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Category: Management

The Impacts of Robots in Regular Life!

Posted on by Imarticus Learning

Robots are used in many areas of our life, including 10 possible uses of robots in our daily life: Automated transport (autonomous robot) Automated transport (autonomous robot) The first major spread of visibility The use of mobile robots is seen through autonomous cars.

The advances in the development of automated autonomous vehicles over the past 10 or 15 years have been astonishing. New cars without robotics are like computers on wheels. But with robotics, they’re more efficient and dangerous. Autonomous robots are not robots that can drive cars. What it really means is that cars are built like robots and artificial intelligence is fed into those cars.

In a modern world like many countries in Europe and America, the automated autonomous vehicle is available like buses, trams and trains are automated, but vehicles like cars that circulate on the streets are not very general, but recently Audi, Mercedes, Google, they are presenting autonomous cars. The day is not far off when human drivers are not needed to drive vehicles.

As a result, accidents may not happen as many as there are today. Security, Defense and SurveillanceSecurity, Defense and Surveillance The work of security, defense, and surveillance robot is normal: it inspects the desired area. Immediately notify the owner if there has been any kind of malfunction. This type of robot is used in the military. This type of robot can also be used in everyday human life.

In the army, this type of robot does different types of work. . They are used to arm and defuse bombs. You will be sent to the desired area to monitor enemy activity, which is definitely a dangerous job for soldiers.

Robotics trainingFor use in everyday human life, this type of robot monitors your house. This robotics training helps people to monitor the sky, the ground, and the water from a remote location.

You can control this kind of robot from another location to send them to the desired location to monitor the activities of that location. Your home and property will not be damaged if you are not around to monitor them.

Cooking with Robots Cooking with Robots After spending a full day at the office, it becomes annoying to motivate yourself at home to cook a delicious meal for yourself.

The abbreviation is sometimes not healthy and tasty enough. But what if you had a robotic kitchen assistant to help you cook the food to your liking? There are many programmable robots that can prepare the food of your choice. All you have to do is set the number of food ingredients. The robot does the rest. A lot of robots are now being introduced that you can copy. You only need to cook in front of the robot once.

The movement of your body is registered by the camera, from then on the robot will copy your actions to prepare this meal for you, this type of robot kitchen helpers are being introduced in many hotels and homes, some companies are making these types of robots, including, Moley Robotics, Shadow Robot companies are quite famous.MedicalMedicineThe influence of robotics is undeniable in the medical field. Recently, engineers have successfully discovered surgical robots.

This success has resulted in a large financial investment in robots in medicine. Recently, Google and Johnson & Johnson worked together to develop a next-generation medical robotic system. While robots were only used as assistants in the clinical system in the recent past, they are now being introduced as an integral part of the clinical system.

Although not yet possible, it is not far from replacing the surgeon with robots in operations. The robotic system has established itself in clinics around the world. Therefore, engineers work hard to successfully invent micro and nanorobots.

Doing things that require precise and accurate performance in a way that a human cannot. For the drug delivery system, these robots can concentrate the therapeutic payload locally around the pathological sites so that they can reduce the dose of the drug delivery and the side effects they cause.

Education roboticsEducation Robotics is now known as an all-purpose technology. This means that it has the potential to change societies through its effects on economic and social structures.

So it is now natural to start discussing robotics in education. Many students suffer from different types of illnesses on a daily basis.

Therefore, they cannot physically attend classes. Because of this, the lessons are lost. Engineers have developed robots that can help students attend their classes remotely. The robot acts as a person in the classroom that is controlled by the person himself. His cameras are his eyes and the body is used for interaction.

Complete Overview on – Computer Science And Engineering(CSE) Projects!

Posted on by Imarticus Learning

Computer science is a branch of engineering that deals with the logical investigation of computers and their use like calculation, information preparing, frameworks control, advanced algorithmic properties, and man-made reasoning.

The skills of computer science incorporate programming, outline, examination, and hypothesis. Computer science engineering includes outlining and advancement of different application-based programming. Computer science venture points can be executed by various instruments, for example, C, C++, Java, Python, .NET, Oracle, and so on.

Mini Projects

A mini project is a bit of code that can be produced by a group or a person. Small-scale projects are utilized as a part of the Student field. A mini project is a source code with enhanced capacities it can even be taken as the last year venture.

