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Tag: Analytics and Artificial Intelligence

Why Should You Learn Python For Data Analytics and Artificial Intelligence?

Posted on by Imarticus Learning
Reading Time: 3 minutes

2022 has seen a huge increase in both the number of data science applicants and also future aspirants all around the world. In India alone, LinkedIn, the global job search leader, announced a 25% spike in data science professionals as compared to 2021, and that is a huge number by a number of standards.

But one of the most common questions that ponders the mind of data science aspirants most often is why they should learn Python to get an edge in this profession?

Thus if you are planning for a career in data analytics and artificial intelligence in the future, and too have this question in your mind, in this article, we will answer exactly that.

Let’s get started.

Why Is Python Important for Data Science?

At the present moment, there are more than 35 different programming languages that are actively used by developers and coders all around the world. But among all of these, Python is undeniably one of the most versatile and well equipped, especially in the field of data science.

The reason behind this is simple; if you take a look at some of the most common tasks that are executed by a data scientist on an everyday basis, starting from data extraction and ELT (Extraction, Loading, and Transformation) all of them require a solid knowledge of Python coding and operation.

Along with this, another important reason why Python is so often relied upon as the go-to programming language for data science professionals is the fact that it comes with a suite of different packages, starting from SciPy, NumPy and pandas, which make complicated and time-consuming tasks easier, more efficient and effortless.

For instance, Matplotlib, which is one of the leading Python packages, is often used by data science professionals when they want to include visualizations or any sort of graphics in their simulations.

If all of this is not enough good reason, as to why you should learn Python

Learn Python ProgrammingTo get an edge for your career in artificial intelligence, here are some of the biggest advantages of the standalone programming language in itself.

Advantages of Python

Easy to Learn

If you are a beginner at coding and you are looking for a programming language that is easy and fast to learn, then Python should be your choice.

The programming language has been around since the late 1980s and has thus undergone several developments and improvements in the last couple of years, which has made the current version extremely user and beginner friendly to learn and execute.

Since data science is such a fast-paced career, where developments are literally happening overnight, the need for a language that is easy and fast to learn is a no-brainer, thus making Python one of the most obvious choices.

Scalable

When you would have spent a considerable amount of time coding, one of the first things you will realize is the fact that Python as a programming language is immensely scalable. Compared to programming languages like Matlab and Stata, which are industry leaders in their own might, Python makes it very simple and straightforward for anyone to scale. The language comes inbuilt with a suite of features that allows you to have multiple approaches and perspectives to solve the same problem, along with having a wide range of flexibility to try out new things as and when they are developed.

Learn Python ProgrammingThe scalability aspect of Python is the second reason why companies prefer their data science professionals to know Python. Scalability is immensely important in both data science and artificial intelligence, mainly because of the fact that new discoveries are being made on the regular.

Conclusion

Thus, if you want to give your career in data science an edge, now is the time to start enrolling for an Artificial Intelligence Training that comes packed with a course in Python.

We offer analytics and artificial intelligence courses at our centers in Mumbai, Thane, Pune, Jaipur, Delhi, Gurgaon and Bangalore.

Why Senior Leaders Must Take Lead For Cybersecurity Across Businesses?

Posted on by Imarticus Learning
Reading Time: 2 minutes

With the increase in technological advancement, being up to date with all the trends in technology is important for businesses to stay in the fast-paced race of today’s market. Along with upgrading systems, businesses need to pay very careful attention to their cyberspace which means enhancing cybersecurity.

Cybersecurity is extremely important to protect vital information and assets belonging to a particular business. This would require company leaders and senior executives to strategize and protect the company from the now frequently happening data breaches as well as cyber-attacks.

Cybersecurity Training CourseIn order to drive more informed investing procedures and resourcing methods along with increased efficiency and resilience, it is looked on to senior company officials to make good strategic decisions and protect the company from any threats. When we say senior executives it includes C-suite officials as well as policy-makers.

