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In songs, poems and novels the term ‘cloud’ has been used since time immemorial. Who can forget the famous lines of William Wordsworth, “I wandered lonely as a cloud…” Despite this gap between imagery and actuality, “the cloud” has succeeded in becoming the agreed-upon shorthand for modern data storage. As far as it relates to computers, the term “cloud” dates back to early network design, when engineers would map out all the various components of their networks. The term ‘Cloud computing’ has been there since the early 2000s, but the concept of computing-as-a-service is much older than we might think. It goes back to 1960s when computer bureaus were built to rent time on a mainframe for companies instead of buying one.

By the emergence of the PC in 1980s, these ‘time-sharing’ services were completely replaced, as it had become cheaper to own one’s own computer to store and access data.

But in due course of time when a large data has been collected over internet the concept of renting access to computing power has come in to play repeatedly — like utility computing, and grid computing of the late 1990s and early 2000s.

This was followed by cloud computing, which really took hold with the emergence of software as a service and large scale cloud computing providers such as Amazon Web Services, Microsoft Azure, Oracle and many others.

Cloud computing is a method of storing and accessing data and programs from any device that can access the internet. It has reduced the requirement of a computer’s hard drive.

The data in the cloud is stored on several physical and/or virtual servers that are provided by a third-party service provider.

Types of cloud services

There are three basic types of cloud services:

Software as a Service (SaaS)

It is the most commonly acknowledged cloud service software. This includes a variety of services, such as file storage and backup, web-based email and project management tools.

Examples of SaaS cloud service providers include Dropbox, G Suite, Microsoft Office 365, Slack and Citrix Content Collaboration. In these applications, users can access, share, store and secure information in “the cloud.”

Infrastructure as a Service (IaaS)

Infrastructure as a service, or IaaS is a cloud-computing offering in which a vendor provides users access to computing resources such as servers, storage and networking. It serves as the complete data center framework, eliminating the need for resource-intensive and on-site installations.

Examples of IaaS are Amazon Web Services (AWS), Microsoft Azure and Google Compute Engine. In these providers all storage servers and networking hardwares are maintained. Providers manage security, operating systems, server software and backups.

Platform as a Service (PaaS)

Platform as a service, or PaaS, serves is a web-based service where developers can create cloud apps. PaaS enables its users to access a database, operating system and programming language that can be used to develop cloud-based software.Many IaaS vendor also offer PaaS capabilities.

Cloud computing for Engineers

Cloud computing is one of the hottest technologies with a high demand for qualified professionals. Since it is a specialty area it is not an easy thing for an individual to acquire a job in this field.

Some skills required for obtaining a secured position in cloud computing are:

Programming Languages and Coding Skills

Java and C languages are two of the most common languages, but these are rarely used in creating cloud computing services The data-oriented programming languages like SQL, XML data language, and R Math Language, in addition to Python and Ruby are needed in addition to exceptional coding skills.

Linux

This is another skill required for cloud computing job. At present bout a fourth of the servers is powered by Linux based Microsoft Azure and it is definitely going to increase with the coming days.

Cloud Security

Security is an in important factor when cloud storage is concerned. It is one of the primary aspect developers are looking into.To secure the data of their organizations, professionals can use various security tools in the market.CCSP (Certified Cloud Security Professional) training provides an adequate and professional understanding of Cloud Security.

Artificial Intelligence (AI)

The technologies that can perform exemplary actions at data integration, aggregation, and analysis without human assistance like: Artificial Intelligence and Machine learning are gaining more attention in the field of Cloud-based technology

Database Management Skills

Collecting, storing, maintaining, and accessing data stored in the cloud is pivotal to cloud systems. Hence, data management becomes a most significant skill. Along with this Data-oriented languages like SQL and Hadoop are a must.

Cloud Platforms

Amazon Web Services (AWS) and Microsoft Azure are two of the leading cloud platforms including some others. So doing a certification course on these platforms can provide better opportunities.

Business and Analytical Skills

In addition to the technical skills, business and analytical skills are also important for cloud computing job which helps in managing, communicating, and negotiating business within an organization and also with cloud providers.

DevOps

It is the most commonly used framework in cloud computing.

DevOps is a process of software development. DevOps means combination of Dev (software development) and Ops (information technology operations) to lessen the application development life cycle. There are various tools such as Monit, Jenkins, or ELK that can be useful.

