket science; you just have to know the tricks of the trade. In today’s blog post, we’ll teach you how to write a good Computer Science research project in three simple steps!

1. Choose The Project Topic Wisely

When it comes to the topic of research, often mentors hand over the assignment topics to students and research fellows, but then again, sometimes you might have to make the choice for yourself. This shouldn’t be tough for there are numerous exciting topics to choose from such as algorithms, databases, AI, graphic design, OS, programming, embedded systems, web/mobile applications, and multimedia, to name a few.

While choosing the project topic, you must ask yourself the following questions:

Will I be able to carry on an extensive research in this particular area?’

‘Can I find all the requisite resources for completing the research in this particular area?’

‘Will I have access to all the necessary information required to make this project a successful one?’

If the answer to all these questions is ‘yes,’ then go ahead with your chosen topic of interest.

2. Dig In Deep — Research!

Once you’ve selected your research topic, it’s time to get cracking on it. You have to be extra attentive and careful during the research part and also, you must be aware of all the right places to look at. For Computer Science projects, the Internet is by far the best source for research. Like we said earlier since Computer Science is a rapidly evolving field, the Internet is the best place to access the latest and most reliable journals, peer-reviewed papers, and ebooks on Computer Science. The Institute of Electrical and Electronics Engineers (IEEE), The International Journal of Computer Science, and The Journal of Computer and System Sciences are some great sites to hunt for top-notch informative materials.

An important part of research that many students tend to overlook is taking notes. By taking notes while researching, you are not only able to delineate the most crucial points required for your research project, but you can also save time as you don’t have to read the entire paper/article over and over again.

3. Write — Give Coherence To Your Research

Like any other research project, you must begin your research project with an introduction or Preface. The preface will basically outline your topic of research, the things you’ll be elaborating on, and your hypothesis on the topic at hand. In other words, it will highlight the goal of your research.

Now, comes the body of your research project. Naturally, the body is what makes the majority of the research paper. In the introductory part of the body, you should explain the topic at hand and then gradually build on it to make way for your research on the topic. Moving on, the middle part of the project will focus on your research, your findings, and how they can help look at the topic at hand in a new light or enhance it in any way. The concluding part of your research will show the results you’ve achieved from your observations and experiments (if any), while also highlighting the fact of whether or not the actual results met the expected results.

While writing the research project, amalgamate your thoughts in such a way that your paper can answer any and every question that arises in the mind of the reader. If your project is able to do so, you know that you’ve done a good job.

After writing your Conclusion for the project, make sure to include all the sources of reference and the names of all the informative materials under the Acknowledgment section.

So, there you go! Follow these steps diligently and you will surely be able to nail any project in Computer Science. Now go and try it (you can thank us later)!

Top-down and bottom-up: The difference between the two programming approaches


In the world of programming, algorithms take the prime spotlight. These complex mathematical and computational designs are used to find solutions to even more complex programming issues. But that’s something we’re all aware of. However, do you know how these algorithms are designed and created?

That’s precisely the topic of our conversation today!

How Are Algorithms Designed – The Top-Down And The Bottom-Up Approach

Basically, the top-down approach, as the name suggests, is all about breaking a bigger problem into smaller chunks, whereas, the bottom-up approach focuses on amalgamating smaller chunks to paint the complete and bigger picture. Get it? Now, let’s take a closer look at these two methodologies.

The Top-Down Approach

In the top-down approach, a complex algorithm is broken down into smaller fragments, better known as ‘modules.’ These modules are then further broken down into more smaller fragments until they can no longer be fragmented. This process is called ‘modularization.’ However, during the modularization process, you must always maintain the integrity and originality of the algorithm.

By breaking a bigger problem into smaller fragments, the top-down approach minimizes the complications usually incurred while designing algorithms. Furthermore, in this approach, each function in a code is unique and works independently of other functions. The top-down approach is heavily used in the C programming language.

The Bottom-Up Approach

Contrary to the top-down approach, the bottom-up approach focuses on designing an algorithm by beginning at the very basic level and building up as it goes. In this approach, the modules are designed individually and are then integrated together to form a complete algorithmic design.

So, in this method, each and every module is built and tested at an individual level (unit testing) prior to integrating them to build a concrete solution. The unit testing is performed by leveraging specific low-level functions.

What Are The Key Differences Between The Top-Down And The Bottom-Up Approaches?