It is not a secret anymore but a well-known fact that in the digital frame that the world is functioning in today, cybersecurity should be among the top priorities for any and all businesses. However, a number of issues of both organizational as well as structural nature pose as obstacles for the establishment of cybersecurity models that are driven by business and that focus on risk management.

Hence, only a continued support shown by officials in the upper and top management positions of any organization would allow the decrease in cyber risks and increase in progress and growth.

What Would Incorporating Cybersecurity Mean for Senior Leaders?

In every organization or company, there are people at the top that are held accountable for making important decisions which would set the course and direction for the company to follow in. Their duties also involve holding ground on priorities, maintaining and influencing the company as well as preventing risks. They are thus basically responsible for the healthy functioning of the organization, company, business or establishment.

As mentioned above cybersecurity, in this fast-changing and fast-moving business environment, is the main concern for all organizations. Thus decisions taken regarding cybersecurity are left to the decision-makers of the company. Their duties now would include:

● Managing and decreasing cyber-related risks to the business while setting up effective methods of governance
● Making cybersecurity programs a priority and focusing on resourcing
● Managing and protecting vital information that holds the business together when it comes to planning
● Encouraging cybersecurity from within

This is all very important in order to promote organizational growth through the protection of digital assets and delicate data information. Executives at the top thus need to gain a better understanding of cybersecurity and this can be easily done through cybersecurity training which would help them understand what exactly can be a risk to their organization.

This understanding would in turn help in making rational decisions in a timely manner. It would also promote resourcefulness and strategic thinking.

A cybersecurity training course would thus also help further the artificial intelligence and machine learning career of aspirants by equipping them with all the necessary skills and information that they would need.

How Machine Learning Systems Can Streamline Healthcare Disbursement Setups?

Posted on by Imarticus Learning
Reading Time: 3 minutes

The ripple effects of the COVID19 pandemic have been felt across industries at several levels. The healthcare industry wasn’t spared either, with essential healthcare workers moving to the frontlines to deal with the emergency. As a result, many organizations saw their back-end operations, such as appointment bookings and disbursement trackers, floundering.

However, there is a silver lining in this situation– it’s that technology has speedily been integrated into systems. Telehealth software has seen a surge in demand so as to prevent risks of exposure; healthcare disbursements are next on the list to be made easier.

Healthcare disbursements are traditionally tricky and convoluted processes; the pandemic has put further amounts of strain on the system and caused frustration, delays, and errors. However, machine learning in healthcare is a step forward in fixing disbursement delays.

Here’s how:

  • Moving from Checks to Digital Disbursements

A majority of disbursement systems around the world rely heavily on cheques and other outdated methods. However, this has become a point of friction at this time considering courier services have shut down and deliveries are very delayed. In such a scenario, the use of digital reimbursement options, bolstered by machine learning, is tempting.

Providers can facilitate faster payouts through DTC (direct-to-consumer) payments. By shifting the process online, providers will also be able to keep track of all patient and consumer data on one server. Machine learning can be used to pull up the relevant information, create automated disbursement setups, and ensure the consumer receives their disbursement digitally. The reduced reliance on paper payment processes will lessen the load on healthcare finance systems as well as get disbursements out to the right people in a flash.

  • Addressing Glitches in Systems

Several reports talk of misplaced cheques, incorrect deposit information, and several such kinks in telehealth and digital healthcare solutions being used today. Machine learning can be leveraged to iron out these kinks because, especially during a healthcare crisis, such errors can have a snowball effect on consumers and providers alike.

Providers who use machine learning systems to manage delays will be able to maintain strict records of past and future payouts. The system can be trained to collect the right deposit information as well as cross-verify with other records if required. The reliance on an automated system, in this case, equals to a lesser reliance on outdated methods of payout tracking.

  • Simplify User Experience

Claiming payouts and processing them can become a nightmarish experience for both patients and healthcare providers alike. Machine learning systems effectively reduce quite a number of manual steps which, in turn, saves time, money, and efforts. Machine learning can be leveraged to extract critical information from healthcare contracts, estimate how much is owed, and prepare the right documentation in time for a payout.