 “I don’t need a hard disk in my computer if I can get to the server faster… carrying around these non-connected computers is byzantine by comparison.”  Steve Jobs, Co-founder, CEO and Chairman of Apple Inc.

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“[M]achine learning will bring about not just a new era of civilization, but a new stage in the evolution of life on earth.”― Pedro Domingos

Communication is the basic phenomena in the nature. All species communicate to each other. The languages are nothing but a medium to represent the thoughts but as technology evolves people can talk to machine also. For example Siri or Alexa, Facebook friend suggestions, Gmail spam filters, traffic congestion predictions are some common examples where one talks to a machine and all this is machine learning.

Machine Learning (ML) is emerging as one of the hottest fields today.“Machine learning is the study of computer algorithms that allows computer programs to automatically improve through experience” as defined by Computer Scientist and machine learning expert Tom M. Mitchell.

The scientific field of machine learning (ML) is a branch of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed by relying on patterns and inference instead.

How does machine learning work?

Machine learning utilizes a variety of techniques to intelligently handle large and complex amounts of information to make decisions and/or predictions. It describes computer algorithms trained with real-world data to build predictive models.  An algorithm can be thought of as a set of rules/instructions that a computer programmer specifies which a computer is able to process. Machine learning algorithms are learnt by experience, similar to as humans do. For example, after having seen multiple examples of an object, a compute-employing machine learning algorithm can become able to recognize that object in new, previously unseen scenarios.

In practice, the patterns that a computer (machine learning system) learns can be very complicated and difficult to explain. Once the machine learning model has been trained, we can give different images as input to see if it can correctly differentiate between them.

Types of Machine Learning

There are different types of machine learning for different kinds of problems. There are generally two categories: supervised and unsupervised – but sometimes combination of both is also used.

Supervised Machine Learning

In Supervised Machine Learning our training data contains known, correct answers for the thing we’re trying to predict. It’s called supervised because we can easily evaluate how good our model is while it is being trained by comparing it to known correct answers. Most machine learning algorithms fall into the supervised learning category including regression, decision trees, XGBoost, and many more.

In the field of machine learning, the thing we try to predict is the label. So, supervised machine learning deals with labeled training data.

Unsupervised Machine Learning

Sometimes, we try to find hidden patterns in the data we have. The goal in unsupervised learning is generally to cluster the data into characteristically different groups. Unsupervised machine learning is more challenging than supervised learning due to the absence of labels. The unknown attributes are called latent features. Techniques such as K-means clustering, principal component analysis, latent Dirichlet allocation, and K-nearest-neighbors can be used to uncover these latent features.

Here as we don’t know the correct answers, unsupervised algorithms use unlabeled training data.

Semi-Supervised Learning

Real-world projects aren’t always so definite.

In this type of learning, the algorithm is trained upon a combination of labeled and unlabeled data. Typically, this combination will contain a very small amount of labeled data and a very large amount of unlabeled data. The basic procedure involved is that first, the programmer will cluster similar data using an unsupervised learning algorithm and then use the existing labeled data to label the rest of the unlabeled data.

 Supervised learning is used to train a model that assigns labels to unlabeled data, based on the human-generated labels it receives. With some practice we can compare the labels produced by the supervised algorithm to the labels produced by humans. As they start to agree, we can use the supervised model to label our training data instead of humans in cases where the model has high confidence. Those machine-generated labels are called pseudo-labels. Since our training data now contains a mixture of known labels assigned by humans and data that was inferred by a model, these models are called semi-supervised.

Areas where ML is employed

Machine learning technology has immense advantages in the industries which are working with large amounts of data. It has been observed that the organizations working with ML are able to work more efficient and be ahead their competitors.

Financial services

The two key purposes to use machine learning technology in banks and other businesses in the financial industry are to identify important insights in data, and prevent fraud. It can also identify investment opportunities, or help investors know when to trade. Data mining can look for clients with high-risk profiles, or use cyber surveillance to prevent from any fraud.

Government

Government agencies such as public safety and utilities utilize machine learning by collecting data through sensors from various inputs to fetch desired results. Machine learning can also help detect fraud and minimize identity theft.

Health care

Machine learning is growing at a fast pace in the health care industry, with the addition of wearable devices and sensors that can use data to assess a patient’s health in real time. The technology can help the medical field to analyze data to identify trends that may lead to better diagnoses and treatment. 

