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Tag: business analytics courses

The two paths from Natural Language Processing to Deep Learning

Posted on by Imarticus Learning

The two paths from Natural Language Processing to Deep Learning

Natural Language Processing is a branch of linguistics, computer science, and artificial intelligence that deals with the interaction between computers and human language, in particular how to design computers to handle and evaluate huge volumes of natural language data. We want a computer that can “understand” the text in documents, including its context and subtleties.

As a result, the papers’ data and insights may be correctly extracted by the technology, which can also classify and arrange the documents themselves.

Massive amounts of unprocessed, text-heavy data need a system like this, which is widely used in machine learning. Professionals with expertise in designing models that analyze voice and language, find contextual correlations, and generate insights from this unprocessed data will be in high demand as AI continues to grow. Natural Language Processing and Deep Learning with Python are one of the most common phrases used in the domain of Artificial Intelligence nowadays.  

In machine learning and artificial intelligence, a technique known as “deep learning” mimics human learning processes. Data science, which encompasses the statistical analysis and forecasting models, relies heavily on deep learning techniques to do its work. For data scientists, deep learning is a godsend since it speeds up the process of processing and understanding massive volumes of data. 

It is possible to think of deep learning as the automation of predictive analytics. Deep learning algorithms are piled in a hierarchical structure of increasing complexity and abstraction, while typical machine learning algorithms are linear.

Neural Networks and Deep Learning

A Neural Network, also known as an Artificial Neural Network, is made up of layers. Imagine the neurons in a human brain; they are the computing units, and they form a single layer when layered. stacking neurons together creates several layers. It is termed the input layer because it contains the data that we are working with. We run our algorithms and get an output, which is then utilized to do our computations for the following layer, the output layer.

At each successive layer, all of one layer’s neurons are linked to those at each successive layer, which are then linked to the next layer, and so on, until we reach our output layer, where we achieve our desired outcome for the specific data we were working with. Those layers that are between the input and output layers are referred to as Hidden Layers. A Neural Network is the result of this process.

A deep neural network is an artificial neural network with two or more hidden layers, and a model built on a deep neural network is referred to as Deep Learning. 

What are the main components of Natural Language Processing?

NLP consists of a number of components, a few of them are mentioned below:

  • Analysis of morphological and lexical patterns.
  • Syntactic Analysis: Study of logical meaning from a given part of the information, be it text or audio.
  • Semantic Analysis: Used to analyze the meaning of words.

8 benefits of Power BI for businesses

Posted on by Imarticus Learning

Businesses of all sizes are starting to realize the importance of data. To make informed decisions, you need access to accurate and timely information. It is where Power BI comes in. It allows you to visualize your data in various ways. This blog post will discuss eight benefits of Power BI for businesses. 

Power BI is a business analytics tool that enables you to connect to your data, visualize it, and share insights. With Power BI, you can get the most out of your data to make better decisions for your business.

Here are eight benefits of using Power BI:

Benefit # 01: Rich, personalized dashboards:

With Power BI, you can create rich, personalized dashboards with data visualizations unique to your business. You can include data from various sources, including Excel files, SQL Server databases, and cloud-based services like Salesforce and Google Analytics.

Benefit # 02: Seamless Integration:

Power BI integrates seamlessly with Excel, making it easy to connect to your data and get started quickly. You can use Power BI Desktop to create reports and dashboards that you can share with others.

Benefit # 03: Q&A functionality

With Power BI, you can easily ask questions about your data and get answers in return. This functionality is beneficial for businesses that want to make sure they get the most out of their data. 

Benefit # 4: No memory or speed constraints

 It means that you can quickly analyze large data sets without having to worry about your computer running out of memory or processing power. 

Benefit # 05: Collaborative features

With Power BI, you can easily collaborate with other team members. 

Benefit # 06: Drag-and-drop functionality:

Power BI also offers drag-and-drop functionality, making it easy to create visualizations and reports. 

Benefit # 07: No specialized technical support is required:

Power BI does not require any specialized technical support. It means that you can quickly get started with Power BI without having to worry about whether or not you have the right skillset. Additionally, Power BI is easy to use so that you can get started quickly and easily.

Benefit # 8: Supports Advanced Data Services:

Power BI also supports advanced data services, which means that you can easily connect and analyze your data. It is constructive for businesses to get the most out of their data.  

 If you are searching for the best technique to ensure you are getting the most out of your data, then Power BI is a tool you should consider.

Discover data analytics course in India with Imarticus Learning

This data visualization program is by industry specialists to help students master real-world Data Science applications from the ground up and construct challenging models to deliver relevant business insights and forecasts. 

