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Category: Management

2022- The Wake-Up Call for Strong Logistics Management?

Posted on by Imarticus Learning

The global pandemic was a downward spiral for several industries but the logistics industry handled it as a wake-up call. Even though there are several areas where they incurred loss, the overall outcome of the pandemic proved to be positive for it. Increased use of AI-driven technologies has helped this industry map a new strategy for the upcoming years. 

The last two years have been a learning curve for the logistics industry so, in the year 2022, the industry needs to strategize its moves for the upcoming years. With the help of the latest technologies, those who have completed a Logistics and supply chain management course could extend their services to change the overall face of this industry. 

Future of logistics industry in 2022

The COVID-19 pandemic forced the supply chain system to shift from the low-cost management system to an agile framework of data-driven technologies. A major percentage of companies in this industry have already invested in such technologies. It helped the management to make decisions based on the data. The future of this industry will be seen in some key areas. The future trends in these areas are mentioned here. 

  • Better visibility

One of the strong positive outcomes of the pandemic is higher visibility of the supply chain system. The real-time tracking of the consignments and instant feedback from the customers etc will enable the companies to have a re-evaluation of themselves. They can use the data to make appropriate decisions and make their service more impactful. 

  • Optimized network

A logistics company may be provisioning shipments internationally, nationally, and in local areas. They must have a quality optimized network to have customized changes according to the region and the behavior of the customers. 

  • Changing customer expectations

When the supply chain system has improved its functioning the expectations of the customers have also increased many folds. They expect lower costs with faster shipping and a simplified return policy. They are even ready to pay for the same-day delivery so the companies must comply with such demands and make the necessary changes. 

  • Better risk mitigation

Utilizing centralized data to come up with reliable forecasting plays a huge role in preventing losses. The major steps that can prevent loss or risk are automation and optimization of the various processes. It helps minimize the possible errors. This is one of the strong points that you can learn from a supply chain management online course. 

  • Stronger relationship management

A resilient industry requires stronger relationships between the various departments and the personnel involved. A larger company may find it difficult to comply with this but they can share the data among all the departments and bring them all to the same page. This will eliminate the issue of lack of visibility in the lower levels of the chain. 

Conclusion

The best approach for logistics companies is to hire professionals who are trained to achieve these goals. They can understand the changes much better and can also come up with successful strategies that have a positive impact and reduce risks. 

One of the best and most popular choices for the aspirants is to choose the Certification in Supply Chain Management and Analytics course from Imarticus. The course is in collaboration with IIT Roorkee. 

This course will be ideal to prepare you for the job description of a Supply Planning Analyst, Supply And Operations Planner, or Logistics Manager with the right knowledge in the key operational areas. Upskilling with the latest technologies and methods will be essential to understand future trends so that you can make appropriate decisions. 

Here’s why music created by AI is better than you think

Posted on by Imarticus Learning

Artificial Intelligence or AI is capable of carrying out tasks that are much more advanced than just arranging words to generate lyrics. AI already has the ability to offer an immersive listening experience by adapting to a user’s preference. As seen in Spotify and Apple Music for a long time, AI systems understand the user’s preference and recommend songs that the user will enjoy.

AI has gone a step further and now is also able to compose completely personalized music for users. AI can understand certain benchmarks such as harmony, structure, and balance, using which, AI models can generate songs or background music based on the input provided by the user.

Is AI Capable of Creating Better Music Than Humans?

If AI is able to compose music without human supervision, people who need background tracks or copyright-free songs might not need music producers or artists as much as they currently do. Purchasing AI-created music also is easier as there are no royalties while the music generation process would be faster and available on demand.

Yes, with vast amounts of data and training, AI can help in creating a very capable autonomous music generation system, however, it will still be relying on historic data and other pieces of music in order to generate future songs. But, due to the vast amount of data available, the probabilities are limitless and if taught to truly identify good music, AI can become capable of generating hit songs one after another using the very same data.

