Data Analytics, Big Data, Data Scientist, these are no longer big terms from a far away profession, these words or rather roles are becoming catalysts, impacting the growth of our businesses and enhancing the overall experience we get in doing our daily tasks.
Our online presence is not a matter of choice anymore; we often find ourselves using online portals to shop, connect with a doctor, research, basically from going on a vacation to preparing for motherhood, marriages, and dating, to banking, and even school and college admissions, all of these are done online, we even use social networking to express ourselves, through tweets, posts etc…,
Excessive usage of the internet creates online activity logs that contain humongous amounts of data.
Now imagine the camera’s mounted almost on every corner of the street and satellite based observations like the google map and google earth, they also collect data in large numbers on how people conduct themselves.
This data that is generated is being collected in large numbers around the clock, in real time and historic, this data further needs to be extracted, however, it is easier said than done, data is huge and extraction and explanation of the same cannot be done effortlessly. Most of the data collected is unstructured and not authentic, so you need to be wise to catch the correct characteristics at the right time.
People who can perform this extraction in a functional manner and make sense of it are called, Data Scientist or Data Analysts. The competencies that help them in this task are, sound knowledge of Mathematics, Computer Science, and Statistics.
The job of a data scientist is not only extracting data and analysing it, but to clean the data in such a manner that they can also predict and forecast trends for an assigned business, based on certain hypothesis or conditions. And that is the uniqueness they get to their job, the ability to accurately pre-process data and predict and forecast, sets one data analyst apart from the other.
A career in big data has become a dream choice for most job seekers these days, there is a lot that an organisation can achieve with the right application of data science. Some companies have identified this, and are either training their internal staff on the skills required to perform the job, while others are not yet too open to hire a full time resource. Although that day is not too far when the position of a data analyst will become imperative in every organisation.
If you are planning to enter the data science industry to make a great career in big data, then you need to adapt and acquire certain competencies and expertise in data analytics related tools, in addition to the above mentioned prerequisites. For example, programming languages, like R, and Python, SAS, a working knowledge of Machine Learning, and Predictive analysis. Also a sound knowledge in the industry you plan to work for, e.g., healthcare, or IT, Education etc.., will be an added advantage.
There is a huge gap between the demand and available resources in the field of data science, hence making a career shift in this direction would be wise and also lucrative, recent researchers have suggested that a data scientist earns more than experienced engineers. Clearly, this is a field with huge potential.
Do take up certifications, that will further assist you to springboard yourself in the field of data science.
There is a lot of confusion in the data science Job, as it is relatively new profession. We have got a lot of queries about Data Scientist salary and there career path. In this blog will talk about the how data scientist came into a picture and what is the starting salary for this job.
Statistics state that history’s most unbalanced demand and supply ratio is seen today in the Big Data Industry. It is known that in the U.S.A there would soon be a shortage of around 140,000-190,000 professionals, with the required skill set for data analytics. With a tsunami like amount of information being generated by firms on a daily basis, it becomes difficult to for them to make sense of it.
This is where the Data Scientist or the Data Analyst comes into the picture. These are individuals equipped with a certain skill set, who can take all this information or more popularly known as data and make sense of it. They work with great volumes of data sets, study them and generate various insights which help the company prosper.
As this is a fairly new thing, there are a lot of areas which are clearly out of focus. There has been no clear distinction between the two terms ‘Data Scientist’ and ‘Data Analyst’ and people still haven’t had any clear cut idea about what is meant by either Hadoop or SAS Programming and so on.
As this field needs a specific skill set like statistics, an eye for drawing out the patterns, being great at analysis and exceptional at programming knowledge; makes the number of professionals apt for this job very limited. The fact that there has been a rising demand in the firms for Data Scientists, states that the career prospects in this field have grown exponentially.
Glassdoor placed it in the first position on the 1st, as a Best Jobs in America list. According to IBM, demand for this role will soar 28% by 2020.
It is believed that the field of Data Analytics would be further divided into three different categories. These would be for professionals who would be good at coding and creating languages to sort the data, people possessing exemplary statistical skills and those who have an eye for drawing traits and patterns from the same.
With the Data Analytics Industry becoming dynamic by the day, the prospects for someone looking to make it their career are really high. The average salary of a Data Scientist starting into this industry can range from 3lakh-4lakh and can go onto 12lakh- 20lakh per annum.