Computer vision coursesLast year Mini undertakings, which they may need to make as a part of their instructive educational programs. These projects can be created in JAVA, VB .NET, ASP .NET, C, C++, PHP, C#, JSP, J2EE, ASP, Cloud Computing Networking, Big Data, Data Mining and that’s just the beginning.

 

You can get online courses at Imarticus with guaranteed internships over different languages C, C++, Java, Python, etc..

Topics

The topics for mini Projects in Computer Science and Engineering are as follows:

 

IEEE Java Mini Projects

Java is the world’s most popular language and it controls billions of gadgets and frameworks around the world. An assortment of recommended understudy term ventures is including java. Here are some IEEE java venture lists utilizing the most recent methods.

Most recent Java points, Latest java Concepts, Java venture focuses with astounding Training and improvement, Latest J2EE Projects with ongoing Technology. Here is a rundown of undertaking thoughts for Software ideas. Some of the project ideas involving the concepts of java are as follows:

  • Classroom scheduling service for smart class
  • Privacy-preserving location proximity for mobile apps
  • Mobile attendance using near-field communication.
  • LPG booking online system by smartphone

Projects on Cloud Computing

Cloud computing is the conveyance of on-request figuring assets over the internet, huge development in the recent software technologies which is associated with the remote servers through a systems administration connection between the customer and the server.

The information can be uploaded and it can be anchored by giving diverse sorts of security. Systems for securing information respectability, message validation codes (MACs), and advanced marks, require clients confirmation to download the majority of the records from the cloud server, We have the best in the class foundation, lab set up, Training offices, And experienced innovative workgroup for both instructive and corporate areas. The project topics for cloud computing are as follows:

  • An efficient privacy-preserving ranked keyword search method.
  • Vehicular Cloud data collection for Intelligent transportation system.
  • A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data.
  • Live data analysis with Cloud processing in wireless Iot networks.

Projects on Big data/Hadoop

Big Data is having a huge development in the application industry and in addition to the development of Real-time applications and advances, Big Data can be utilized with programmed and self-loader from numerous points of view, for example, for gigantic information with the Encryption and decoding Techniques and executing the charges.

Big Data examination has been an exceptionally hot dynamic amid recent years and holds the potential up ’til now to a great extent undiscovered to enable chiefs to track improvement advance. Most recent Big Data themes, Latest Big Data Concepts regions take after:

  • An online social network based Question Answer System using Big data
  • Efficient processing of skyline queries using Big data
  • User-Centric similarity search
  • Secure Big data storage and sharing scheme for cloud tenants.

Don’t miss reading Software Every Engineer Should Know About.

Projects in Networking

Networking works with all the directing conventions, for example, exchanging the information from a place to another which takes the assistance of numerous conditions like filaments and so on, Adhoc systems are utilized for exchanging information from a portable system to a web application. Some of the networking based projects are:

  • Cost minimization algorithms for data center management
  • Detecting malicious Facebook applications
  • Software-defined networking system for secure vehicular clouds

Data Mining Projects

Data mining is the mining of information from data, Involving techniques at the crossing point of machine learning, insights, and database frameworks. It’s the intense new innovation with awesome potential to enable organizations to center around the most critical data in their information stockroom.

We have the best-in-class foundation, lab set up, Training offices, and experienced innovative workgroups for both instructive and corporate parts. The projects topics on data mining are as follows:

●Link Analysis links between individuals rather than characterizing the whole
●Predictive Modelling (supervised learning) use observations to learn to predict
●Database Segmentation (unsupervised learning) partition data into similar groups

Learn Cloud Computing, Big Data, Data Mining, and many other courses at Imarticus with guaranteed internships.

Some more computer science-based project topics are:

  1. Data  Warehousing and Data Mining Dictionary
  2. Fuzzy Keyword Search in Cloud Computing over Encrypted Data
  3. Web-Based Online Blood Donation System
  4. Web-Based Graphical Password Authentication System
  5. Identification and Matching of Robust-Face Name Graph for Movie Character
  6. Controlling of Topology in Ad hoc Networks by Using Cooperative Communications
  7. An SSL Back End Forwarding Scheme of Clusters Based On Web Servers
  8. Motion Extraction Techniques Based Identifying the Level of Perception Power from Video
  9. Approximate and Efficient Processing of Query in Peer-to-Peer Networks
  10. Web-Based Bus Ticket Reservation System

15 Reliable Sources to Master Data Science

Posted on by Imarticus Learning

15 Reliable Sources to Master Data Science

Data Science is growing at a rapid pace and businesses have been dynamically benefitting from this. A lot of Data Science Courses are available at the Imarticus Learning Data Science Training Center. No doubt, the insights and knowledge of data science have helped business emerge a winner with better knowledge and insights available at their fingertips. Have a look at these 15 important blog resources with the highest number of followers if you are willing to understand and learn data science. These blogs have rich data science resources and won’t let you miss you anything in the world of data science.