Even coming up with new songs are just mathematical likelihoods for AI and by analyzing enough combinations, AI is bound to come up with good music. Similarly, meaningful lyrics can also be generated with Natural Language Processing or NLP. However, it will take a while till AI systems become as sensitive to the context of lyrics and innovative in using musical notes.

How AI is Helping in Creating Music?

Even though completely AI-generated music has not reached the Billboards Top 10 yet, services such as AIVA uses AI and Deep Learning models for composing soundtracks and music for users. This helps both small content creators and mainstream celebrities generate music for YouTube, Tik Tok, Twitch or Instagram. This is a cheaper alternative as well. Amper is another great online tool for content creators and non-musicians to make royalty-free music based on their own preferences and parameters. Amper has been created by the music composers who are behind creating the soundtrack for movies such as ‘The Dark Knight’. 

Alex the Kid is a UK-based Grammy-nominated music producer who has used ‘heartbreak’ as a theme and with the help of Machine Learning (ML) and Analytics, has created the hit song ‘Not Easy’. The song even features celebrity music artists such as Wiz Khalifa, Sam Harris, and Elle King.

The hit song had reached the 4th rank in iTunes’ ‘Hot Tracks’ chart within 2 days of its release. Alex used IBM Watson for analyzing billboard songs of the last 5 years as well as cultural and socially relevant content, scripts, or artifacts in order for including references to these elements within the song. Then, the producer used Watson BEAT, the ML-driven music generation algorithm powering the cognitive system for coming up with various musical backgrounds till he found the most suitable combination. 

Conclusion

Artificial intelligence and Machine learning courses can definitely help one learn AI topics for getting involved in interesting projects such as those mentioned above. A Machine Learning and Artificial Intelligence course, such as one offered by Imarticus, are essential for building AI systems such as soundtrack generators or lyrics generators. 

What competitive advantages can be achieved through integration, automation and big data in supply chain management

Posted on by Imarticus Learning

The need for Supply Chain Management (SCM) integration, automation, and big data are increasing rapidly. In order to stay competitive in the marketplace, it’s imperative that organizations have a strong SCM strategy in place. The benefits of integrating these three technologies are enormous – from efficiency gains to cost reductions to improved customer satisfaction.

With a single view across all supply chain activities, teams can make informed decisions about capacity utilization and inventory levels. They can also identify new opportunities for growth while identifying potential risks ahead of time.  

The benefits of integrating the three technologies go beyond SCM

  • Integration reduces complexity and downtime in manufacturing plants by applying automation to key business processes such as Supply Chain planning and scheduling. This enables organizations to achieve higher levels of performance with less human intervention – leading to greater efficiency throughout the entire enterprise. 
  • Automated systems can reduce errors and improve productivity while also freeing up employees’ time for more valuable activities like research and development or customer service initiatives. 
  • Big data offers a treasure trove of opportunities that enterprises are just beginning to tap into today. In addition to providing new insights on sales trends from across the supply chain network, big data analytics lets companies gain critical knowledge about their customers, which they can then use towards improving product development and marketing strategies.

Big Data Analytics, Supply Chain Integration, and Automation are three technologies that can’t be ignored in today’s competitive marketplace. By integrating these technologies together within a single platform or solution to achieve seamless supply chain collaboration across an enterprise, people not only realize numerous benefits of the Supply chain Management course – but they’re able to create new business opportunities that will set them apart from their competitors now and into the future.

Some Other Benefits Listed!

– More efficient utilization of resources (inventory levels) within organizations throughout the value chain network.

– Better understanding customers’ needs which allows for improved product development/marketing strategies as well as better service delivery through channels like social media etc…

– Competitive advantages via increased efficiency along with shorter lead times resulting in greater customer satisfaction.

– Ability to identify new opportunities for growth which help organizations stay ahead of the competition now and into the future.

In addition, integrating automation within supply chain management systems allows companies to realize operational benefits such as:

– Improved throughput/performance levels through reduced error rates due to lowest cost staffing models that provide minimal human intervention across all processes.