There are a lot of courses offered in Data Analytics today, whereby any aspirant can get trained in various data analytics tools like R Programming, Python, SAS Programming, Big Data Hadoop and many others.
At, Imarticus Learning we offer various short term and long term courses in Data Analytics and the tools therein.
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Data is omnipresent, it is available everywhere. We cannot deny the fact that data is changing the world in ways we cannot fathom. We are at a time, where we are witnessing innovation in the way we are collecting and interpreting this data. Big data analysis is a groundbreaking step and it is only becoming bigger by the day. We are slowly realising that the use of data in almost all aspects of our lives, is actually making our lives simpler, at the same time it is presenting an opportunity for us, by helping us shape the world that we live in for the good.
There are many mainstream uses of data, which can be collected from various sources, and on interpretation can produce huge values. For example, e-commerce sites, that increase revenue with the inputs from customer feedback and shopping pattern.
Eventually, every aspect of our lives will be impacted by the advent of big data. It is not all buzz without action. There are some significant areas where big data is already making a difference, in fact in some areas it is doing so in a camouflaged approach.
Analytics is working in wonderful ways, and it has found some pretty interesting applications.
A quick read below will reveal some unobserved ways in which big data is touching our lives :
1. Enhanced Sport Performance
Most select sports are now using the benefits of big data analytics, video analytics is used to map the performance in football or baseball, sensor technology is also used in the sports equipment such as basket, golf clubs which relay feedback over smartphones, via cloud servers, on how to improve performance in the game. Health bands help track activities of sport persons outside of the sporting environment to keep a check on their nutrition and sleep also social media usage and conversations to understand the psychological wellbeing.
2. Elevating Machine Performance
Big data tools are used to control autonomous cars, for example, Toyota’s Prius is equipped with GPS, powerful computers, and sensors to safely drive on road without human intervention. Computer performance can also be enhanced by using big data tools.
3. Augmenting and Refining Cities and Countries
Many cities use big data to improve aspects of its functioning. For example, traffic situations could be better controlled, by getting factual data, by weather understanding and through social media. Some cities ae planning to use big data to upgrade themselves as smart cities, where the transport, infrastructure and utility processes are all interconnected. In other words, a train would wait for a delayed plane, or where traffic signals change their functioning on predictions to minimize traffic jams.
4. Use of Sentiments in Elections
Big data analytics can impact the way we choose our leaders, or perhaps the way the leader ensure we choose them by appealing to our sentiments and needs, voter models are designed to identify specific voters who could make a difference in elections and specifically target messages to those voters. The Obama campaign in 2012 presidential elections took this to another level into their stride.
5. Better Healthcare
Big data, with its computing ability, can assist us to decode entire DNA strings in moments. This will allow us to achieve better results and maybe understand or better still predict disease patterns. It can almost help us identify epidemics and outbreaks by linking data from medical records along with social media analytics, and imagine all this will be in actual time. Just by reading messaging like ‘not feeling good today” or “in Bed no energy” on social media.
As time extends, there will be many applications and tools of big data that will have a variety of possibilities. While it can be debated how this data is invading our privacy, it is best to look at the bright side and acknowledge how this data will make our lives easy.
By now it is mostly common knowledge, that Big Data is essentially a large volume of information collected through myriad sources, in various formats, it is also understood that this big data has a key to all future plans and strategies that the company needs to adopt if it truly wants to succeed.
True, big data is information gathered from the internet enabled services, social media, and other similar sources. It can be typically characterised by 4 V’s…
- Volume – it is getting vast as compared to the traditional sources through which data used to be captured
- Variety – data comes from various sources, machine generated and people generated
- Velocity – the speed at which this data is being generated, it is phenomenal and never stops
- Veracity – basically the quality of data, as one has little control of the volume.
The evolution of the technology has helped organisations apply the findings, not only while strategizing but in almost every aspect of the functioning of an organisation. For internal and external benefits. Merely capturing data is not beneficial, but to understand what insights you get from that data is paramount in decision making. In the ever-evolving business environment, having historical insights is not enough, but to get accurate future predictions, using data analysis and predictive modelling and visualisation techniques is also colossally essential, mostly while developing strategies.
Big data, eliminate intuition such that all imperative decisions can be made through a structured approach, and with a data-driven insight.