Course Benefits For learners:

 

 

Does Machine Learning Excite You? Check Out Our Data Analytics Course!

Posted on by Imarticus Learning

Machine learning (ML) is truly a blessing to modern computing and technology, possessing the ability to endow systems and machines, the ability to think for themselves and tackle tasks on their own without any supervision of humans. Machine learning is able to do this by creating artificial neural networks which simulate how human brains work. Machine learning is assisted by data science and supports its applications in various fields.

Even though machine learning was initially invested upon with the primary focus on Artificial Intelligence, it was later recognized as a separate field and started being heavily invested upon from the 1990s and is one of the most valuable fields of computing that has one of the highest industry requirements of skilled professionals and freshers holding expertise in various skills and tools which assist in machine learning.

In this article, we will learn more about machine learning and how a well-planned data analytics course can help you progress in your career if you are already in this field or how it can help freshers get exposed to ML. 

What is machine learning?

Machine learning first came into existence due to the interest of having systems and computers learn from data on their own. “Machine learning” was first termed by Arthur Samuel in 1959, who was working in IBM at that time. During his tenure there, he was responsible for various important projects related to computer gaming and AI. It all started when Mr. Samuel took the initiative to teach computers how to play games through the game of Checkers on IBM’s first commercially available computer, the IBM 701.

Eventually, machine learning started being used for various purposes and borrowed many models and approaches from statistics and probability theory. AI uses predictive analytics along with machine learning to execute the various responses or trigger actions. All of this is acquired from the training data set which helps the machine in learning and equips it with the information.

Machine learning is an important branch of computing and data science that creates autonomous systems which learn from data on their own. A machine trained with clean processed data eventually identifies trends and patterns to respond to situations without human supervision.

Machine learning also promotes the automatic improvement and development of algorithms or data models which improve on their own. Machine learning is an important part of Artificial Intelligence which uses data mining, predictive analytics, and various tools to assist machines in learning more extensively with methods like deep learning to allow them to execute functions that emulate the responses of a human, just much more accurate and fast.

Machine learning is also not biased unless specifically asked to do so, hence promoting unbiased AI-supported systems that make fewer errors. Data mining is also a very relevant field and quite valuable to machine learning as it helps systems come to conclusions without having some bits of data or having unknown bits of information. Machine learning is a type of predictive analytics which is backed by data and is exploratory in nature.

Perks of a Data Science Prodegree from Imarticus

The Data Science Prodegree is a great data science course that students and working professionals can choose to gain more exposure and skills in the fields of machine learning, business analytics, and AI.

 

  • Acquire skills and learn how to use required tools and algorithms
  • Gain valuable industry and course certifications
  • Get placement support and opportunities from the best companies
  • Advanced live classroom learning supported by technology and real-life projects

 

Imarticus’s Data Science course with Placement is a great choice if you wish to advance in your career and learn about machine learning, AI, business analytics, or data analysis which will help you become more effective as a data scientist and pursue your dream career in this respectable field.

AI, Data Science, Machine Learning Terms You Need to Know in 2022!

Posted on by Imarticus Learning

In the present paradigm of technical knowledge, it is imperative to be aware of certain concepts to survive and thrive. Whether you are pursuing a career in artificial intelligence (AI), have a cursory interest in data analytics, or simply wish to broaden your horizons, here are some artificial intelligence, data science, and machine learning terms you need to know in 2021. Read on…

  1.     Natural language processing: 

Both humans and computational devices use their own modes of language to communicate and share ideas to the extent of imparting and debating on the information. The languages, however, are different in their basic forms and formats. Using natural language processing, or NLP, artificial intelligence can decipher many human languages to suit specific functions that may range from the academic study of linguistics to providing utility to hearing-impaired people.

  1.   Data warehouse: 

A data warehouse, as the name suggests, contains a large ensemble of data pertaining to businesses and learnings from past successes and failures to provide better services. One who is not entirely proficient in data architecture may yet take the advantage of data warehouses to gather business analytics courses and make far better decisions. This method allows one to find new ways to process old data and change future iterations of that data with his/her actions. 

Career In Data Analytics   Data journalism: 

This is a mode of journalism that is slowly gaining greater prominence and is proving its necessity in combating the ever-growing trend of fake news. In this form of news reporting, one focuses on proving his/her assertions through the collection and presentation of reliable data. This may be done through human and/or AI collection and calculations. Soon, we may be able to have a collated base of data obtained through AI learning. This will make it very hard for individuals and/or groups to spread misinformation.