Retail

When we online shopping on any website it provide us recommendations for the items we might like based on our previous purchases using machine learning. Retailers use machine learning to capture data, analyze it and use it to personalize a shopping experience, implement a marketing campaign, and merchandise supply planning. 

Oil and gas

Machine learning can be used to finding new energy sources, analyzing minerals in the ground, predicting refinery sensor failure and streamlining oil distribution to make it more efficient and cost-effective. The number of machine learning use cases for this industry is vast – and still expanding.

Transportation

The data analysis and modeling aspects of machine learning are of great importance to delivery companies, public transportation and other transportation organizations. Machine learning is utilized to analyze data to identify patterns and trends in the transportation industry, which helps in making routes more efficient.

Career Opportunities in ML

There are some of the best engineering colleges in Delhi NCR which offer 100% Placement .

Job opportunities in Machine Learning

1. Machine Learning Engineer – They are sophisticated programmers who develop the systems and machines that learn and apply knowledge without having any specific lead or direction.

2. Deep Learning Engineer – They are specialized in using deep learning platforms to develop tasks related to artificial intelligence.

3. Data Scientist – They extract meaning from data and analyze and interpret it. It requires methods, statistics and tools.

4. Computer Vision Engineer – They are software developers who create vision algorithms for recognizing patterns in images.

Machine learning has already and will change the course of the world in the coming decade.

Therefore, there is a huge scope of Machine Learning in India, as well as in other parts of the world, in comparison to other career fields when it comes to job opportunities. According to Gartner, there will be 2.3 million jobs in the field of Artificial Intelligence and Machine Learning by 2022. Also, the salary of a Machine Learning Engineer is much higher than the salaries offered to other job profiles.According to Forbes, the average salary of a Machine Learning Engineer in the United States is US$99,007. In India, it is ₹865,257.Thus, the future belongs to the Machine Learning, and one has a bright future if he/she becomes an ML professional.

“Machine learning will automate jobs that most people thought could only be done by people.” ~Dave Waters

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Life in lockdown
The global lockdown has made us confined to our primeval cave-like shelter of home. The post-global earth is in suspended condition as if it needs some time for hibernation. Surely the world will change permanently after this and if we are fortunate enough to see the post-Corona world, we will reminisce about our pre-Corona days. These are unprecedented times, a never-before, and perhaps never-after world that we now live in. Groping in the dark, in this age of social distancing, we have got the time to reflect on our idiosyncrasies. How do we transform ourselves from the flashy Joneses and beard ourselves in our dens? Let us accept the newfound world as it is, and hope against hope. Youth is the most precious resource of a country. They are the future, current times are challenging for them the sudden change in the educational system has affected not just their lives but even their psyche.

Effect of COVID-19 on Education System
Indeed, a sudden jolt, the COVID-19 pandemic has affected educational systems worldwide, leading to the near-total closures of schools, universities, and colleges. According to the UNICEF monitoring, 106 countries are currently implementing nationwide closures and 55 are implementing local closures, impacting about 98.6 percent of the world’s student population. Approximately 1.6 billion children and youngsters are unable to attend physical schools due to temporary closures and lockdowns.

There is a severe impact of coronavirus on higher education. Universities and college campuses are the places where students live and study in close proximity to each other. They are also buzzing cultural hubs where students are brought together from nations around the world. Recently, the foundations of this unique ecosystem have been impacted significantly by the rapid spread of the coronavirus (COVID-19) outbreak, creating uncertainty regarding the implications for higher education. Over the past weeks, education officials have been forced to cancel classes and close the doors to campuses across the world in response to the growing coronavirus pandemic. But, knowledge cannot be confined within the boundaries even during the lockdown. This phase can be utilized by our youth to learn, enhance their knowledge, and upgrade their skills, so that one can become future ready, to take up the new challenges.

Invest your time in learning
In the “live with COVID” era, a lot of options will be forced to develop to replace the conventional style of functioning of man-machine and knowledge delivery. The year 1985 implemented the digitalizing of education in India by the central government. DIGITAL INDIA projects are playing a conspicuous role in imparting education.