  1. Reddit – It’s an American social news aggregation, web content rating and discussion website for everyone who loves to share content and satisfy their curiosity. The registered members at Reddit can submit content such as text posts or direct links and get opinions on the same. It’s a hugely popular website where everyone can participate because it’s simple and easy.

Frequency — About 84 posts per week

Facebook Fans: 1,108,745

Twitter Followers: 511K

2. Google News – Comprehensive and most dynamic up-to-date news coverage, aggregated from all over the world by google news. It’s a popular medium throughout the world since Google has become a most reliable name everywhere. It’s a reliable source of Data Science information where everything related to it will be at your fingertips.

Frequency — About 21 posts per week

Facebook Fans: n/a

Twitter Followers: 214K

3. Data Science Central – Now this is a platform where every kind of information is available in one place. It wouldn’t be wrong if we say that it’s the industry’s online resource for big data practitioners. And it’s damn popular among the practitioners. From analytics to data integration to visualisation, data science centre provides a community experience.

Frequency — About 24 posts per week

Facebook Fans: 1,013

Twitter Followers: 100K

4. KDnuggets I Data Science, Business Analytics, Big Data and Data Mining – Now, if you are looking for the most interesting and updated blogs on day to day evolution of the Big Data, then this is the place to be. Here, one can find the most interesting stuff on analytics, big data, data science, data mining and machine learning, not necessarily in that order.

Frequency — About 34 posts per week

Facebook Fans: 21,860

Twitter Followers: 96K

  • Kaggle I Data Science News – No Free Hunch – A competitive platform where companies and researchers post data while statisticians and data miners compete with each other to produce the best models for predicting and describing the data. It’s a popular platform where professionals compete with each other to come up with the best ideas that they have.

Frequency — About one post per month

Facebook Fans: 35,137

Twitter Followers: 89.1K

    • Revolution Analytics – An exclusive blog dedicated to the news and information of interest to the members of the community, who are deeply interested in analytics and relation disciplines. The blog is updated every US workday, with contributions from various authors.

Frequency — About six posts per week

Facebook Fans: n/a

Twitter Followers: 25.9K

  •  Data Science for Social Good – This social good data science does the work of training data scientists to handle the problems that matter. It effectively trains the data scientists to work on data mining, machine learning and big data.

Frequency — About one post per month

Facebook Fans: n/a

Twitter Followers: 20.5K

  • Data Camp – You can learn to be a data scientist from the comfort of your home through your browser with Data Camp’s data science blog. It’s a comfortable way where total information is available in one place, and you can pick up the topics that you want to master.

Frequency — About seven post per month

Facebook Fans: 340,109

Twitter Followers: 16.2K

9. Codementor – This blog tells you about the latest trends in data science. Here you can read tutorials, posts and insights from top data science experts and developers. This will eventually help you gain knowledge from experienced experts.

Frequency -About one post per month

Facebook Fans: 12,587

Twitter Followers: 22,1K

10. Dataversity – Data Science News, Articles & Education – Here, learn about the latest business intelligence news and get a thorough business intelligence education. This blog is focused more on the business side and understanding it is necessary from the business point of view.

Frequency – About one post per week

Facebook Fans: 6,312

Twitter Followers: 17.4K

11. Data science @ Berkeley I Online Learning Blog – If you are interested in an online course called professional Master of Information and Data Science (MIDS) from UC Berkeley School of Information.

Frequency — About one post per month

Facebook Fans: 14,804

Twitter Followers: 10.2K

12. Data Plus Science – This blog helps people find real answers in data science, quickly and effectively. So it’s a swift means of knowledge generation.

Frequency — About two posts per month

Facebook Fans: 2,932

Twitter Followers: 25.1K

13. NYC Data Science Academy Blog – A one-stop destination for in-depth development tutorials and new technology announcements created by students, faculty and community contributors in the NYC DCA network.