  1.   Deep learning:

This uses artificial intelligence to construct structures that mimic the human neural network – starting from simple problems to finding layers of hidden information. Meanwhile, it makes errors and learns from them with the program often ending up with a different solution than what was expected by its programmers and set parameters. Using this process, we can identify and solve possibly any real-world problem. The degree of human supervision in this process can be ascertained at various levels of this process.

  1.   Cybersecurity: 

Both defenders and attackers of databases are getting smarter, escalating the never-ending battles between cybersecurity and hackers. Often, the strategies used by either group are similar to the point of being indistinguishable. Here, any large organization employs AI and/or deep learning to be one step ahead of the threats that plague them.

The above-mentioned terms are only the tip of the iceberg when it comes to talking about new technology-related topics. Hopefully, they have provided you with new avenues to look into as per your interests, or at least recapitulated some of the basic terminologies.

How Do Business Analytics & Data Analytics Differ? What Are Their Applications?

Posted on by Imarticus Learning

Both business and data analytics is about processing data and gaining insights from data.

The terms business analytics and data analytics might be used interchangeably in organizations on a small scale. On the other hand, big firms hire both business analysts and data analysts to perform well-defined functions, thus making it very necessary to understand the difference between the two.

With Imarticus’s, you can choose between the best data analytics courses and business analytics courses in India. Read on to have a deep insight into the two important career paths and their respective applications.

best data analytics courses in IndiaBusiness Analytics

Business analytics course focuses on business impact when analyzing data and the actions that should result from the insights. For example, it provides answers to the following questions, “Should a company develop a new product line?” Or, “Should it prioritize one particular project over another?”

Business analytics combines various capabilities, tools, and applications to measure and improve the effectiveness of core business functions such as marketing, customer service, sales, or IT.

Business analysis (also Business Analytics) is the iterative exploration of a company’s data. There is a statistical analysis method used to bring information to light that can help to stimulate innovation and business results. Companies that rely on analysis consider big data to be a valuable asset of the company: data helps to advance business planning and forms the basis for future strategies. Business analysis helps these companies get the maximum value from this gold mine of insights.

Sufficiently large volumes of high-quality data are required for business analysis. Companies that want to achieve the most accurate results possible have to integrate and compare the data from different systems. A decision is then made as to which subsets will be made available to the business.

Data Analytics

A Data analytics career involves combing through massive data sets to identify patterns and trends, create hypotheses, and support business decisions with data-based insights.

For example, data analytics seeks to answer questions such as, “What impact do geographic factors or time of year have on customer preferences?” Or, “What is the likelihood that a customer will defect to a competitor?” In practice, data analytics encompasses many different techniques and approaches. It is also known as data science, data mining, data modeling, and big data analysis.

In data analysis, raw data is collected and examined to conclude it. Every company collects huge amounts of data, such as sales figures, market research, logistics, and transaction data. The real benefit of data analysis is in identifying patterns in a data set that can indicate trends, risks, and opportunities.

Data analysis enables companies to use this knowledge to change their processes to make better decisions. In practice, data analysis can help, for example, to decide about the next product developments, to develop customer loyalty strategies, or to evaluate the effectiveness of new medical treatments.

Applications of Business Analytics and Data Analytics

Since Business Analytics and data analytics are both based on big data tools, they have several applications in various industries across the globe. Some of them are mentioned below:

  1. Digital Advertising
  2. Energy Management
  3. Medical Applications
  4. City planning and mapping
  5. GPS tracking
  6. Transportation
  7. Risk detection and management
  8. Security
  9. Transportation
  10. Traveling
  11. Customer interaction
  12. Internet Browsing
  13. Expenditure Management

Conclusion

Business and Data analytics share the same overarching goal: use technology and data to drive business success. We live in a data-driven world where the amount of information available to businesses is growing exponentially. Both functions in combination can help companies achieve maximum efficiency and gain some useful insights.

Imarticus Learning: Fuelling India’s Data Analytics Workforce

Posted on by Imarticus Learning

What is Data Analytics?

 Data Analytics involves analyzing raw data and drawing meaningful conclusions and patterns from that data. In data analytics, a lot of processes are automated to eliminate manual intervention. You can take up a data analytics course to understand the intricacies of the subject.

In data analytics, a lot of algorithms are prepared to make the job easy. These days you can take up a data analytics course with placement. A data analytics certification course makes you credible enough for the job.

