The demands of the present day Corporate world pertaining to it's hiring-mechanisms' are being promulgated vastly due to the emergence of newer technological devices at a speed that can be characterized as nothing but rapid. And as a consequence, only those who are ready to imbibe various skills into their repertoire stand a chance of meeting the aforesaid demand and thereby stand a real chance to get a placement of their choice in this dense and immense competition. Therefore skill development has become the essential prerequisite for professional to have it in their grasps.
In setting out a clear vision and action, it is necessary to have a strategy that structures around four key areas: the skills of educators, access to technology, curriculum & assessment, and leadership. This strategy is precisely leveraged at our successful dispense that requires a coordinated effort at all levels of the system which we are obliged to imbibe into our programs.
Evidently those who want to extract the true benefits of skill development programs include both the working and the non-working professionals and the students as well. And it is this necessity at its core that drives Altimate towards a specific fulfilment.
It goes without saying that Technology has a significant contribution where our educators are supported through professional development, resources, and leadership. The skill deployments of digital technology ensure our students to develop a level of specialized digital skills that are so vital for learning, work, and life management. Imaginative use of this technology will enable an aspirant to explore the world to the extent of its realm. As a calculated projection towards future, in making students their own masters, Altimate incorporates all these strategies and resourceful technologies in fostering its pedagogical productivity to accelerate the momentum of the learning curve.
An ever-striking question that befalls before us is, how this technology can make teaching and learning practices more effective. We, the thriving educational hub, do infuse classrooms with digital learning tools such as computers and hand-held devices, course materials, 24x7 online supports, and 21st century skills that intensify student engagements and motivations.
Skill development as the term itself indicates is never a one stop-go, but rather a continuous process among other professional pursuits as such.
Any advent of new technology in general, and in particular computing systems when it is out in the public that is meant to explore and extract the utilities to empower themselves thereby, with all the freedom necessary is not by any means devoid of fangs. The most devious of the lot is the security, as it is susceptible for breach for being open in the public domain. What needs is the shield to keep everything in tact and the modes by which we safeguard everything to the minutest detail is to employ the mechanism termed Cyber Security.
The universally accepted definition of this so called mechanism goes thus:
"Cyber security is the practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks”.
It's also known as information technology security or electronic information security. The term applies in a variety of contexts, from business to mobile computing, and can be divided into a few common categories as follows: -
Network security: the practice of securing a computer network from intruders, who might well include malicious attackers as well as opportunistic malware breaches.
Application security: the practice of focusing on keeping software and devices free of any threats. A compromised application could well provide access to the data its designed to protect. Thus we can comprehend that any successful security begins in the design stage, well before a program or device in question is readily deployed.
Information security: protects the integrity and privacy of data, both in storage and in transition.
Operational security: the practice of including the processes and decisions for handling and protecting data assets. The permissions users were given access to have the network at their disposal and the procedures that go along with it determine how and where data may be stored or shared.
Disaster recovery and business continuity: The practice of defining how an organization responds to a breach of cyber-security incident that causes the loss of operations or data. Disaster recovery policies are meant to dedicate via dictating how the organization restores its operations and resources.
"Digital Innovation is a Novel Archetype that augments its Horizons of the Global Pursuits with its Ever-Changing Technologies."
Digital Marketing is one of the technologies that stand at the apex in online businesses to augment their scope in all its diversities towards ensuring the inevitable success. But on the forefront, the biggest challenges for marketing team lies in integrating data from diverse platforms.
In this swiftly changing digital age, delivering excellence and equity is a challenge set forth with immense competition where Digital Marketing plays a significant role in customer’s Journey- Be it B2B or B2C- that is well suited in attracting customers and takes an ideal and firm stance as a gateway to all successful business endeavours.
Having a prudent look into the role of Digital Marketing, it’s life-cycle include several platforms that were sophistically well researched and equally simplified by putting all things together into two definite acronyms : ‘p-RACE’ & ‘SMART’.
Though cloud computing seems to be a relatively new concept, but in a way its inception actually dates back to 1960s, emerging as the very concept of time sharing which has then became popularized through Remote Job Entry (RJE). Its basically a ‘Data centre Model where users submitted their jobs to operators run on Maindframes, a dominant usage in that era; A time that can be precisely called a time of exploration and experimentation while paving ways to large scale computational power making it available to more users through time sharing, optimizing the infrastructure, Platforms, and applications where the orientation was focused towards increasing efficiency for end users.
To state it simply: “cloud computing is a privilege of getting the availability of computer system resources that includes Data Storage through cloud mechanisms and computing power as well without any direct active management of the user, on-Demand, where and when one pleases”.
Each acting as a data center, large clouds enable the functions of computing distributed over multiple locations. Thus relying on the utility of sharing resources, Cloud Computing intends to achieve coherence using a typical model that can be termed as PAY-AS-YOU-GO, thereby drastically decreasing the capital expenditures, but on the Hindsight, may lead to unforeseen operational expenses for the Users.