For patients, too, the process of claiming payouts become simpler. They will no longer have to fill out a myriad of forms and move from office to counter over days. Instead, by automating certain processes from the providers’ ends, patients can be called in only to verify details if necessary and to provide any other physical documentation the healthcare provider may need.

Conclusion

The healthcare industry will most likely see a surge in the adoption of machine learning and artificial intelligence. This will be across the board– from handling disbursements to automating admissions and discharges. Therefore, students who are interested in pursuing an artificial intelligence career would do well to explore this niche and develop the right skillset for it.

You can do this by enrolling in a machine learning course that focuses on the healthcare system, or take on related projects that could leverage your portfolio when it comes to it. The current strains on healthcare providers worldwide have exposed significant cracks in the system that machine learning could most likely fix.

How an Artificial Intelligence and Data Science Work For an Online Conference?

Posted on by Imarticus Learning
Reading Time: 3 minutes

Artificial Intelligence and data science are the driving force behind most of the online conference tools available now. The more advanced the AI used, the better its experience is for the users. The advancement enables the user to have a more personalized and better quality video feed and experience.

Artificial intelligence and video conferencing

Already there is the option to replace and blur the background as per convenience. The use of Artificial Intelligence and data science in this arena is much more than that. Background manipulation is only the tip of the huge iceberg.

There are other features such as translation for those who are not familiar with the language spoken and it works either way when implemented properly. There is another possibility of transcribing the same to make it easier to understand.

The noise reduction in the background comes as another advantage where there could be distractions, especially when it is working from home scenarios.

All of these features make online conferencing more convenient and comfortable which is crucial at the moment. As work from home is becoming more normal than ever and online conferencing is the big ‘thing’ now, it needs all inputs from the Artificial Intelligence industry to make it simpler.

How data science comes into the picture?

Although Artificial Intelligence and data science sound similar, they are two sides of the same coin. While AI is the major force behind online conferencing, data science is no less important.

Data science comes in handy when the employee’s data needs to be analyzed. For eg, in order to find the ideal time for a conference, the log in log out time of the employees would be useful. By analyzing this data, a more appropriate time could be deduced where there is a possibility of maximum participation.

The chatbots powered by Artificial Intelligence could also need the backup of data science to implement it more effectively. It helps to communicate with multiple users at the same time and reduces the call time for both sides.

Amazon has implemented these chatbots and has found success with the same. The users have also expressed satisfaction when it comes to minor issues which do not usually need waiting in line to talk to customer care. This is a perfect example of AI and data science in use.

Learn Artificial Intelligence and data science

AI and data science are raising the bar with their advancements and specializations. Its popularity and demand are at an all-time high with numerous job opportunities in both fields.

People are queuing up to enroll in an Artificial Intelligence course at any cost. Specializing in this area is fruitful for the professionals and newcomers equally.

Artificial Intelligence and Data ScienceStarting a data science career may have been difficult in the past but it is a golden opportunity for all right now. Unlike Artificial Intelligence, data science is more beneficial for working professionals to maintain and advance in their careers. It helps them climb the corporate ladder a lot easier than ever. Moreover, there are multiple branches in data science that one can easily choose the most appropriate for their career.

Wrapping up

Though data science and Artificial Intelligence were present in various aspects of life, the pandemic has made it more familiar for the common man. Online conferences are only one such aspect but the one that has made the maximum impact on everyone. There was a time when such concepts were frowned upon but the increasing use of smartphones and the user-friendly approach of such technology has made it possible to make online conferencing a normal and ordinary household term.

How To Write And Display Easily The Fibonacci Series In Java?

Posted on by Imarticus Learning
Reading Time: 3 minutes

What is Java?

Java is a programming language that was developed by James Gosling in Sun Microsystems in the year 1995. The aim of designing Java was to support a digital Television screening; ultimately it was found out that Java was developed advanced to just be used for a TV network. The first version of Java 1.0 was released in the year 1996.

The latest version of Java is 14 that launched in the year 2020. Presently, innumerous applications are existing on the internet which won’t work without the support of Java. Usage of Java has also been considered beneficial in Artificial Intelligence.