Based on the core preferences and values of each methodology, we can chalk out certain basic differences between the two. They are:

  • While the top-down approach focuses on breaking down a big problem into smaller and understandable chunks, the bottom-up approach first focuses on solving the smaller problems at the fundamental level and then integrating them into a whole and complete solution.
  • The top-down approach is primarily used by structured programming languages such as C, COBOL, Fortran. On the contrary, the bottom-up approach is preferred by OOP languages such as C++, C#, Python, Java, and Perl.
  • In the top-down approach, each module and submodule are processed separately, and hence, they might contain redundant information. However, the bottom-up approach relies on data encapsulation and data-hiding, thereby, minimizing redundancy.
  • The top-down approach doesn’t require the modules to have a well-established line of communication among them, whereas, in the bottom-up approach, the modules must have a certain degree of interaction and communication among them.
  • While the top-down approach can be used in module documentation, debugging, and code implementation, the bottom-up approach is primarily used in testing.

Thus, in conclusion, we can say that the top-down approach is rather the conventional method that seeks to decompose a complex problem into smaller fragments (from high-level specification to low-level specification), the bottom-up approach works is just the opposite – it first concentrates on designing the fundamental components of an algorithm and then moves up to a higher level to achieve a complete result.

We hope this helps! Happy coding!


Guiding path for a fresher to start their career in software programming/development


You’re almost through with your Bachelor’s. The hunger for bagging the ideal Software Engineering job is intensifying by the minute, but you don’t want to rush into just any job – you want to be hired by your dream IT company and strive to become an indispensable part of it. This is the story of almost every fresher who’s just passed out of college and is ready to step out into the real world now. However, many freshers give in to skepticism and ‘settle’ for jobs that they don’t enjoy. You don’t want to be one among those, do you?  

Granted that the job hunt process is stressful, time-consuming, and overwhelming, but you cannot give up without trying. You have the right to aim for the stars and don’t let anybody tell you otherwise. The key to bagging a well-paying job at a reputed company is to strategize and prepare yourself for any challenge they may throw at you.

Here’s how you can kickstart your career in Software Development!

  1. Prepare An Impressive Portfolio

An impressive and well-designed portfolio is what will help you catch the attention of your interviewer, so, make sure your game in on point! Your portfolio should highlight all the projects you’ve undertaken and completed. It helps to show your progress and experience outside the world of books and theory. For instance, if your portfolio states that you know Java or Scala or both, it should also mention the programs/projects you’ve completed on the same. Many freshers out there do not have work experience as developers or coders. In such situations, these projects denote your credibility and talent as a budding developer.

While your portfolio should show all your achievements, projects, and unique traits as a developer, it always helps when you can communicate about these passionately to your interviewer. Don’t be shy of talking about your strengths and weaknesses during interviews.

Bonus points: If you have experience with Git and GitHub, you’ll take home extra points for sure! These are extremely resourceful and vital tools for version control and collaboration.

  1. Brace Yourself For Technical Interviews

When it comes to technical interviews, you must be prepared to showcase your skills on spot. In most technical interviews candidates are required to solve all kinds of coding problems, be it on a whiteboard or on a computer. This is a test of not only your coding skills but also to assess how well you perform under pressure. Thankfully, there are numerous platforms such as Leetcode, Glassdoor, HackerRank, TopCoder, InterviewCake, Pramp, Coding Ninjas, and many more, to help you with this.

Start practicing coding without a code editor on paper or on a whiteboard. Although it will be tough in the beginning, you’ll get better with time and practice. Now, coming to the part of the interview questions. In a technical interview, it’s natural that you’ll be asked a lot of technical questions and the interviewer will expect you to know all the fundamental technical and coding concepts like conditions, variables, pseudocode, data structures, and syntax, to name a few. There are also many informative online resources such as this or this to help you prepare for this.

  1. Decide On What Kind Of Role You Want And Define It Clearly

As a fresher in the job industry, you must remember that now you have to devote a maximum portion of your day to your work. And hence, it is extremely essential to choose a job that you enjoy. So, now the question is, how do you know the perfect job role for yourself?

The best way to go about is to chalk out a list of your interests, challenges, opportunities, and work environment, that you’re looking for in a job. While doing so, keep in mind that a job should have adequate work-life balance. When you do this, you’ll see your priorities before you and can embark on the job hunt accordingly instead of wasting your time on any and every job offer.  

During interviews, make sure that you’re not the only one who has to put up with questions but ask questions too. Make sure you bring up all the above-mentioned factors before your interviewer and see how he/she responds to it. This will help you determine whether or not a company is a right fit for the job role you have in mind.

  1. Prepare A Neat And Meaningful Resume/Cover Letter

This is something where you need to invest a significant amount of your time and energy – building a high-end and impressive resume. Just like your work portfolio, your resume speaks a lot about you. Thus, you must ensure that your resume and cover letter is a commendable one. It should be neat, well-aligned, and free of grammatical errors. Also, try to keep in within one page (resumes that are over one page or more tend to get rejected immediately).