Understanding Data Analytics

best data analytics certification courses in IndiaData Analytics can be complex when you try to understand it. A data analytics certification course can help you know what the subject entails and how to make the best use of it. The data analytics course will also introduce you to the world of algorithms.

Data Analytics is a broad subject that includes several diverse types of data analysis techniques.

Data Analytics can be used to mine different kinds of data insights. These insights can be used in improving processes and transforming them for the convenience of the data users. You can take up a data analytics course with placement to practically apply these algorithms and techniques of data sorting and data analysis.

Companies like Imarticus Learning are tirelessly working towards making the Indian workforce tech-savvy and well-versed with data analytics and its application. If more and more workforce joins hands with Imarticus to learn data analytics, the workforce will become digitally enabled to deal with a large amount of data. They would know how the data would be put to proper use.

Use Cases of Data Analytics

Data Analytics training can be used to understand several trends that dominate the market. You can apply predictive analysis using the insights from these data points. Several industries are now making use of data analytics to optimize their processes.

For instance, in the manufacturing industry, data analytics is used to store and record runtime, work queue, and downtime of all the machines in the factory. The data can then be utilized to optimize all the processes and to make manufacturing better.

However, data analytics is not limited to spotting bottlenecks in the process. It can do much more. It can make the entire process better and more efficient. You can also use data analytics to speed up the manufacturing process as a whole, as with data analytics, you can reduce the waste to a great extent.

Types of Data Analytics

If the workforce knows how to use Data Analytics, they will be able to use technology better. Some of the types of Data Analytics are:

  1. Descriptive Analytics: This is used to understand what has happened over a while.
  2. Diagnostic Analytics: If something happens, you can analyze what went wrong using diagnostic analytics.
  3. Predictive Analytics: In the case of predictive analytics, the algorithms are used to predict a future trend.
  4. Prescriptive Analytics: These algorithms are used to take a suggestive measure for any action.

Conclusion

Building an analytics workforce is the need of the hour. Therefore, it is essential to train more professionals and prepare them for the analytics world. Digital literacy is very important to automate functions, and data analytics is an integral part of it.

Imarticus is on a spree to enable people to use data analytics to decode patterns and understand data. Imarticus has several courses on data analytics. You can enroll in all of these courses to get an in-depth insight into how data analytics works and make the best use of it. The certifications from Imarticus have a great value in the industry.

Top 5 Skills for Business Analysts – You Should Be Aware Of!

Posted on by Imarticus Learning

Careers in business analysis have shown excellent success rates and this is probably why a lot of aspirants in the job market aim to be business analysts. However, for those who want to excel in this career field, a quick summary of the top skills needed to be one would be helpful.

 5 Skills Required for a Successful Business Analyst

  1. Problem Solving Skills: For a business analyst, each project offers different issues and problems that require quick, long-term solutions. So, a business analyst must be able to learn about a problem, analyse the available solutions and then recommend the best option. They must be able to look at a problem from multiple perspectives within the business – that of a technical expert and the end-user. A business analyst training courses must be able to work in a collaborative problem-solving environment where continuous discussion with technical team is possible and solutions that are technically viable are discovered.
  1. Communication Skills: For a typical IT analyst, modes of communications include meetings, discussions, emails, documents, charts and many other. In all these modes, a BA must be able to be concise and clear. The communication of a business analyst is not always about getting their points across but also about understanding what others have to offer. So, patient listening, communicating adequately are key skills an analyst must possess.
  1. Management Skills: A business analyst has to juggle several activities in each day and he or she should be able to manage all these activities effectively. These activities include gathering requirements, documentation of requirements, getting sign-offs, testing, ad-hoc tasks and managing the project as a whole. Balancing all these tasks is a crucial requirement for an analyst or a vicious circle of deadlines will be all around them.
  1. Technical Skills: Even though a business analyst is not required to write codes for the project, some basic knowledge in IT is important to succeed in this career. A business analyst is expected to act as a conduit between the technical and business departments of an organisation. To work among these departments with confidence, a working knowledge of the technology is required. MS Office Suite, Operating Systems, Testing Skills, Programming Languages, and Data Base are some areas where a business analyst is expected to have some knowledge.
  1. Analytical Skills:Being able to tackle every single problem analytically is one of the most important skills for a business analyst. That refers to understanding a problem, visualizing it, analysing it, and solving it. An investigative approach backed with logical thinking and interpretation skills are required to achieve this feat. Knowledge in various analytical techniques such as Interface Analysis, Feasibility Analysis, and SWOT Analysis is recommended.