Artificial IntelligenceBeginners in this field may enrol for a Java Programming Training in Analytics.

 Principles of Java 

When Java was developed, it came out with a certain set of goals or the principles. These principles have to be followed while programming in Java.

The Principles of Java are:

  • It must be simple, object-oriented and familiar.
  • It must be robust and secure.
  • It must be architecture-neutral and portable.
  • It must be interpreted, threaded and dynamic.
  • It must execute with high performance.

Some Java-based Applications

Java has encapsulated most of the functions in web-based applications. Some of the fields covered by Java are:

  • Java Desktop GUI Applications
  • Java Mobile Applications
  • Java Web-based Applications
  • Java Web Servers and Application Servers
  • Java Enterprise Applications
  • Java Scientific Applications
  • Java Gaming Applications
  • Java Big Data Technologies
  • Java Business Applications
  • Java Distributed Applications
  • Java Cloud-based Applications

What is the Fibonacci Series?

Fibonacci is the concept which is found to have appeared in Indian History in a connection with Sanskrit Prosody. This concept was given by Parmanand Singh in 1985.

Fibonacci series is a series of some integers, where the Nth term is equal to the sum of N-1th and N-2th (last two terms). The first two numbers in the Fibonacci series are supposed to be 0 and 1 and each of the subsequent terms of the series is the sum of the previous two terms.

An example of Fibonacci series can be:

0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89…..

Artificial Intelligence

Algorithm to Generate Fibonacci Series

While generating a Fibonacci Series, some of the key points need to be focused on. Following is the algorithm to program a Fibonacci Series:

  • First two terms of Fibonacci Series need to be 0 and 1.
  • The last two terms of Fibonacci series have to be stored in “last” and “second last” integer values.
  • The current term of Fibonacci series is always equal to the sum of “last” and “second last” term.
  • The last and the second last integers need to be updated as Second Last= Last and Last= Current.

Ways to Write Fibonacci Series in Java

When writing a series in Java, recursion plays a vital role. The coding has to be done with or without the usage of recursion. Some of the programmers may just consider the use of recursion while coding Fibonacci series in Java but writing Fibonacci in Java without recursion is also a great way of coding which gives out amazing outcomes.

The two main ways of writing and displaying the Fibonacci series in Java are listed below:

  • Fibonacci Series without using recursion
  • Fibonacci using recursion

Ways to Display Fibonacci Series in Java

When it comes to the Display of Fibonacci series, it can be generally done by two ways in Java. Both the ways are listed down below:

  • Fibonacci using For LoopArtificial IntelligenceFibonacci using While LoopArtificial IntelligenceApplication of Fibonacci Series

Fibonacci is used in various application systems. It is used for interconnecting the parallel and distributed systems. It can also be used in the following ways:

  • Computer algorithms are known as Fibonacci Search Technique and Fibonacci Heap Data Structure.
  • A certain specific type of graphs and tables particularly known as Fibonacci Cubes.

Top Python Projects You Should Consider Learning?

Posted on by Imarticus Learning
Reading Time: 3 minutes

Understanding Python

Python is a high-level programming language that is used by programmers for general purpose. There’s a whole lot you can do after learning python, it can be used to develop web applications, websites, etc. You can also develop desktop GUI applications using python. Python is more advanced than other traditional programming languages and provides more flexibility by allowing you to focus on core functionalities and taking care of other common programming tasks.

One of the major benefits of python as a programming language is that the syntax rules of Python is very transparent and allows you to express models without writing any additional codes. Python also focuses on readability of codes. Building custom applications without writing additional code is also an advantage that Python offers. Being an interpreted programming language Python allows you to run the same code on multiple platforms without recompilation.

Why learn Python?

One of the major advantages of python programming language is that it is relatively simple to learn and has a smooth learning curve. It is a beginner-friendly programming language. The simple syntax used by Python makes it easy to learn programming language as compared to programming languages like Java or C++.

Python has a standard library and the external libraries are also available for users. This can help you to develop concrete applications quickly. You can easily learn python by enrolling in python programming course online. Let’s take a look at some of the top python projects that you can easily learn.