Conferencing apps such as Zoom, Google Classroom, Google Meet, and Webex are the popular apps used for conducting interactive classes. All India Radio is broadcasting syllabus based educational contents daily in its VIDHYABHYASA RANGAM program. Television channels reach out to students in a better way since they can telecast video, multimedia content and audio simultaneously. For example, Doordarshan in collaboration with the government of Bihar started a programme named MERA DOORDARSHAN MERA VIDHYALAY. This programme is a big hit in states where education facilities in rural areas are less. ‘Diksha’ an educational programme by MHRD is conducting various courses for lessons, plans, etc. can be accessed from DIKSHA and teachers can easily upload educational resources created by them. NATIONAL REPOSITORY OF OPEN EDUCATIONAL RESOURCES (NROER) established in 2013 by MHRD and developed by NCERT is also an open resource platform for digital resources for class 1 to 12.

Video audio documents and interactive contents are available online. SWAYAM is a programme initiated by the Government of India aimed at offering everyone, easy access to high-quality digital aides and resources. Premier government organizations host this programme. Subject-specific courses conducted by SWAYAM are available free of cost to the learners. Undergraduate education supported by NPTEL, AICTE, CEC, IIM Bangalore. Postgraduate education supported by NPTEL,AICTE, IIM Bangalore, and UGC. UGC has started promoting online courses by higher educational institutions. The distance education bureau of UGC is managing these programmes. Various universities and SCERTs are also supporting digital education in all possible ways. One can access a large volume of digital resources from YouTube and other social media platforms. YouTube is the largest source of digital learning material. Take the membership of free Digital libraries.

Challenge or Opportunity?
It is not doom and gloom phase completely. Every challenge comes with some hidden opportunities. This time can be utilized by the youth to develop their skills, learn from the rich resources available to them. No barriers can stop the youth from learning and attaining knowledge. With the hope that the educational institutions will reopen soon and then things will be back to normal. As the students are coming into terms with the new normal the educational institutes are also gearing up.

Universities and colleges are also implementing changes to campuses in response to the novel coronavirus. The steps are already being taken by the educators to understand what has worked, what hasn’t worked, and how to tackle the challenges they may face. With the spread of the disease expected to worsen before it gets better, administrators are taking quick action to safeguard their campuses and students.
The campuses are also ensuring safety and are preparing themselves for the new normal, measures like sanitization tunnels, temperature checks, monitoring safety by technology surveillance, rigorous campus cleansing, etc. are being implemented for the safety.

The higher education sector has withstood turbulent economic times in the past, and it withstands them again. In a digital age, universities and colleges are better placed today more than ever to provide students with easy access to continue their studies online. They are ready to prepare their students for post corona times and are thus coming up with courses on trending technologies such as IoT, AI, Data Science, Machine Learning, etc. which will be in high demand in the market and this demand is expected to grow exponentially in the coming decade.

Hoping against hope
The youth today is unable to hang out with their friends, peers, and classmates like they used to, and are not being able to expend their energy on sports, is not be easy on them. They have to cope up with the new mechanisms, build and strengthen their connections with supportive adults, including their teachers. Things will be back to normal one day.“Hope begins in the dark. The stubborn hope that if you just show up and try to do the right thing, the dawn will come. You wait and watch and work: you don’t give up.” – Anne Lamott, Novelist

“Our progress as a nation is no swifter than our progress in education. The human mind is our fundamental resource.” John F. Kennedy

Education plays a significant role in the growth of a nation. In a country like India education and knowledge have always been given substantial value. In ancient India, the aim of education was to develop the pupil’s personality, his innate and latent capacities as a process of one’s inner growth and self-fulfillment. The education system also needs to transform according to the ever-changing needs of the society and the world. Thus, for the overall development of the education in and the progress of the nation, a proper policy is needed. The National Policy on Education (NPE) is a policy formulated by the Government of India to promote education amongst India’s people. The policy covers elementary education to the colleges in both rural and urban India. The first NPE was promulgated by the Government of India by Prime Minister Indira Gandhi in 1968, the second by Prime Minister Rajiv Gandhi in 1986, and the third by Prime Minister Narendra Modi in 2020. The National Education Policy 2020 (NEP) brings reform after 34 years, especially in higher education, shifting focus from academic to non-academic activities. An NPE is a comprehensive framework to guide the development of education in the country. Recently, the Union Cabinet has approved the new National Education Policy (NEP), 2020 with an aim to introduce several changes in the Indian education system – from the school to college level. The NEP 2020 aims at making “India a global knowledge superpower”.

The Cabinet has approved the renaming of the Ministry of Human Resource Development to the Ministry of Education.