To put it simply it is a broad three-step process performed in a loop. (a) Manage Data- extract relevant data (b) Perform analytics on the data – gain insights and use algorithm’s (c) Make Decisions.
Big Data can further Benefit organisations in the below mentioned 5 areas
- Comprehend market Conditions – through big data, organisations can predict what future customer behaviour will be, purchasing patterns, choices, product preferences. This will leverage the company, and help contest competitors.
- Know your Customer Better – through big data analysis, companies come to know the general thought process and feedback in advance and make course corrections. Companies can reduce complaints and act on it before it becomes big. There are big data tools that predict negative emotions, prompt action can be taken to mitigate the same by organisations.
- Control Online Reputation – Sentimental analysis can be done through Big Data Tools; thus a company can check on what is being said by whom online and manage their online image efficiently and effectively.
- Cost Saving – firstly, there might be an initial cost of application of big data tools, but in the long run, the benefits will outweigh the cost. Secondly, with the application of real-time big data tools, the IT staff will be less burdened, so these resources could be used elsewhere, and lastly, the application of big data technology will make storing of data easier and more accurate.
- Availability of Data – Through Big Data tools, relevant data can be available, in an accurate and structured format, in real time.
The value of Big Data Insights is priceless. One needs to have the patience and discipline while application of the same. Ask the right question to gain accurate insights. With the quality of data, the possibilities are great, for businesses to flourish.
It’s no longer a question whether an association needs Big Data technique. It’s an issue of how soon they grasp it. IT experts are scrambling to get certified in Big Data or Hadoop, which is relied upon to end up basically the most heated tech-expertise in the following couple of years. Huge Data is gradually receiving noticeable interest known everywhere throughout the world, as organisations overall verticals like utilities, retail, media, pharmaceuticals, vitality, and others are grasping the most current IT idea. This is also the reason why Big Data training and certifications in big data have become so popular in the recent years.
According to some current techniques, numerous association did not have the capacity to meet the requests of the client because of the unpredictability of information to break down and prepare the information. To dodge these sort of issues, Organisations are actualizing Big Data innovations. Overall areas of the world, 53% of the 1,217 organisations had embraced no less than one Big Data activity.
Why Big Data Certification?
The truth of the matter is, organisations are attempting to get Hadoop ability. Ventures embracing Hadoop need to be guaranteed that individuals they contract can deal with the petabytes of Big Data. The testament is a proof in such manner, making a man in charge of the information.
The following happen to be the benefits of big data training, especially with Hadoop:
- Taking after are a portion of the regular points of interest Big Data affirmation offers.
- HR managers and HR groups are chasing for aspirants having big data and Hadoop certifications. It’s an unequivocally preferred standpoint over those having no affirmation.
- Huge information accreditation gives an edge over different experts, in regards to the compensation bundle.
- Hadoop, as well as big data certification, helps an individual quicken vocation development amid the inside employment posting process.
- One of the real points of interest Big Data certification gives is that it is useful for those attempting to change over to Hadoop from other specialised foundations.
- Hadoop certification underwrites hands-on understanding of working with Big Data.
- Confirms that an expert knows about the most recent Hadoop highlights.
- The big data certification helps in talking all the more unquestionably about the innovation to the organisation while organising with others.
While the above are the general benefits of anyone who happens to have pursued a big data training or certification. The biggest benefit of all would most definitely be the salary packages that some of the expert Data scientists receive these days. As the world becomes increasingly data driven, organisations of various stature have begun to depend on these big data magicians, to create their magic with numbers and help their respective firm’s progress.
Now for the important question. Where does a data aspirant go to get a certification in Big Data? Imarticus Learning happen to be the best in class, especially when it comes to certification in Big data courses that are thoroughly industry endorsed.
The program includes comprehensive coverage of Big Data trends, HDFS architecture, MapReduce concepts, Query tools like Hive and Pig, data loading tools and several advanced Hadoop concepts, all taught by experienced industry professionals who have 15+ years of experience in this domain.
Our program is aligned to meet the needs of the industry and the focus is always on job-readiness rather than being excessively academic. The curriculum and learning methodology is designed and vetted by our Analytics Advisory Council which features senior management from top Analytics firms to ensure effective learning. You will also have periodic guest lectures with industry professionals to help gain new perspectives and broaden your horizon.
Data engineering and data scientist are job titles which might be new to us in recent times, however, these roles have been around for a while.