The United Stated National Institute of Standards and Technology identifies 5 essential characteristics in its attempt to define cloud computing, which are in themselves self-explanatory. They are:
The Service Oriented.
Architectures(SOA) promotes the Idea of Cloud Computing as the Idea of “Everything As Service(EAS)” as defined by this concept of operation is carried through several models in Cloud Computing. Among them, the three Standard Service Models are Infrastructure As A Service(IaaS), Platform As a Service(PaaS), and Software As A Service(SaaS). These services provided at different levels are based on as an Abstraction and are commonly depicted as Layers in a Stack.
And Cloud Computing, pertaining to the modes of deployment are categorised into four main types, which are basically the Storage types, for, any Computing presupposes a storage mechanism to begin with, and those are:
A Data Science is a multi-faceted field of study that integrates statistics, high-end computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from potentially noisy, structured, or unstructured data.
It acts as a prodigious umbrella in all its aspects of data processing—from the collection to modeling insights. Adding to this, Data science correlates itself to a much bigger picture that surmounts organizational data that definitively meets Industry demands.
Any professional who up skills himself in Mastering this science of data ends up his pursuits to be called a Data Scientist. In most workplaces, a data scientist designs the way the data is stored, manipulated, and analysed to work more closely with data technology.
Precisely, A data scientist is a professional who creates programming code and combines it with statistical knowledge to create insights with the available data. In doing so, he creates new methodologies in processing the data for further use of analysts. Data scientists use the data that the data engineers have processed to build and train predictive models. Once the job is done Data scientists work in coherence with analysts to come up with the best of the results that comes in aid to a perfect decision making process.
Here, a data scientist uses a wide range of tools and technologies as part of the data science methodology. Based on the problem, he smartly picks the ever-trending combinations in getting quicker and more accurate results.
However, in smaller teams, a data scientist may wear several hats. Based on experience, skills, and educational background, they either perform multiple roles or the overlapping roles. In any case, their daily responsibilities compels them to invest their expertise on models that include engineering, analysis, and machine learning alongside the core data science methodologies.
Artificial Intelligence speaks about any technology that simulates Human Intelligence. Its application cuts across the challenges posed by Semantic Search, Machine Learning, and Image-Voice Recognition. AI has become the Great Deflation-Bomb that is going to hit the White-Collar Force of resources.
Thanks to the advent of emerging technologies among which AI is playing a pivotal role by offering the passionate professionals with an exceptional opportunity to Identify, Analyze, Convert, and Retain the Data providing more room to Specialize, collaborate, and explore their creativity and in a way hone themselves to evolve simultaneously with Machines of this diversified information super highway.
Today, as Organizations have multiple options to collect data, AI revolutionizes how to analyze data and process it to the comforts of Industrial Demands.
Until the birth of AI, all these Challenges seemed a mere impossibility. Today, students are bestowed with readily available technology by Adopting AI to build Intelligent Systems that can analyze with utmost precision and assimilate the response in semblance to Human Intellection.
According to a report from the organization of economic cooperation and development clearly stated that, in all, 27% of jobs in the world’s richest countries are at the risk of being replaced by AI. Industries like Banking & Finance, Media & Marketing etc are compelled to apply AI as it makes these Industries to acknowledge immense benefits it renders as its share of contribution to the striking growth of Global Economy.
Keeping this in mind, we have come up with Applied propensity models for AI where in the application of these models catch up with an optimal simulation process involved in predicting the events upfront.
These applications refer to all the other forms of AI that perfectly meet the demands of both the Individuals and the Corporates, and above all, in compliance with the inevitable contingencies of the emerging Digital Paradigms.
Data Analytics can be termed as: “A process that which is procedural and systematic computational analysis of the data at hand”.
Data such analysed is crucial to discover, interpret, and communicate towards meaningful insights by transforming them into informational segments and gets stored as such. This information paves it's way as a beneficiary insight about the certain market trends and even unto a particular customer, which has become a necessary prerogative for any business success.
With such rich insightful information at hand, Analytics can lean on the simultaneous applications of Statistics, Computational Programming and Operational Research to further quantify the performance of any typical business from time to time, to get it's complete scalability. A business can also describe, predict and improve by applying Analytics and the kinds of businesses that are coming into this groove are only increasing day by day.
Modern businesses landscapes are more often than not are thriving on consuming as well as procuring large amounts of datasets. As a Perfect resolve,
According to International Data Corporation, global spending on big data and business analytics (BDA) solutions is estimated to reach $215.7 billion in 2021 itself, and it wouldn't be a wonder to assume that it has spiked exponentially for the last two or three years.
The best type of Data Analytics that is to be taken into consideration so as to employ one, for any business, strictly rests on the respective developmental stage of that particular business. But businesses are already into the implementation of some sort of Analytics. As such what they typically afford are insights that can be termed reactive rather than proactive for their business decisions.