Key Points:
School Education:

• Universalization of education from preschool to secondary level with 100% Gross Enrolment Ratio (GER) in school education by 2030.
• 2 crores out of school children are going to be brought back into the mainstream through an open schooling system.
• The current 10+2 system is going to be replaced with a new 5+3+3+4 curricular structure corresponding to ages 3-8, 8-11, 11-14, and 14-18 years respectively.
• The uncovered age group of 3-6 years which is being recognized globally as the crucial stage for the development of mental faculties of a child, is also considered under school curriculum,
• It will also have 12 years of schooling with three years of Anganwadi/ pre schooling.
• The board examinations of Class 10 and 12 are to be made easier, to test core competencies rather than memorized facts, with all students allowed to take the exam twice.
• School governance is set to change, with a new accreditation framework and an independent authority to regulate both public and private schools.
• Emphasis on Foundational Literacy and Numeracy, no rigid separation between academic streams, extracurricular, vocational streams in schools.
• Vocational Education to start from Class 6 with Internships.
• Teaching up to at least Grade 5 to be in mother tongue/regional language. No language will be imposed on any student.
• Assessment reforms with 360 degree Holistic Progress Card, tracking Student Progress for achieving Learning Outcomes
• A new and comprehensive National Curriculum Framework for Teacher Education (NCFTE) 2021, will be formulated by the National Council for Teacher Education (NCTE) in consultation with National Council of Educational Research and Training (NCERT).

Teacher Education:

• By 2030, the minimum degree qualification for teaching will be a four-year integrated B.Ed. degree.

Higher Education:

• Gross Enrolment Ratio in higher education to be raised to 50% by 2035. Also, 3.5 crore seats to be added in higher education.
• The current Gross Enrolment Ratio (GER) in higher education is 26.3%.
• Holistic Undergraduate education with a flexible curriculum can be of 3 or 4 years with multiple exit options and appropriate certification within this period.
• M.Phil courses will be discontinued and all the courses at undergraduate, postgraduate and PhD level will now be interdisciplinary.
• Academic Bank of Credits to be established to facilitate Transfer of Credits.
• Multidisciplinary Education and Research Universities (MERUs), at par with IITs, IIMs, to be set up as models of best multidisciplinary education of global standards in the country.
• The National Research Foundation will be created as an apex body for fostering a strong research culture and building research capacity across higher education.
• Higher Education Commission of India (HECI) will be set up as a single umbrella body for the entire higher education, excluding medical and legal education. Public and private higher education institutions will be governed by the same set of norms for regulation, accreditation and academic standards. Also, HECI will be having four independent verticals namely,
• National Higher Education Regulatory Council (NHERC) for regulation,
• General Education Council (GEC) for standard setting,
• Higher Education Grants Council (HEGC) for funding,
• National Accreditation Council (NAC) for accreditation.
• Affiliation of colleges is to be phased out in 15 years and a stage-wise mechanism to be established for granting graded autonomy to colleges.
• Over a period of time, every college is expected to develop into either an autonomous degree-granting College, or a constituent college of a university.

Digitalization of Education:

The new education policy has emphasized the incorporation of technology in all the stages of learning.

• An autonomous body, the National Educational Technology Forum, is going to be formed for the exchange of ideas on use of technology to enhance learning, assessment, planning and administration.
• A dedicated unit for the purpose of creating digital infrastructure, digital content and capacity building will be set up in the ministry.
• Integration of technology will be done to improve classroom processes.

Financial support:

• Meritorious students belonging to SC, ST, OBC and other socially and economically disadvantaged groups will be given incentives.
• Private institutes will be encouraged to offer scholarships to students.

Professional education:

•  Standalone technical universities, health science universities, legal and agricultural universities will aim at  multi-disciplinary institutions.

Other changes:

• An autonomous body, the National Educational Technology Forum (NETF), will be created to provide a platform for the free exchange of ideas on the use of technology to enhance learning, assessment, planning, administration.
• Creation of a National Assessment Centre- ‘PARAKH’.
• It also paves the way for foreign universities to set up campuses in India.
• It has also put emphasis on setting up of Gender Inclusion Fund, Special Education Zones for disadvantaged regions and groups.
• A National Institute for Pali, Persian and Prakrit, Indian Institute of Translation and Interpretation is to be set up.
• India spends around 4.6 % of its total GDP on education. The new Education Policy plans to increase the public investment in the Education sector to reach 6% of GDP at the earliest.