Traditionally, anyone who would analyse data would be called a Data Analyst, and the person responsible for creating platforms to support the analysis is a Business Developer.
In the world of IT, the data scientist gets more visibility and praise, as they are the ones, extracting vital intelligence from big data and help organisations take critical decisions with regards to their business swiftly. But it is important to note that the data scientist does not work in isolation, they are not capable of generating valuable information independently, and they need the constant support of Data Engineers. The engineers are the ones designing and maintaining software and platforms that operate the big data pipeline. They set the stage and keep it running.
A Data Scientist is someone who is an excellent statistician, with above average software engineering skills. Should be primarily inquisitive, have the skills of data visualisation and storytelling along with programming skills. His tasks would essentially be to identify the question and finding answers through data, finding a correlation between dissimilar data, to be able to tell the findings, hence storytelling ability, and lastly should be hands on with tools like Julia, Python Programming, data visualisation tools like Qlik view or Tableau.
The description of Data Engineers and Data Scientist can be quite obscure, there is an overlap. While these roles still maintain to be distinct data science job roles, they require different skills and experience. Some data scientist can do data engineering, while some data engineers can do data analysis and visualisation as well.
The emergence of big data has opened space for new titles and roles to come into existence. Over the past couple of years’ businesses have applied all means to get individuals who have the skills to turn data into gold.
A lot has changed in the way businesses function, earlier a lot of companies were functioning in the physical world, nowadays most businesses function on the digital platform. When a company is mostly functioning online, there is a huge accumulation of data. Data about who is visiting your website, if they are choosing your competitor’s website as opposed to yours, what could be the reason, you also get data about the statistics of the competitor’s target audience, So the possibility of the data accumulation is too big and very fast. The data are screaming information and is noisy beyond comprehension.
In order to find a way in this data, one needs to sort this in two ways,
Firstly, to create a database to process the data and to store it and the second would be the need of people to comprehend the data and know how to ask a relevant question and research the data in a method that the concerned business can take informed pointers from it. This stored data needs people who know statistics who know how to write code, in order to get insightful information.
Data Scientist and Data Engineers are these people; they are the need of the hour. To know how to process data using various platforms, and more importantly, we need them to be around, These people also know how making sense of the information, how to analyse it. They don’t only plot graphs from data collected from a spreadsheet but also create statistical models that over a period of time affects the business and products with effective ways to increase the revenue.
The data available could be stand but smart and appropriately skilled people are the ones who help find that needle in the haystack.
You cannot achieve tomorrow’s results using yesterday’s methods, and this line is the need to understand and accept the impact of BIG DATA and growing demands of business.
Big data means access to big information, leading to abilities in doing things you could not do before.
Case in point – a small exercise…
Before you read ahead, check the posture you are sitting in, now look around and check the posture of others sitting beside you, observe… what do you see? Someone is slouching. Someone has their legs crossed, elbows resting on the armchair, palms pressed against their chins, a constant moving of the limbs. Not everyone sitting around you has the same posture. What if we put many sensors on the chairs around you to help record and create an index, which is unique to you, which says person X sits in these particular postures during specific intervals of the day?
In addition, say what if this data was sold to car manufacturers as an anti-theft design to help recognise that the person sitting behind the wheel is not the same and say until he keys in a password the car even though entered would not start.
Now imagine what if every single car in the world had this technology, think of the benefits of aggregating this data. Maybe we would be able to predict which postures while driving would lead to an accident say in something as close as the next 7 seconds do, and alert the driver to change position or take a break from driving.
Now my dear reader THAT is the power of BIG DATA. It can help record, collect, understand, predict, and prevent events from a random collection of information.
So if that is so useful where lies the problem? Why is the world not already a better place?
Because there is a gap between opportunity and demand in skilled professionals to help comprehend and present valuable insights into specific relevant trends, big or small from the available data.
Big data is all around us and there is a calling need to preserve all the generated data for the fear of missing something that could be important. Hence, comes the need for big data Analytics, Big data is crucial to do better business, to take accurate decisions and in always being a step ahead of your competitors. Therefore, if you are a professional in the Analytics domain there is a sea of opportunity waiting for you to dive in.