– Reduced downtime resulting in continuous operations with increased capacity utilization along with lower fixed costs per unit produced etc…

Finally, big data analytics provides a treasure trove of business insights by giving enterprises access to a wide variety of customer information from throughout their value chains. This data can then be mined for critical knowledge about existing customers and prospects who may not have been considered or targeted before now, which can then be used to improve product development and marketing strategies.

Boost Your Supply Chain Management Career with Imarticus Learning

At Imarticus Learning, supply chain aspirants can make their supply chain management career with the 6-months program that is uniquely designed by IIT faculty and industry leaders. With the ever-increasing trend of e-commerce, the amount of movement of goods has been ever-increasing. There has been a top-heavy jump in the number of jobs for SCM across industries.

Course USPs:

  • Cutting-edge curriculum and certification from e-learning Centre, IIT Roorkee
  • Experiential learning & impressive project portfolio
  • SCM and analytics – a power couple
  • Learn through real-life industry projects.

For further details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon.

Understanding the basics of data visualization with python

Posted on by Imarticus Learning

Data visualization has become an increasingly important part of the data analysis process in recent years. Many analysts have found that a picture is worth a thousand words, and in this case, it just might be true. You could say that good data visualization can save even more than 1,000 words–it can save lives! Let’s explore some basics of making compelling visualizations with Python.

What is Data Visualization?

Data visualization represents data in a visual form. You can use visualizations to help people understand data more efficiently, ranging from simple graphs to complex infographics. Data visualization is an increasingly popular field with many practical applications. For example, you can use it for business intelligence gathering and analysis or education purposes. Some experts consider data visualization to be a vital part of the expanding field of big data.

Data types and how they get visualized?

There are many types of data, including categorical, univariate, multivariate normal, and so on. Data visualization methods vary depending on the type of data represented. For example, there are several other ways to express categorical data than with graphs.

Univariate data is usually best displayed in a simple bar graph or line graph. Categorical information is often best represented by a pie chart. Multivariate data can be shown in a radar graph or spider chart, while multivariate average data get visualized with a scatter plot.

How to use Python for data visualization?

Python is an easy-to-use programming language that You can use for data visualization. Many libraries, including matplotlib, make it possible to create visualizations without much technical knowledge.

You can even create interactive online visualizations using Python. For example, you can use Python to create visualizations for the Vega-Lite specification, which allows you to create interactive online data visualization. Due to its flexibility and ease of use, it has become one of the most popular languages for data science. It is perfect for working with large amounts of data because it can easily handle large lists or arrays.

Python-based data visualization libraries are beneficial because they typically allow for rapid prototyping of visualizations. It makes them an excellent choice for exploratory data analysis because you can quickly try out different algorithms and processes. The downside is that they can sometimes be challenging to use for more complex projects.

Explore and Learn Python with Imarticus Learning

Industry specialists created this postgraduate program to help the student understand real-world Data Science applications from the ground up and construct strong models to deliver relevant business insights and forecasts. This python tutorial is for recent graduates and early-career professionals (0-5 years) who want to further their careers in Data Science and Analytics, the most in-demand job skill.

Some course USP:

This Python for data science course for students is with placement assurance aid the students to learn job-relevant skills.

 

Impress employers & showcase skills with the certification in Python endorsed by India’s most prestigious academic collaborations.

World-Class Academic Professors to learn from through live online sessions and discussions.

How to forecast high-profit low-volume products in supply chain management and analytics

Posted on by Imarticus Learning

Supply chain management is a broad term that has many applications. Supply chain managers are responsible for ensuring that the right products get to the right place at the right time and that they have all of their necessary components. Supply chain analytics can be used in almost any industry, but it is especially important in industries where high-profit low-volume products exist – such as fashion retail. Hence, a supply chain management career is in high demand.

The Growing Importance of SCM Analytics?

Supply chain management and analytics are becoming more important than ever. Supply chains are growing in size, importance, and complexity – especially as modern businesses expand into global markets. Supply chains have become so complex that managers can no longer rely on traditional methods of forecasting such as historical data or gut intuition! Instead, they must develop a new approach to forecasting high-profit low-volume products using supply chain analytics!