Guess the Number

This project will use the random module in Python. Some of the concepts that will be used while doing these projects are random functions, while loops, if/else statements, variables, integers, etc. Here, the program will begin by generating a random number that is unknown to the user. The user will have to provide and input by guessing this number.

If the user’s input doesn’t match the actual random number generated using the program, the output should be provided to indicate how close or far was the guess from the actual number. A correct guess by the user will correspond to a positive indication by the program.

You will need to apply functions to check three parts of this program; the first is the actual input by the user, secondly the difference between the input and the number generated and lastly to make comparisons between the numbers.

Password Generator

This is a very practical project given the use of password generators for everyday applications. You simply need to write a programme that helps to generate a random password for the user. Inputs required from the user are the length of the password to be generated, the frequency of letter and numbers in the password, etc. A mix of upper and lower case letters and symbols is recommended. The minimum length of the password should be 6 characters long.

Hangman

You are already familiar with “Guess the Number” game, this is more of a “Guess the Word” game. The user has to input letters as guess inputs. A limit is required to be set on the total number of guesses a user can make. It is advisable to give the user 6 attempts at most to guess.  You will need to apply functions to check if the user has made a letter input or not.

You will also need to check if the input shared is there in the hidden word or not. You will have to find a solution to grab a word that will be used for guessing. The main concepts applicable in the Hangman project are variables, Boolean, char, string, length, integer, etc. It is comparatively more complex than the projects mentioned above.

Job Opportunities in The Field of Artificial Intelligence in This Pandemic Time!

Posted on by Imarticus Learning
Reading Time: 3 minutes

To become an Artificial Intelligence (AI) professional, you need to have practical problem-solving skills, logic, communication, and analytical skills. AI is made to create computer programs that can achieve goals and solve a problem better than humans. With lesser mistakes and emotions to hinder the work, AI gives better and jan efficient output.

The scope in AI is vast. You can get into robotics, gameplay, language detection, machine learning, computer vision, speech recognition, and many more.

Some of the factors that characterize a great career in AI are as follows:

  • Robotics
  • Use of sophisticated computer software
  • Automation

Math, technology, engineering, and logic are some of the specific fields that individuals have to specialize in if they are considering a job in this field.

Along with this, learning science including physics and computer studies is beneficial.  Considering the computational approach to AI, knowing the technical, as well as physiological knowledge of the system, is immensely helpful. Knowledge of primary machine language is a must. There are many other courses that you can do to get into the world of AI like, Machine learning.

Data Science Online CourseMany institutes like IIT provide machine learning courses, there are other institutes that provide these courses online and then there are certification courses that you can take up in private institutions.

Some of the career opportunities in AI

  • Robotic Scientist

Robots are gradually taking over the industrial worlds. There is lesser workforce and more robots. To help create such robots that can solve problems as a human would, we need engineers or programmers. For a career in Artificial Intelligence field, a master’s in robotics engineering and having a license from the state can be of help.

  • Software Engineer

In every phone that is there in the market, there is an option for face recognition or finger print recognition. Many companies, including big businesses, security companies, casinos, etc. have face recognition and fingerprint recognition to understand the people who use their services. Hence being a software engineer is one of the opportunities here.

  • Game Programmer

To keep the players challenged and highly anticipated, every gaming company requires candidates that are well known with the basics of AI and can design games that can keep the players engaged and interested.

  • Search Engine Manager

Many big companies, like Google, pay a massive amount to candidates with an AI degree to manage their massive search engines. Many may search for various things on Google, but Google search is able to predict the search even when there are spelling mistakes or grammatical errors. This is done with the help of knowledge and the study of artificial intelligence.

  • Government Sector

There are jobs not just in the Private sector, but there is an intense need for candidates with a degree in AI in the government sector too. The pay is high, and along with that, the amenities provided are even better.

Conclusion

The scope of artificial intelligence is vast. Having a master’s degree or a doctorate is the best if you are looking for a long term job in the field of AI.