If we attempt to segregate Data Analytics on the basis of difficulty and added potential value that it brings forth to a business, we can well split it into four major types:
1. Predictive Data Analytics: Basically it is used to bring about the future predictions based on the historical data that have been segmented. A business may get a forecast of the number of clients or users preferring to purchase newer products that are about to get into the market. This can be done by pairing it with similar products and the current social trends.
2. Prescriptive Data Analytics: This type comes very handy to make the business statements about what actions that are to be taken and what are to be avoided within the best interests of that particular business.
3. Descriptive Data Analytics: This sort can be termed as the backbone of reporting, as it brings forth the description on what is happening by summarising the data into core statistics so as to present it for the purposes of visualization. A query such as how much web traffic a business has had for a particular time period can be diligently answered.
4.Diagnostic Data Analytics: This feature is mainly concerned in knowing or identifying the root cause of a specific problem or issue that has arised in the business process that can be an anomaly. Distinctive from the other three, it focuses on the WHY, thus bringing any adhoc situation to the forefront as such pave a way to take up concrete measures in addressing the situation at hand.
The swiftly changing Digital age calls for application development programmers with utmost commitment and whose eccentric skills in programming lay strong foundations to build an entire product that befits their versatile usage in dealing with applications, be it intranet or internet, with utmost sophistication.
In referring to the term “Full stack web development”, it is simply the development of both the frontend and the backend components. A full stack developer, thus, has a lot to offer with regards to his efficiency of skills that drives him to achieve all that is needed in full stack development.Here comes the crucial role of Python for being multipurpose, high-level, and interpreted programming language.
According to Stack-overflow, Python was ranked the third most-used language by the beginners. Adding to this passion of a committed student or a working professional, Python has become an obvious choice for Programmers to lay a gateway for themselves in spiking up their careers.
This Pursuit of Python today has become increasingly self-evident to become the prominent and on-demand programming language for the seekers in the following streams of technology:
As a full-stack developer, attending workshops, training programmes and industry events can help you interact with other engineers, IT managers and experts, allowing you to learn about recent developments in the field, upcoming coding events and other essential details during these programmes. Follow experts' repositories to learn about their current projects and any new algorithms, tools or techniques they used.
In today’s coding age of programmers, getting into web development is a scintillating idea. There are many potential and compelling career paths within the web development industry to signify that Tech jobs are all set to be plentiful and reliable and Java as a technology isn’t going anywhere in the farsighted future.
If one is Wondering what a Java full-stack is, we’re here to break it down to the ease of your comprehension. Firstly, Java is a coding language, like Python or JavaScript. All software programming is done through coding languages, and Java is one of the top languages ever-trending in today’s tech fields.
And Secondly, a Full-stack refers to an entire computer system wherein the frontend is what users see and interact with, and the backend is mainly what the developers foresee and articulate codes with utmost precision.
As a full-stack Java developer you are responsible for programming back-end code and software systems and designing the front-end areas of software or websites in the Java coding language.
In addition, as Full-stack Java developers often lead teams that work on software, websites, or other applications.
As part of our program, we foster your eccentric skills to become Web developers who can specialize either in front-end programming (user-facing programming), or back-end programming (server-side programming), or both. As a web developer all you need is to master both front-end and back-end full-stack programming Tools we offer in becoming the creators of your own info-superhighway.
Full-Stack Java Developer Skills Set:
If you’re thinking of becoming a Java full-stack developer, some specific skills will serve you particularly well. With a View that envisioned Ascending Careers in mind, Altimate has come up with following skills meticulously well designed:
1. HTML and CSS
While HTML(HyperText Markup Language) helps with creating web content, CSS(Cascading Style Sheets) is a customization tool that helps with website design.
Both these skills work Hand-in-Hand to help developers create functional and visually pleasing websites.
2. Javascript
To be a Java full-stack developer, you need to begin with Javascript coding language. Not to be confused with Java, which is a back-end coding language, Javascript is a front-end coding language.
3. Git and GitHub
GitHub is a development platform where a software is built and maintained. It uses Git to provide Internet hosting, which is software that tracks changes within the files. A combination of these programs allow for ease of web development, collaboration, and communication, especially across teams.
4. Web Architecture
It is the process of designing a website or program. It predominantly takes user inputs into consideration to build the project that is functional, navigational, and informative for users.
5. Backend Languages
To be called a full-stack developer, you need to have knowledge and skills of back-end languages.
And as these back-end languages are aplenty, the more you know the more exponential would be the demand for your profiles.
Consider learning multiple back-end coding languages such as Ruby, PHP, Java, Net, and Python that will last as an irrevocable asset.
6. Spring Frameworks
A Spring Framework is an open-source application that supplies infrastructure support for developers working on Java applications.
7. Databases and Web Storage
understanding databases and web storage has become the inevitable skill today to incline your profiles as a developer.
Cloud-based storage is a great skill to master with regard to relational databases. Developer teams often need to work in collaboration efficiently access data in gliding projects to their successful completion.