Thus, NPE has geared itself for the challenges of the 21st century. The flexibility to choose the subjects according to the interest of the student is an amazing initiative. The existing 10+2 academic structure has also been replaced with a new 5+3+3+4 pedagogical curricular structure. The experiential learning is focused upon which will help in the holistic development of a child. Our education system is now similar to the education system of the western developed countries. A ten-day bag less period with the emphasis on Vocational study is a step towards the right direction. Top 100 institutes have been given permission to set up their campuses with in India. Undergraduate courses with multiple exit options are welcomed by the educationists. Appreciating the New Education Policy our Prime Minister Sri Narendra Modi said that “ The New Education Policy aims at changing ‘intent’ and ‘content’ of education system.” The NPE is also lauded by the academicians, Byju Raveendran, Founder and CEO, BYJU’S: “India is home to the world’s largest K-12 population and the universalization of early school education, the push to improve gross enrolment ratio and a renewed focus on new life skills such as coding will help create a stronger pipeline of future leaders in India.” The NPE will begin a new era in the field of education.

“The IoT is big news because it ups the ante: ‘Reach out and touch somebody’ is becoming ‘reach out and touch everything’.” — Parker Trewin

Why is IoT so Important?
In recent years, IoT has been one of the 21st century’s most influential innovations. We can link everyday objects such as cars, cooking appliances, thermostats, baby monitors, etc. to the internet through embedded devices. Seamless communication is possible between people, systems, and items. Physical things can share and gather data with minimal human intervention by low-cost computing, the cloud, big data, analytics, and mobile technologies. In this irreducible world, digital systems can record, track, and modify any interaction between the items related.

What Technologies Have Made IoT Possible?
While the principle of IoT has been in existence for a long time, it has become a reality through a series of recent developments in many different technologies.

• Low-cost, low-power sensor technology available. Inexpensive and reliable sensors allow manufacturers to use IoT technology.

• Signing in– A host of internet network protocols have made connecting sensors to the cloud simple for efficient data transmission.

• Systems for Cloud computing– The growth in cloud platform availability allows both companies and customers to access the resources they need to scale up without needing to manage it directly.

• Analytics and machine learning– Businesses can gain information faster and easier with advancements in machine learning and analytics, along with access to diverse and large volumes of data stored in the cloud. Publication of these allied technologies continues to expand IoT’s limits, and IoT’s generated data also feeds these technologies.

• AI (Artificial Intelligence)- Advances in neural networks have introduced natural-language processing (NLP) to IoT devices (such as Alexa, Cortana and Siri digital personal assistants) and made them appealing, affordable and feasible for home-usage.

How is IoT for Industry? Industrial IoT (IIoT) refers to the implementation of IoT technology in industrial environments, in particular concerning instrumentation and monitoring of sensors and devices participating in cloud technologies. IIoT is also called Industrial Revolution Fourth Wave, or Industry 4.0. Some specific uses of IIoT are as follows:
Smart manufacturing
Preventive and predictive maintenance
Smart power grids
Smart cities
Connected and smart logistics
Smart digital supply chains

What are the Top IoT Applications? IoT’s ability to provide sensor information and allow device-to-device communication is driving an extensive array of applications. The following are some of the most popular features and what they are doing.

Establish new manufacturing efficiencies by control of the equipment and the product quality. Machines can be tracked and tested continuously to ensure that they work within the appropriate tolerances.
Enhance monitoring of physical properties and “ring-fencing.” Tracking helps businesses to identify the position of the stuff quickly. Ring-fencing allows them to ensure high-value assets are secured from theft and removal.
Use wearables to track environmental and human health analytics. IoT wearables enable people to understand their health better and allow doctors to monitor patients remotely.

Drive efficiencies in current processes and new possibilities; One example of this is the use of IoT to make fleet management effective and safer. Companies can use IoT fleet monitoring to guide trucks to boost performance in real-time.

Allow changes to business processes. One example is the use of IoT devices to track remote machinery’s health and cause service calls for preventive maintenance.

What Can Industries Benefit from IoT?
Organizations best suited for IoT are those that would benefit from using sensor devices:

Manufacturing- Manufacturers can gain a competitive advantage when sensors detect an imminent malfunction by using production line monitoring to allow take-over maintenance on equipment. Manufacturers may quickly test equipment for quality, or withdraw it from output until it is fixed, with the aid of sensor warnings.