Frequency — About five posts per week

Facebook Fans: 2,136

Twitter Followers: 17,1K

14. Data Science 101 – A blog on how to become a data scientist.

Frequency — About five posts per week

Facebook Fans: 15,925

Twitter Followers: 2,365

15. Data Science Dojo – It’s a revolutionary shift in data science learning. The course offers short-duration, in-person, hands-on training that will get the aspiring data scientists started with practical data science in just a week!

Frequency — About one post per month

Facebook Fans: 12,009

Twitter Followers: 4,664

The Data Science Resources will help you keep updated and gain new knowledge and insights in the ever-evolving field of data science. The data science course at the Data Science Learning Center – Imarticus Learning will ensure updated knowledge to candidates.

Top Data Science Datasets Project Ideas for Beginners!

Posted on by Imarticus Learning

What is Data Science?

Every company receives too much information about something at a moment which becomes tough to be processed at the same pace. Here is when Data Science comes into the picture.

Data Science is a field of study which deals with gathering massive information about a particular field from various sources and then converting that Big Data into a meaningful output. This data is combined with Machine learning and Artificial Intelligence which all together act as a base for scientific research to take place.

Data Scientists are hired to convert that Big Data into useful conclusions which further assists in lucid Decision Making.

With the advent of technology, everyone is pretty much connected which is the main reason how all the information related to a topic can be made available through the internet. A data science career can open the gate to multiple possibilities.

Data Science Course with Placement in IndiaData Science Datasets Project Ideas for Beginners.

According to a survey, it has been found that by the end of 2020, the demand for Data Scientists will increase by 28%. This is because of the current scenario where everything has shifted to online mode.

Data Scientists can lay their hands on various new topics and elements on the internet which can be the basis for their researches.

Some of the Data Science Projects that can help beginners to build a stronger resume are:

  1. Automated Chatbox Project

Considering the current situation, everything has become internet-based. Renowned companies are also switching to the Chat mode in their Customer Care Departments rather than taking up the calls. Chatting has become way more convenient than any other mode of communication. As far as formal or official communication is concerned, chatting sounds the best.

For a beginner, research on an Automated Chat Box can be really promising and fresh. There can be modifications in the classic chatting pattern in terms of official and formal chatting. For instance: When a company receives so many messages from their customers about certain queries, the automatic chatbox can answer some of the repetitive questions by itself.

This lessens the burden on the employees leading to a better focus on the queries rather than a formal salutation.

  1. Automated Caption Inserter Project

Talking about the current trend, where everyone wants to upload their pictures and photographs on Social Media Platforms, they want their captions to be suitable and trendy.

For a beginner who is aspirant of researching Data Science, this can be something new and likable.

When a picture alongside a river is posted on any Social Media Platform, this feature can give suggestions to the users regarding specific captions revolving around rivers or water bodies. This can save a lot of time and effort for the users leading to a great monopoly on the internet.

  1. Song Recommendation Project

Various music and song applications have been designed throughout the world. There can be research in the field of automated song recommendations to the users based on their current playlist or already downloaded songs on the application. This can be a  practical and helpful solution for users who are searching for songs that they may like.

Overview

Data Science, on the whole, is a massive field that can be explored with no limits and boundaries. One can keep carrying out amazing researches in several areas.

Investment Banking Courses with Placement in IndiaAll beginners must take up the Data Science Course if they wish to pursue a bright Data Science Career.

This is a field of study that is always going to be engaging and creative no matter how much work and research gets done.

How To Advance Your Business With Analytics & Build The Right Team?

Posted on by Imarticus Learning

In 2020, data is a goldmine of information, and if you can collect and analyze the right data sets, a lot can be achieved in a short period of time.

As companies around the world, start recognizing and collecting more data points from their customers, it is crucial than ever before to have a data analytics team, which can not only process and analyze the collected data but also emphasize sharing key insights which will assist you in advancing your business.

LinkedIn, the number one job search portal reported that 2020 saw a 25% increase in professionals who are seeking a Big Data Career in data science and analytics.

Bi Data CareerWhile this clearly indicates that the importance of data scientists is on a steady rise, it also indicates that companies need to better analyze the capabilities of each individual domain to choose the right man for the job.

How to Choose and Build the Right Data Analytics Team for Your Company?

One of the first and most crucial aspects to understand and embrace is the fact that in 2020, data scientists come with a variety of different skill sets, and thus it is essential to recognize each of the skills and categorize them into the functions best suited for.

While building an analytics team for your organization, you can follow either of two different approaches.