The demand for people with knowledge of AI is strong. Companies like Google, Apple, etc. are always on the lookout for candidates who can take the world of AI to another level. The choices are plenty, and the income from working in such a field is high.

‘Eve’, a robot created by the scientist at the University of Manchester, Cambridge, discovered that a common ingredient found in toothpaste is capable of curing malaria. This event, itself, can show how much this field has grown, and the job possibilities are endless.

How AI in The Energy Sector Can Help to Solve The Climate Crisis?

Posted on by Imarticus Learning
Reading Time: 3 minutes

How AI in the Energy Sector Can Help Solve the Climate Crisis

Have you not complained about the crisis that is looming large in our environment? The news reports of untimely floods, missing rain patterns, fires in forests, carbon emissions and smog affect each and every one of us. The Davos meeting of the World Economic Forum threw up some important measures that we need to take in enabling AI, ML and technology as a whole in symbiotically tackle the climate crisis of all times.

The main cause of the changes in climate is being attributed to emissions of carbon and greenhouse gases. And each and every person in tandem with AI, technology and the big industrial players have a bounden duty to support such measures and immediately move to reduce these emissions if we wish to halt such catastrophic climate changes. Noteworthy is the funding of nearly billion dollars in such ventures by Bill Gates and Facebook’s Mark Zuckerberg.

Here is the list of the top suggestions. In all these measures one looks to technology and artificial intelligence to aid and achieve what we singularly cannot do. This is because the noteworthy improvements brought about by AI are

AI helps compile and process data:

We just are not doing enough to save our planet. The agreement between countries in Paris to be implementable means elimination of all energy sources of fossil-fuel. AI enabled with intelligent ML algorithms can go a long way in processing unthinkable volumes of data and providing us with the insight and forecasts to reverse the climatic changes, use of fossil fuels, reduction of carbon emissions, waste etc, and setting up environment-friendly green systems of operations.

AI can help reduce consumption of energy by ‘server farms’

The widespread use of digitalization has led to server farms meant to store data. According to the Project Manager, Ms. Sims Witherspoon at Deepmind the AI British subsidiary of Alphabet when speaking to DW said that they have developed a bot named Go-playing with algorithms that are “general purpose” in a bid to reduce the cooling energy of data centers of Google by a whopping 40%. This does amount to a path-breaking achievement when you consider that a total of 3 percent of the energy globally used is just used by the ‘server farms’ to maintain data!

Encouraging the big players to be guardians of the climate.
The industrial giants are using technology, AI and ML to reduce their footprints of carbon emissions. AI tools from Microsoft and Google are aiding maximized recovery of natural resources like oil, coal, etc. Though with no particular plans or place in the overall plan-of-action such measures do go a long way in preserving the environment through reduced emissions and set the trend into motion.

Using smartphone assistants to nudge for low-carbon climate-friendly changes.
The rampant use of smartphones and devices of AI makes this option possible and along with zero-click AI enabled purchases the virtual assistant bolstered through ML algorithms and tweaked infrastructure can be used to influence choices of low-carbon climatic and emission-reduction changes.

Social media can transform education and societal choices.
The biggest influencer of social change is the social media platforms like Instagram, Facebook, Twitter, etc these can be harnessed to publicize, educate and act on choices that help reduce such carbon emissions and use of resources.

The reuse mantra and future design.
Almost all designing is achieved through AI which can help us design right, have default zero-carbon designs, commit to the recycling of aluminium and steel, reward lower carbon footprints, grow and consume optimum foods and groceries and create green and clean smart cities.

Summing up the suggestions to be placed at the UN Global Summit for Good AI at Geneva, it is high time we realize that the future lies in data and its proper use through AI and empowering ML. We need new standards for use of the media and advertising digitally. All countries need to globally work to reduce the use of fossil fuels in automobiles and transportation. We must cut our emissions by half in less than a decade and this is possible through proper use of data, AI, ML, and digitization.

If you care enough to be a part of this pressing solution to environmental change, learn at Imarticus Learning, how AI has the potential to harness data and control the damage to our environment. Act today.