Automotive- Industry stands to realize significant benefits from the use of IoT software. The benefits of applying IoT to production lines, sensors can also detect nearing equipment failure in vehicles already on the road and can alert the driver with details and advice. IoT-based apps, designers and manufacturers will be able to learn more about how to keep vehicles going and car owners updated.

Transport and Logistics- Transport and logistics services are benefiting from IoT applications. Thanks to IoT sensor info, motor vehicles such as cars, buses, ships and trains carrying inventory can be re-routed according to weather conditions, driver availability, and vehicle availability. The product itself may also have sensors for track-and-trace and temperature-control.

Retail- IoT applications allow retail companies to control inventory, enhance customer service, optimize the supply chain and reduce operating costs. Smart shelves with weight sensors, for example, can collect information based on radio frequency detection and send the data to the IoT network for warnings and automatically monitor when the inventory of items are running low.

Public sector- The advantages of IoT are equally considerate in the public sector and other service-related environments. For instance, government-owned utilities may use IoT-based applications to alert their users of mass outages and even smaller water, electricity, or sewer service interruptions. IoT systems may gather data about the severity of an outage and deploy resources to help utilities recover more quickly from outages.

Monitoring of healthcare- IoT assets provides many benefits for the healthcare sector. Doctors, nurses, and an attendant also need to know precisely where patient-assistance devices like wheelchairs are stored. When the wheelchairs of a hospital are fitted with IoT sensors, they can be monitored from the IoT asset tracking program, so that the nearest accessible wheelchair can be identified easily by anyone searching for one.

General safety in all sectors- In addition to tracking physical property, IoT can be used to enhance safety in the workplace; for example, employees in dangerous environments such as oil and gas fields, mines, and chemical and power plants need to know about the likelihood of a dangerous accident that could impact them. They can be informed of incidents or saved from them when they are linked to IoT sensor based applications. IoT implementations also refer to wearables that can monitor human health and environmental conditions. These kinds of apps not only help people better understand their health, but also allow doctors to monitor patients remotely.

Why does IoT change the world? IoT reinvents the car through the development of connected vehicles. Vehicle owners may use IoT to operate their cars remotely — like preheating the car before the driver gets into it, or calling for a vehicle remotely by phone. With IoT’s ability to allow device-to-device communication, cars will also be able to book their service appointments where necessary. The connected automobile allows manufacturers or dealers to transform the idea of car ownership on its heads. Earlier, producers had an arms-length relationship with individual clients (or none at all). Car manufacturers or dealers may use connected vehicles to maintain a continuous relationship with their customers. Instead of selling vehicles, they can charge drivers user fees, providing a “transportation-as-a-service” through autonomous cars. IoT lets manufacturers constantly upgrade their cars with new technology, a break from the traditional model of car ownership in which vehicles depreciate both in performance and value at once.

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Data is a precious thing and will last longer than the systems themselves” – By Tim Berners Lee, inventor of the world wide web

Do you know Recommendation Engine is the most common use case of Data Science which has crept into your daily life? Every time you’re on Amazon or Flipkart, do you see these custom suggestions saying “Things you might like”? Well, that’s a perfect example of monitoring and recognizing user search and purchase habits from Data Science algorithms, and then preparing custom recommendation lists.

Thanks to Data Science, new and exciting possibilities are opening up, constantly changing the way we see the world around us. The contribution of Data Science in transforming human lives for the better has been enormous.

Online shopping has become so much simpler thanks to sophisticated algorithms that can recognize individual users’ tastes and interests, and create recommendation lists for them. Online financial transactions have never been that safe, courtesy of Data Science’s Fraud and Risk Detection algorithms.

Not just these, Data Science has also made an enormous contribution to the healthcare field. Algorithms and applications in data science can be used in Drug development, Medical Image Processing, Remote Monitoring, to name a few.
Because data is the omnipresent force that governs our lives now, jobs are booming like never before in this arena. Machine Learning Engineers, Data Scientists and Big Data Engineers rank among the top emerging jobs on LinkedIn. Since 2012, Data Scientists’ job positions have increased by more than 650 per cent, making Data Science currently one of the hottest career sectors.

What is Data science?
The basic concept states that data science is an aggregation of data, which is organized and evaluated in a way that will have an impact on business. A data scientist, according to Google, can analyze and interpret complex data and can make use of a website’s information and assist in business decision making.