  1. The Direct Method of Segmentation
  2. The Indirect Method of Appreciation

The Direct Method of Segmentation

The concept of the direct method of segmentation is based on the ideology that each data scientist depending on their skill set can be grouped into either of three different designations and then hires can be made based on deciding which skill is required first.

  1. Data Engineers: Data Engineers are the crux of any data analytics team you want to design. The main skill sets you should look for in a data engineer include, ETL (Extraction, Transformation, and Load), Data Warehousing, data processing, and other similar roles.The fundamental job of a data engineer can be summarized as preparing the data for further analysis by data scientists and analysts, who form the rest of the team. They generally have a degree in Big Data Analytics Training.

    Big Data Career

  2. Data Analysts: Using the data prepared by data engineers, analysts extract critical information and decisions which are helpful in solving problems and contribute to advancing business decisions within the organization.
  3. Data Scientists: Data scientists form the last hierarchy of the team and are mainly responsible for crafting and perfecting algorithms using either Machine Learning or Artificial Intelligence to make compelling decisions from unstructured data sets. While a data scientist can easily be tasked with the responsibilities of both analysts and engineers, in big teams these designations are separated for better utilization of time and resources.

The Indirect Method of Appreciation

The indirect method of appreciation is based on the concept of recognizing people who have a broad range of skills, but also in-depth knowledge in a few key areas. This method of hiring can be understood using the “T-Shaped” skill concept, where the horizontal bar of the T represents the broader knowledge set of the hires, and the vertical bar represents the specialized knowledge in key areas.

The overall aim of this methodology is always to find the right set of people, who have the expertise and the knowledge to get the work done in a timely manner.

Conclusion

Building the right data analytics team for your business can not only contribute to its immediate success but also long-term growth. Thus always make it a point to invest the right amount of resources and figuring out which methodology of hiring works best for your business.

What does Intrusion in IT mean? And How can it be Detected?

Posted on by Imarticus Learning

Network security, for any organisation, is of prime importance. This does not mean protecting the network with the use of firewalls, but it goes deeper than that to pick up potential threat factors without replacing the traditional or primary security efforts like the encryptions or authentication methods.

To understand this better, it is important to first discuss what intrusion in IT means. Intrusion in IT, to simply put it, it is when a hacker wants to make way in your network with malicious intent. This can be detected by a Network Intrusion Detection System. Why are we using the term network here?

Because an intrusion detection system keeps a check on packets of a network wire, with the main objective of keeping away the hacker from entering or breaking into your system, it does so by analysing the movement on your network, to evaluate any anomaly or signs of threat.

Let us understand the main Objective and Functions of an Intrusion Detection System

  1. To Detect Attacks on the network – by providing real-time monitoring with an intrusion detection system can detect any potential threats or attacks as and when they occur.
  1. Provide Information on the attack – the intrusion detection system is equipped to provide information on an attack if it detects one.
  1. Provide Resolution – in an event, an attack was detected, it not only provides information of the attack but goes forward and applies corrective actions to manage the threat or an attack.
  1. Historical Data – the system stores the information on events locally and also when a case of attack is registered.

A network detection system is most strategically placed on points in a network so that it can monitor the traffic travelling to or from different devices on that network. There are mainly two types of network Intrusion detection systems, one should understand the applicability of this to decide on which one to apply.

Signature-based intrusion detection system, which is programmed towards identifying a specific type of vulnerability. Hence this system will not report every anomaly but only specific ones, thus reducing the number of False Positives.

Anomaly-based intrusion detection system searches every attack that is not meeting with the norms, hence in this system, the rate of false positives is very high.

Many companies set a large network identification system as a backbone network, which monitors blanket traffic on the network, others set up small systems to monitor traffic for a particular server, switch, gateway or router.
Besides monitoring traffic, an intrusion detection system can also scan system files looking for unauthorized activity and maintain data and file integrity.

The intrusion detection system can also work for a proactive role instead of a reactive role. It is proactive as it’s possible uses involve scanning firewalls for potential exploitation and scanning live traffic to see what is actually emerging.
A point to note is that the intrusion detection system is not a replacement for firewalls or any primary security systems, which are put in place to mitigate risks. This system is a backup network integrity device. And either one of the systems cannot replace another.