How to forecast high-profit products in supply chain management and analytics?

  • As Supply Chain Management continues to be a growing field for professionals, the relationships between companies and their suppliers continue to grow as well. Over the past few years, there has been an increase in focus on analytics within supply chain management as it can help provide better insight into business decisions that need to be made. 
  • When considering forecasting high-profit low volume products with Supply Chain Analytics, certain tools may come in handy. With the Logistics and supply chain management course, software programs, and analytic tools available today, Supply Chain managers would have more opportunities than ever before when trying to forecast demand for future products they will sell. 

     

  • Using analytical methods like linear regression analysis can also offer helpful techniques on how best to predict demand for certain products. This can be used when Supply Chain Management professionals want to forecast demand for different types of products, especially those with low volume and high-profit margins. 
  • Other methods Supply Chain Managers can use are multi-variate regression analysis as well as decision trees which may help them make better business decisions in the future concerning their supply chain management processes. 
  • With a greater emphasis on Supply Chain Analytics combined with effective forecasting techniques, Supply Chain Managers will have more opportunities than ever before to offer customers an improved experience throughout their buying process. 
  • Using these tools effectively would also increase sales revenue from new product offerings since having access to this type of data is becoming increasingly important among modern businesses today. 
  • In conclusion, Supply Chain Managers can use Supply Chain Analytics, Econometric Forecasting Software, and Statistical Modeling Tools to effectively forecast high-profit low volume products every day. This allows them to increase their sales revenue from new product offerings as well as offer customers a better experience throughout the buying process.

Make Your Career in Supply Chain Management and Analytics with Imarticus Learning

Imarticus Learning offers a Supply chain Management course to build the career of supply chain aspirants. The duration of the course is 6 months. It is uniquely designed by IIT faculty and industry leaders to help you learn and make a bright career. With the ever-increasing trend of e-commerce, the amount of movement of goods has been ever-increasing. There has been a disproportionate jump in the number of jobs for SCM across industries.

Here’s Course USPs:

  • Experiential learning & impressive project portfolio
  • Cutting-edge curriculum and certification from e-learning center, IIT Roorkee
  • Real-life industry project-based learning for a better know-how.

For further details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon.

What’s happened to the data analytics job market in the past year?

Posted on by Imarticus Learning

A data scientist has been one of the topmost jobs people have been trying to land for a long time. And well after witnessing the benefits of data science and analytics in literally every sector, there is no wonder why. It helps in fields like education, retail, customer service, the health sector, and tourism. It helps corporate firms where it matters. That is, in processing, analyzing, managing, and storing a vast amount of data.

It also helps them to make predictions according to the changing market trends and client demands. This is why it is important to learn data analytics if you want to pursue a career as a data analyst. 

A lot of institutions offer good data analytics courses in India. Check out Imarticus Learnings’ data analytics certification course to hone your skills properly. This will provide you with enough exposure and real-life experience which, in turn, will help you land your dream data analytics job. 

However, last year saw the data analytics job falling behind in the charts for the first time. Now, is it finally coming down from its throne, or is it just another victim of the coronavirus? That is what we are trying to figure out here. Keep reading to learn more.

Is the market decreasing or a victim of Covid-19?

2020 saw a lot of upheavals globally. From educational institutions being shut down to corporate offices going on hiatus for months and some small businesses going out of business altogether, it was a year of getting used to the new normal. With that came the trend and the necessity to work from home.

Not to mention the terrible loss people faced all over the world. Unfortunately, with the new variant on the rise once again, the troubles seem far from over as of now. This also caused a lot of people out of jobs overnight. Not only that, but a lot of jobs went out of practice as well. 

People are still figuring out how to cope with this unprecedented situation. So, as of now, it is really up for debate as to what caused this upheaval in the hierarchy of job positions. Some things come into play though when it comes to changing market trends. Let us look at the situation by trying to analyze those.