The skills mentioned above are kept to the more important ones than other soft skills. Obviously, skills like presentation, ability to work as a team, flexibility etc. are also required for a solid career as a business analyst. If you are ready to expand your skills and keep them up to date, you will certainly find success in this fast-growing field.

How Businesses Are Building Futures With Data Analytics?

Posted on by Imarticus Learning

Data analytics handles the raw data from the resources using technology, algorithms, and mechanics into a simpler and human-friendly version to help data businesses and organizations. It is now an important factor that drives the business as well as the decision-making process in everyday lives.

In one way or the other, business and organizations depend on data analysis to improve their trade. It wouldn’t be wrong to say that business analytics and Artificial Intelligence have both a major role in building the future everywhere.

  • General analysis: A business needs everyday updates to keep up with the market and trends. It is necessary to identify the low and high points to work on these areas to make the necessary changes. Such random analysis can find new opportunities and can predict the capability of the new strategies.

    This is highly important for all types of businesses in any field. Whether it is the retail, healthcare, medical, technology, food industry, online industries, etc. They all rely on big data to help improve their services.

  • Business improvement: The pandemic has brought the world to a standstill for a while. It is now slowly improving its pace but there are several companies and businesses that suffered a huge loss. In order to get their business back on track, they can rely on data analysis. Finding what is trending or what the public is expecting is the key to a restart. Identifying the trend allows planning and strategy to make necessary changes in the projects to make it plausible for the future and improve the business.
  • Automation: Automation is something the general public does not think about too much but most of them are using it every single day. The use of AI and Machine Learning has integrated to come up with ideas such as Alexa, Siri, Google voice, etc.

    Apart from these, voice-controlled automobiles, electric devices, etc are all part of this. These are definitely in the initial stages right now and have better prospects for the future where they can be applied in many more domains and areas. It is even possible to attract more customers and urge them to use the same.

  • Managing data: The biggest huddle in data analysis is managing the raw data. With the accumulation of data growing in every department of life, it is significant to have proper usage of the stored data. Data analytics Certification could be used to find ideal solutions for the problems in each department.

    Data is useful for every business and department and it is up to the data scientists to find the use of these pieces of information. This is exactly why data scientists are the hottest job profiles in the current scenario. They are needed by every business to build their future by creating strategies for success and predicting their prospects. Since people provide their data in one form or the other through various mediums, managing this data holds a key role in the future of businesses and public lives.

Conclusion
Data analytics was started as a part of technology is now an integral part of lives that has an impact on almost all levels and departments of life. Such reliance on data increases the competition between businesses and it can be healthier when they can identify their key to success from the data available.

But ultimately, it all comes down to how each of them identifies and interprets the same pool of data with their insights and implements them along with the same pulse of the public. After all, going with the trend is more reliable than finding something new and making it successful.

6 Ways in Which Artificial Intelligence is Revolutionizing the Real Estate Business

Posted on by Imarticus Learning

Real estate is not simply buying and selling lands and houses – there is a whole, large industry dedicated behind those acts. It is a given that the age of technology has also affected something that seems so analogous, so much that a huge part of that process has also digitised today. Artificial Intelligence is currently playing a large role in making the work of the decision-makers in the industry easier – let us take a look at how AI plays a huge role.

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A large problem for real estate agents was the act of finding or recommending the perfect plot of real estate for a customer. This might not have been clear even after lengthy talks on the subject, but AI has been making that much easier. Since machine learning and AI feeds on data, the larger the amount of data, the better – they can now find the perfect piece of land.

Availability

The making and use of chatbots have now become an established part of many data science courses, and these can help real estate developers too. Chatbots can be used to learn about customer preference round the clock, and customers now have something to answer their simple questions and grievances at any time of the day.

 Prediction

AI is also able to make a large number of meaningful predictions, from the data provided to it. This can be beneficial in various models, like tracing the price of a particular plot or the changes in customer preferences.

 Automation

Real estate is an extremely documentation-heavy field, so it can be a chore to carry out all the documentation constantly. In this work, the use of AI could lead to quicker uploading and scanning of jobs and documents.

Virtual Tours

Another one of the path breaking implementations, people can now visit any plot of land on offer from any point in the world – virtually, of course. Virtual tours of the homes in question are truly making a huge difference in customer satisfaction and business development.

Disaster Management

Using AI systems, it is now possible for planners to run simulations and build proper disaster-resistant houses so that such natural disasters are mitigated when the inevitable occurs.
If you want to learn more about such important tools like AI or business analytics, you should definitely check out the business analytics training courses offered by Imarticus Learning!