Imarticus offers an extensive certification course in Business Analytics for freshers and working professionals to understand the depth of IT Intrusion :

Data Science Prodegree: This program is co-created with Genpact as Knowledge Partner. This program helps you with the deep understanding of Data Analysis and Statistics, along with business perspectives and cutting-edge practices using SAS, R, Python, Hive, Spark and Tableau.

Post Graduate Program in Data Analytics: This program helps you to understand foundational concepts and hands-on learning of leading analytical tools, such as SAS, R, Python, Hive, Spark and Tableau as well as functional analytics across many domains.

To know more, please refer to our website: Data Analytics Course
To learn more about the Analytics watch this space until next week for the big news!

Everything you Should Know About Business Analytics!

Posted on by Imarticus Learning

Business analysts (BAs) are responsible for bridging any issues in the IT department and the business by creating new models after running strategy analysis. They evaluate processes, decide the needs of an organization and provide suggestions supported by appropriate data and draw reports to executives and stakeholders. 

BAs work with business leaders and users to see how data-driven changes to processes, products, services, software, and hardware can improve efficiencies and add esteem. They must articulate related thoughts or share observations yet in addition balance them against what is technologically practical and financially and functionally sensible.

How to make a career in business analytics?

Possession of hard and soft skills is an important prerequisite for becoming a business analyst. Not all business analysts need a background in IT as long as they have an overall understanding of how systems, products, and tools work.

On the other hand, some business analysts have a solid IT background and less experience in business but are keen on moving away from IT to this hybrid job. 

A relevant bachelor’s degree in business administration or finance will provide the necessary footing for your career as a BA, as any of the subjects hones your logical skill set and gives you a comprehensive layout of how businesses operate and meet targets. 

Numerous companies additionally incline toward individuals with an IT and engineering background. This is on the grounds that business analytics is highly dependent on software and technology. 

At the postgraduate level, you can choose to get straight to business analytics by opting for a certification course in Business Analytics. 

Business Analytics CourseIn any case, for some higher corporate positions like becoming a member of the board or working on high advisory positions, companies lean toward employees with an MBA (Master in Business Administration). This degree won’t throw you straight up into business analytics, but it can kick-start your career and fetch you a good salary. 

Further, a business analytics certification course with placement opportunities can extend employment opportunities, enhance pertinent skills and offer a higher return on investment in a limited timespan.

Notably, candidates with a business analytics certification are in high demand by the companies hoping to employ a BA resource. And, this interest area is considered by top colleges which have begun to offer business analyst courses online that are broadly acclaimed and perceived by the best organizations around the world.

Some of the business analysis certification courses with placement opportunities that strengthen the foundation of aspiring BAs are:

  • Certification for Business Analysts
  • Business Analyst Certification for Beginners
  • Certification of Competency in Business Analysis
  • Certified Agile Business Analyst Certification
  • Agile Analysis Certification Training
  • PMI Professional in Business Analysis

To have the high ground in altered business systems, possessing a business analytics certification is an absolute necessity for anybody seeking a vocation in analytics. In this day and age, it is self-perceived that data is a basic requirement in any calling.

In the business and sales industry, past data is utilized for decision-making and the development of business. Now you know how important a BA is, so why wait? Enroll in a Business Analytics Online Course to gain business analytics certification and grow your career.

 

Related Article:

https://imarticus.org/why-working-professionals-must-learn-business-analytics/

What is The Language Used To Make Artificial Intelligence Programs?

Posted on by Imarticus Learning

A.I. or Artificial Intelligence is considered to be the next big thing in the science community. Many people are worried about its lousy use; many have raised the fear of Skynet in the actual world through the artificial intelligence programs. Well, dangerous or not, when it comes to being in the league of new technology, big MNCs don’t like to fall back.

Having said that it is clear that people who have done big data and machine learning courses are the ones who are getting selected in big MNCs. While learning these courses, the main question that arises is: in which programming language are these Artificial Intelligence programs written? The answer is more than one. Let us list out the big guns of the artificial intelligence industries –