Also, work earnestly on your cover letter. When applying for a company, make it a point to visit the company website/page and see what it is offering and how you can add value to it. Then write a cover letter offering a genuine reason why the company interests you and why you’d like to be a part of it. Keep your language simple but compelling. NEVER copy and paste answers in your cover letter from Google!

  1. Networking Is The Way To Go

You aspire to become a developer. So, why not also be a part of the larger community of developers? Networking is pivotal for everyone and for every line of work, especially for freshers. The more you show up at industry-specific meetups, the more you expose yourself to potential employers and mentors.

The developer community is huge and if you’re someone who bears an insatiable thirst for knowledge (specifically about coding, technology, and technological innovations!), you should definitely head to tech meetups and conferences. You not only get to learn from talented individuals in the field, but you also get to build many interesting and helpful connections with like-minded people. Although job leads may not shower on you immediately, believe us, it will come eventually.

If you have these grounds covered, you’re all set to face technical interviews and maybe even nail a few! The secret is to prepare well and march in confidently. Know your worth and never, ever, settle for less.


Career opportunities after mastering Python


Over the years, Python has gained a massive fan following among the programmer and developer community across the globe. According to a 2017 Stack Overflow report, Python is one of the fastest growing programming languages in the US, Canada, UK, and Germany. Behind this growing popularity lies the fact that Python offers numerous advantages when it comes to software development. It is an open-source, high-level programming language which means that it is backed by an active community of developers. Furthermore, it has a great readability quotient and allows you to write a code in a few lines but with a concrete design. To top that, Python comes with automatic memory management that seamlessly supports multiple programming paradigms. For these reasons, it is widely used for script writing (dynamic script writing too), Web development, app development, system upgrades, and testing.

Career Prospects In Python

Today, companies all around the world are on the hunt for skilled and qualified professionals who’re well versed with at least two high-level programming languages, and Python is one of them. Lately, career opportunities in Python have been booming at a tremendous scale and if you possess the right set of skills (a solid programming foundation and problem-solving ability), you can grab an exciting job role in Python.

For students who’re still studying or are in their final semester, the best course is to take up Data Science Internships as internships can provide a great kick start for building a career in Python. Freshers can apply for job roles as Front-end Developers, DevOps Engineer, Software Engineer, and Python Developer, among others. For experienced individuals who are aspiring to scale up in their career, bagging a high-profile job in Python, re-training in Python is a must. Most high-end job profiles have higher expectations from experienced professionals and hence, you’re required to further strengthen your knowledge base of the core areas of programming. So, you’ve to brush up on concepts like strong typing, dynamic typing, and duck typing, and learn how these are implemented while working with Python. Also, you need to build a good foundation of both scientific and numerical modules, SIMD vectorization, concurrent algorithms, data manipulation, data cleaning, predictive modeling, and multicore programming, to name a few. Taking up an advanced certification program in Python or Data Analytics can be a good option here.

In addition to the full-time career opportunities in Python, job prospects for freelancers skilled in Python have also increased significantly, particularly in the US. Freelance jobs in Python are basically a contractual job that may span anywhere between three to six months with a minimum hourly rate of $30 (a decent pay for a part-time job). Job portals like Upwork, PeoplePerHour, and Freelancer.in are excellent platforms to search for freelance projects in Python.

Data Scientists and Data Analysts who have a flair for Python tools and libraries have a competitive edge in the job market as they are able to handle data better. If you have a strong command over Data Analytics and ML and AI technologies, your chances of bagging a high-end and well-paying job increase manifold.  

Other than just being an industry-favorite, learning python also has numerous other benefits. Especially when you combine it with the knowledge of data structures and algorithms.

Benefits of learning Python:

  1. Python can be used to develop prototypes real quickly, because of extreme ease in reading/writing Python codes.
  1. Everything that deals with automation, data mining, or big data, requires you to have some experience of working with Python.
  1. Python makes you a lot more organized as a coder than other heavyweight languages like, say, C++ or Java. The reason for this is simple – when you code in Python, you let go of the syntactical quirks and focus on just the programming logic.
  1. Being an open-source language, Python has a massive support base. Millions of like-minded developers are there at your disposal – all you need to do is visit forums and communities.
  1. Python is what powers Django – a complete and open-source web application framework. Other frameworks like RoR can be used to simplify the development process.

With so many benefits of learning this language, combined with the definite edge a Python programmer has in the market, what do you say? Do you want to dive deeper into the world of programming using Python?

If you’re game for Python, let’s help you make Python a game for you — and make you ace at the game. Check out our specially designed Python course that will definitely set up your base right. Combined with Data Structures, this course is all you need to get a jump-start in the career as a Python developer.