Future Scope of Data Science
Data science has emerged as one of the world’s hottest careers today. Being a data professional will broaden job opportunities and offer more options today to get lucrative salary packages. Let’s look at a few points which describe the bright future of data science.

Data science is still an evolving technology.
To stay relevant in the Industry, professionals must upgrade themselves to the latest technologies. Over the coming decade, data science is growing to provide an array of work opportunities. Because the supply is low, this is the right call for professionals seeking skills in this area.

Organizations are facing a challenge using data that is generated.
Realizing the amount of data that is to be developed in the next decade is unimaginable. It is getting difficult for an enterprise to access the value of such data. Being a professional in data science, one can help organizations make progress with the data being gathered to gain positive insights.

In-demand skill-set
Many data scientists possess the in-demand skill set that the new Industry needs today. Skills like Machine Learning, R and Python programming, Predictive Analytics, AI, and Data Visualization are the most popular skills employers are seeking from today’s candidates.

Advancement in career
The data scientist is the most promising career of 2019, according to LinkedIn. The main reason for this job to be ranked the highest is that people were being paid enormously. The study also predicts that there are high chances of winning promotion as a data scientist, giving a career development score of 9 out of 10.

Experts in data science are required in virtually every field of employment — not only in technology. There is not only a massive demand but also a significant shortage of trained data scientists. . If you have a passion for computers, math, and discovering answers through data analysis, then earning an advanced degree in data science might be your next step.

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BRIDGING GAP BETWEEN MARKET AND ACADEMIA BY NAZUK ENDLAY

India, the nation of growth is considered to be one of the emerging superpowers of the world with approximately 1.5 million engineers trained for the job market every year. With the growing economy, India is also witnessing the growth of educational sector. However, Indian industry is still looking for reforms for betterment of job-readiness of the graduates.
There is an urgent need that the industry and academia come together and address some of the underlying challenges. Though educational institutions are preparing millions of students for the corporate requirements with new and innovative internships and training programs yet there lies a question over the existent gap between the corporate requirements and the academia.
The intersecting requirements and jointly inter-reliant relationship requires identifying means of further improvement in academia-market partnerships.

Major Points of Concern:

Syllabus:
Engineering courses in India are still tuned with the traditional way of teaching. Although, new teaching methods and programs are improving things at the grass-roots level, but further reforms are required to improve the employability of candidates.

Faculty Requirements:
The traditional way of teaching engineering doesn’t let teachers to evolve. It is true that basics are important, but in this fast-pace world it is important to gain some pragmatic experience before entering the job market. Teachers need to impart this side of academia and for that, they will require training beforehand to improve the overall situation.

Improvement in Innovation and Research:
Our students think more about the result rather than fun learning. They are taught technologies that are not relevant in the 21st century which makes engineering boring. They are high on potential and talent but, lack the “out-of-the-box” thinking attitude with no inclination towards innovation and research. The things are improving on this horizon with Government of India and corporate houses providing funding for research and ensuring a brighter future for the scientists in India.

Skill Based Learning:
Education in India is still majorly theory oriented. We have observed some breakthroughs in Indian engineering academia with several competitions such as go-karting, robotics etc. But, students are still not aware of on how to apply theory in day-to-day life. They lack skills to get employed.

Soft Skills:
One the major problem arising is the continual ignorance of soft skills which are major factor when it comes to corporate employability. Students focus only on the result of placement; they spend all their time focusing on subject curriculum.

Panacea:

Aligning Curriculum with Industry:
The imperative need to re-structure the existent educational system is to address the varied needs of the dynamic industry. The curriculum needs to be regularly revised and developed in accordance with the market needs.

Shift to Practical Learning :
The classroom methodology and theory inclined approach needs to be reoriented with making the entire approach more dynamic with the help of practical hands-on learning.

Workplace Exposure :
Need to increase exposure of students to industries and market by simultaneous practical implementation through internships, live projects and corporate interactions.

Channel Industry Challenges:
Channeling some real-time industry challenges and problems to students as add-on to the curriculum; can help students to crack interviews and big jobs in the future.

Focus on Soft Skills :
Besides learning of core or technical knowledge, academia should also focus on the overall development of the student including soft and behavioral skills such as leadership capabilities, attitude, professional communication and interpersonal skills.

Its high time now for us to recalibrate the Indian education system with modern methods of teaching and training. Collaboration of industry and academia will play an important part in tapping the gap between what is given to what is actually needed.