Big data Analytics is Unfathomable and depending on the environment one can choose from
- Prescriptive Analytics
- Descriptive Analytics
- Predictive Analytics
Big Data Analytics market is predicted to surpass $125 billion in between 2015 – 2020, which in turn in some sense means handsome pay brackets for the skilled individual.
- Salary Aspect
To improve the performance of the organisation, most companies have either already implemented or are in the process of implementing Big Data Analytics, as they already have the data at their disposal.
- All Organisations adopting some form of Data Analytics = Growing Market
There is a big gap in skilled professionals who are able to convert the data available. The ability to see small trends from the pool of big information. Which ultimately advances the organisation in the right direction. There are two types of talent deficits. Data consultants – who have the ability to not only, understand but also use the data at hand in the appropriate way and the other is Data Scientists who can perform analytics.
- Skill Deficit
Big data Analytics is not restricted to any specific Domain; it can be and in recent times is being used in Healthcare, Automobiles, Manufacturing and more, creating a massive global demand.
- Global demand across industries
Analytics becomes a competitive resource for organisations, according to certain studies Analytics has already become the most important asset in current times. Because we are emerging from the undeveloped analytics trends to more advanced forms. It is undeniable that Analytics plays a vital role in decision making and taking strategic initiatives for the business.
- Importance of Analytics for Better Decision Making in Organisation
So in deduction to the above, Analytics no matter how advanced is human dependent. These are exciting times for skilled people who can comprehend data and give valuable insights from the business point of view. A trained individual with the right Analytics insight can master an ocean of big data and become an indispensable asset to the organisation becoming a springboard to the business and their career.
Did you enjoy knowing about Big Data Careers? Read some of our Blogs:
Today’s society is absolutely in throes of a pulsating data revolution. Every kind of information out there, including information about the most minute of details, like for instance, the life forms thriving in the smallest inch of earth, is available online. This very information is rapidly being converted into data, that is accessible and can be read by machines. New ways are being discovered, to make great progress, across a number of fields and industries, all of which are on the basis of analysing of data. Many experts belonging to the field of Data Science believe, that the future holds a lot in store especially when it comes to innovation with data. As technology progresses, the world finds better ways to adapt, in terms of collecting, storing and analysing data. It won’t be long until the time when our economies and societies are fully data driven.
While data is gradually becoming one of the key drivers of the 21st Century economy. Data Science and Data Analytics, both these concepts have shown incredible potential, for stimulating innovations as well as progress in various different areas of the industry. Since its emergence, people belonging to the IT sector or other related industries, have been able to understand the complexities of the world, in a much better way, which has then prompted them to make better decisions, for the growth and development of their respective firms. As the world and humankind evolves, it gets more complex and the advent of technology is ensuring that we are able to make sense out of this melange of complexities. Take for example cars manufactured by the Tesla company, which specializes in manufacturing self driven cars and is also trying to make use of non-conventional energy resources in the place of fuel and gas for cars. From a lay perspective, this is what is meant by Data Driven Innovation.
Big Data, probably is the most used term in the corporate world these days. It basically refers to the process of various firms and companies, which gather enormous amounts of information, in the form of large data sets, which are frequently updated to be further analyzed and used, in order to make value based decisions for the furthering of the companies. In the earlier days, companies and firms especially in the service sector, had to host a number of surveys and take into account samples (set of people for an experiment) and then make assumptions, as to how it would impact the larger society. With the introduction of Data Science and Big Data, companies no longer have to collect data sporadically, as they can very well generate their own data. The generation of their own data may possibly depend on a number of sources, but one of the most popular sources would be inviting consumers to provide feedback on the various, different products and services they provide. Another very important source of data is the Internet of things, which is a term that is used in reference to a number of devices, which are wirelessly connected to any particular network. This is how data driven innovation has been taking place and as the area for this development increases, the number of people wanting a make career out of Data Science also multiplies.
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The best possible example of the usage of big data analytics can be found in the legendary fictional works of Sir Arthur Conan Doyle. Sherlock Holmes, as we all know him today through the famous crime detective show, Sherlock is said to be one of the biggest patrons of this concept. The world’s first consulting detective, Holmes once said, “It is a capital mistake to theorize before one has data.” These words uttered during the case of A Study in Scarlet, hold true as data proved to be his timely assistant in solving extremely difficult cases, by helping him come to perfect deductions.