  • Python: Since its discovery, Python has gained significance as a popular programming language. Many artificial intelligence programs are written in this programming language. Python is liked among the personnel working in the artificial intelligence field due to its syntax simplicity and versatility. It is easier to learn than C, C++, Java, etc. It is more dynamic and supports neural networks, which makes it easier to develop NLP solutions in an ideal structure.
  • C++: C++ may be a little bit complex than Python, but it is one of the fastest programming languages out there. As artificial intelligence programs are vast numbers of lines of codes, the fast processing speed of C++ gives it an edge over the others. C++ allows the use of humongous algorithms while presenting statistical data. C++ is considered to one of the most suitable programming languages to learn for writing artificial intelligence programs.Investment Banking
  • Java: Java is popular among the programmers because of its ability to be a multi-paradigm programming language. The two main principles followed by Java are object-oriented programming and WORA principle. WORA or Written Once Read/Run Anywhere makes it possible to run Java programs over any system without recompiling it. It is best suited for Neural network and heavy-weight artificial intelligence programs.
  • LISP: LISP is not only a single programming language, but it is a family of programming language. It belongs to the category of the oldest programming languages in the market after FORTRAN. Although old LISP has evolved as the time passed to become one of the most influential programming languages used in artificial intelligence programs, it is favored0 in the account of the freedom it offers to the developers. LISP possesses an exceptional macro system which eases the work of implementation and investigation of specific intellectual intelligence programs.
  • PROLOG: PROLOG is the next oldest programming language in this list. It earned this position due to its underlying mechanisms which come in handy for various artificial intelligence programs. For example, PROLOG’s basic mechanisms include pattern matching, tree-based data structuring, automatic backtracking which are crucial for artificial intelligence programs.
  • Its mechanisms enable a flexible framework which is liked by the programmers. It is also known as a rule-based declarative programming language as its processing is done based on specific rules and elements which lay the very ground of artificial intelligence programs. PROLOG is one of the primary programming languages for artificial intelligence programs. It is used in some artificial intelligence enabled medical systems also.

So these were the first programming languages used in the industry to write artificial intelligence programs. These languages can be learned from various big data and machine learning courses. Organizations like Imarticus Learning are doing an excellent job in equipping people with the knowledge of these programming languages by their A-listed courses.

Top 7 Reasons to Convince You To Take on that Data Analytics Job

Posted on by Imarticus Learning

 

It’s more than just a buzzword, it’s a revolution– data analytics is here and here to stay. For four years in a row, data analytics was ranked the best job in the U.S. alone by Glassdoor in 2019. The data fever is catching on in other parts of the world too, as global economies become more interdependent and related.

More and more companies and industries are embracing data analytics, not least because it’s a science that delivers valuable insights applicable across all plans including business and marketing.

If you’re still hesitating about whether to go for a career in data analytics, allow these top 7 reasons to convince you:

#1: It’s in demand

Data analytics is one of the most in-demand jobs in the world today. This is because all industries need data-driven insights to make even changes, be it to pick a marketing option during A/B testing or rolling out new products. Data analytics is a high-skills, high-stakes job, which is why companies are ready to hire those willing to think creatively and derive data-based solutions to business problems.

#2: It’s easy to start

Educational institutions and course providers have sat up and taken notice of the demand for data analysts, leading them to introduce related training courses. Regardless of whether you’re a fresher or a professional in the tech field, data analytics training can help you start from scratch and build a portfolio of projects to showcase your skills These courses also provide tutorials in essential data analytics software such as Hadoop, Sisense and IBM Watson.

#3: There are plenty of job roles

Within the data analytics field, there are job roles that span academic divisions and aren’t restricted to engineering or software alone. Data scientists, systems analysts and data engineers will benefit from a background in the aforementioned academic fields. However, statisticians and digital marketing executives can look into roles such as quantitative analysts, data analytics consultants and digital marketing managers to put their skills to good use.

#4: The pay is good

The average salary in the data analytics field is US$122,000– a testament to how in-demand the profession is and how in dire need companies are of skilled employees. The figures vary depending on the role and job description but suffice to say that the pay is often much better than other technical jobs that people still seem to hover to by default. It’s also dependent on what industry you will work for, in what capacity and towards which goals.

#5: Growth opportunities abound

Technology is a dynamic field and with new changes come the chance to upskill, pick up new software and contribute to futuristic projects. Data analytics professionals can find themselves growing through roles and projects, oftentimes being tasked to lead a team or be the sole owner of a large-scale project.

#6: Industries are interwoven

With other tech fields, you might be restricted in your tasks or limited to a company. In data analytics, however, you get to pick and choose the fields you want, whether pure tech or even retail. Data analytics is in use across most industries so, once you find your niche, you’re ready to start dabbling in the industry of your choice.

#7: Influences decision-making

If you’ve ever wanted to be part of the larger organizational or business structure and contribute positively, chances are data analytics might be the niche for you. The insights that emerge from analyses of data can power strategies and create new business plans. This way, your contribution leads to progress on an organizational scale and your work can make or break a business.