As we accumulate more and more of this data, we feel the need to have optimal processing skills and analytical capabilities in order to process it. India, as a country has been making a lot of growth with many government agencies and private companies, getting on board with the data analytics revolution. Continuing in the same vein, the Comptroller and Auditor General (CAG) has also put together the ‘Big Data Management Policy’ for Indian audit and accounts departments, in order to foster the use of data analytics and ensure the improvement of their functions. Many more efforts are being taken in the same regard, like for instance the Centre for Data Management and Analytics (CDMA) has been inaugurated, in order to synthesize and integrate relevant data for auditing process. The aim here is to exploit data rich environments, on both the state level as well as the central level in order to develop the audit and accounts department.
Data has always helped humans in increasing the level of their decision making skills, in every field of medicine, science, and technology. The recent couple of years saw a great surge in the availability and accessibility of Big Data and its storage options. With big data coming to the fore, it has begun arriving on the scene with alarming velocity, volume, and variety. With so many technological advancements revolving around the accessibility and storage, have led to the opening up of new and empowering possibilities.
On the other hand, there are DISCOMS, which are set up for capturing all the data from the sensors, which are installed in order to analyse the power usage patterns, so as to put together preventive measures for Aggregated Technical and Commercial losses. All the cloud based and predictive analytics solutions given by industries in retail, telecom, and healthcare, have collectively resulted in the rapid growth of the country’s industry and economy. Today as it stands, India has about 600 data analytics firms, in addition to the 100 new start-ups, that have been set up in the year 2015. This clearly reflects on the demand for data scientists in the not so far away future. This is why a number of students have been attracted to the field of data science. As not many generic educational institutes are able to provide the required training, many candidates seek help from professional training institutes like Imarticus Learning, which provide a number of industry endorsed courses in the field of Finance and Data Analytics.
The field of Artificial Intelligence seems to working on a winning streak. In the year 2005, the U. S Defence Advance Research Project Agency, held the DARPA Grand Challenge, which was supposedly held to spur development of autonomous vehicles, basically in order to make self-driven, smart cars. This challenge was taken up and successfully completed by 5 teams. In the year 2011, in a great competition of Jeopardy, the IBM Watson system, was successfully able to beat two long time, human champions of the same legendary game. Another great win of technology over the human race would be in the year 2016, when Google DeepMind’s AlphaGo system was able to successfully defeat the world champion of Go Player, who was reportedly the world champion for 18 consecutive times.
While these feats of technology over the human brain are extremely commendable, today the long surviving dream of humans, which basically revolved around developing technology to control their surroundings, has finally come to fruition. This has resulted in the form of Google’s Google Assistant, Microsoft’s Cortana, Apple’s Siri and Amazon’s Alexa. As a result of all of these AI (Artificial Intelligence) powered virtual assistants, people are able to make greater use of technology in order to live better lives.
Artificial Intelligence is considered to be a field of computer science, which is entirely devoted to the creation of computing machines and systems, all of which are able to perform operations that are similar to human learning and decision making. According to the Association for the Advancement of Artificial Intelligence, AI is, “the scientific understanding of the mechanisms underlying thought and intelligent behaviour and their embodiment in machines.” While these intelligence levels can never be compared to those of the humans, but they can certainly vary in terms of various technologies.
Artificial Intelligence includes a number of functions, which include learning, which primarily includes a number of approaches such as deep learning, transfer learning, human learning and especially decision making. All of these functionalities can later help in the execution of various fields such as cardiology, accounting, law, deductive reasoning, quantitative reasoning, and mainly interactions with people, in order to not only perform tasks, but also to learn from the environment.
While the recent changes may be extremely mind blowing, the promise of AI has always been existing since era of electromechanical computing, this began in the time period, after the World War 2. The first conference of Artificial Intelligence was held at the college of Dartmouth in the year 1956 and at that time, it was said that AI could be achieved within the time period of summer. Later on, in the 1960’s there were scientists, who claimed that in the next decade, it would be possible to see various machines controlling human lives. But it was in the year 1965, when the Nobel Laureate, Herbert Simon, who is supposed to have predicted the words, which would have some substance and which were, “In the next 20 years, it would be possible that machines would be able to do any work of labour that man can”.
With Artificial Intelligence, going in full fervour, the field which it has affected most in the field of Data Science. And as there are many who believe that there is a great to achieve in this field, have begun to get trained in the same by approaching professional training institute – Imarticus Learning.