Data analytics gives you the opportunity to become a more active stakeholder and contributor to any business regardless of the industry, so take the leap today.

Top R programming, SQL and Tableau Interview Questions & Answers!

Posted on by Imarticus Learning

Whether you are a fresher or an experienced data professional looking for better opportunities, attending an interview is inevitably the first step towards your dream career. Many of you might already have done a sneak peek into the world of data analytics through self-taught skills.

Data Science Course with Placement in IndiaHaving a good grip on the subject matter will give you an edge over other candidates. Data Science Courses and certifications add more weightage to your profile.

Interviewers might ask situation-based questions to test your knowledge and crisis management skills. So, make sure that you answer these questions wisely and showcase your knowledge wherever possible, without going overboard.

Listed below are some important R programming, SQL, and Tableau interview questions and answers. Check them out!

R Programming Interview Questions

A handy programming language used in data science, R finds application in various use cases from statistical analysis to predictive modeling, data visualization, and data manipulation. Many big names such as Facebook, Twitter, and Google use R to process the huge amount of data they collect.

  1. Which are the R packages used for data imputation?

Answer: Missing data could be a challenging problem to deal with. In such cases, you can impute the lost values with plausible values. imputeR, Amelia, Hmisc, missForest, MICE, and Mi are the data imputation packages used by R.

  1. Define clustering? Explain how hierarchical clustering is different from K-means clustering?

Cluster, just like the literal meaning of the word, is a group of similar objects. During the process, the abstract objects are classified into ‘classes’ based on their similarities. The center of a cluster is called a centroid, which could be either a real location or an imaginary one. K denotes the number of centroids needed in a data set.

While performing data mining, k selects random centroids and then optimizes the positions through iterative calculations. The optimization process stops when the desired number of repetitive calculations have been taken place or when the centroids stabilize after successful clustering.

The hierarchical clustering starts by considering every single observation in the data as a cluster. Then it works to discover two closely placed clusters and merges them. This process continues until all the clusters merge to form just a single cluster. Eventually, it gives a dendrogram that denotes the hierarchical connection between the clusters.

SQL Interview Questions

SQL online Training

If you have completed your SQL training, the following questions would give you a taste of the technical questions you may face during the interview.

  1. Point out the difference between MySQL and SQL?

Answer: Standard Query Language (SQL) is an English-based query language, while MySQL is used for database management.

  1. What is DBMS and How many types of DBMS are there?

Answer: DBMS or the Database Management System is a software set that interacts with the user and the database to analyze the available data. Thus, it allows the user to access the data presented in different forms – image, string, or numbers – modify them, retrieve them and even delete them.

There are two types of DBMS:

  • Relational: The data placed in some relations (tables).
  • Non-Relational: Random data that are not placed in any kind of relations or attributes.

 Tableau Interview Questions

Tableau is becoming popular among the leading business houses. If you have just completed your Tableau training, then the interview questions listed below could be good examples.

  1. Briefly explain Tableau.

Answer: Tableau is a business intelligence software that connects the user to the respective data. It also helps develop and visualize interactive dashboards and facilitates dashboard sharing.

  1. How is Tableau different from the traditional BI tools?

Answer: Traditional BI tools work on an old data architecture, which is supported by complex technologies. Additionally, they do not support in-memory, multi-core, and multi-thread computing. Tableau is fast and dynamic and is supported by advanced technology. It supports in-memory computing.

  1. What are Measures and Dimensions in Tableau?

Answer: ‘Measures’ denote the measurable values of data. These values are stores in specific tables and each dimension is associated with a specific key. This helps to associate one piece of data to multiple keys, allowing easy interpretation and organization of the data. For instance, the data related to sales can be linked to multiple keys such as customer, sales promotion, events, or a sold item.

Dimensions are the attributes that define the characteristics of data. For instance, a dimension table with a product key reference can be associated with different attributes such as product name, color, size, description, etc.

The questions given above are some examples to help you get a feel of the technical questions generally asked during the interviews. Keep them as a reference and prepare with more technically inclined questions.

Remember, your attitude and body language play an important role in making the right impression. So, prepare, and be confident. Most importantly, structure your answers in a way that they demonstrate your knowledge of the subject matter.

Related Article:

https://imarticus.org/20-latest-data-science-jobs-for-freshers/

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