Economic factors that factor into changing trends

About three major factors disrupt an ongoing situation, especially in the job market. Those are, as follows:

  • Demand: The reason why any job ranks as the topmost is its demand. Thankfully, the demand for a data analytics job is still very high, as it still ranks as number three on the list. So, the era of data science is far from over.
  • Supply: The supply of data scientists is quite low as of now. And, it seems that it is going to stay that way for years, so the job is going to keep reigning over for a long time.
  • Growth: Growth is a major factor when it comes to any job being relevant. And, the market for data scientists is still growing. In fact, if reports are to be believed, then this field saw an increase of about 650% since 2012. So, it is safe to say that the market will remain relevant in the coming years.

Conclusion

To begin your career as a data analyst, you need to learn from the best. Check out Imarticus Learnings’ data analytics course and boost your career to the max. 

Here’s what happens when you master the concepts in artificial intelligence

Posted on by Imarticus Learning

Artificial Intelligence is the ability of machines to take action or make decisions on their own without human supervision. AI fundamentally tries to emulate the intelligent behavior of human beings and handles tasks similarly, if not in a more efficient manner.

Artificial Intelligence is also attributed to being faster and being unbiased (unless training data is biased). AI, Deep Learning, and Machine Learning power a lot of services and products we use in our day-to-day life.

Implementations of AI

Here are some implementations of AI:

  • Autonomous Vehicles: Autonomous Vehicles such as Teslas are AI-driven and are able to avoid collisions and navigate around with ease with the help of various sensors such as LiDAR and cameras.

  • Robots and Drones: Robots and Drones are becoming autonomous with the help of AI and now do not require human supervision or a human remotely controlling these machines.

  • Chatbots: Chatbots are smart response systems that are great implementations of AI-powered by NLP or Natural Language Processing. Chatbots are becoming smarter and cannot be distinguished from real human beings soon.

  • Virtual Assistant or Voice Assistants: Virtual Assistants and Voice Assistants such as Cortana, Siri, or Google Assistant are all powered by AI and learn from our actions as well as data from users worldwide to make our digital experience better or to carry out tasks for us better.

  • Sentiment Analytics: Sentiment Analytics use AI that is trained with the help of data that has been labeled with positive, negative, or any other custom sentiments. With the help of this and NLP, the software is able to determine the sentiment behind textual data, social media posts, or content.

  • Search Engines: Search Engines such as Google and Yahoo are powered by AI as well to make searching for things easier and fetch the most relevant results. The AI models in Search Engines are trained to fetch related results as well.

  • Smart Homes: Smart Homes used IoT (Internet of Things) devices and various sensors in devices such as phones and watches in order to provide homeowners with a better experience or a customized experience. For instance, setting the right temperature when the owner returns home or turning on specific lights when the user goes into a room. These smart homes can also be customized directly through mobile devices but owners can also decide to let them act autonomously.

  • Predictive Texts and Spell-check: Predictive texts are spell-checking features that are also powered by AI that is trained using NLP models. These systems are added to software or devices to automatically detect grammatical errors or identify spelling mistakes. Devices, applications, and even services such as Gmail can now even predict the next thing you are about to say and offer suggestions to make one’s job easier.

  • Media Recommendation Systems: Media recommendation systems are implementations of Machine Learning that powers services such as Netflix, Spotify, Youtube, and others. These AI implementations use a user’s video or audio history data and then suggest other media that the user might enjoy.

  • Production and Manufacturing Automation Systems: AI empowers the automation of production and manufacturing. BPA or Business Process Automation helps in reducing cost and AI-backed machines help in making manufacturing more efficient than human workers.

How Mastering AI Helps You

Mastering AI can help one get very desirable job roles in MNCs such as Microsoft, Amazon, Google, or Netflix. One can learn AI topics with courses such as the Artificial Intelligence course in E&ICT Academy, IIT. The Artificial Intelligence course in E&ICT Academy, IIT is a great way to start your career in AI.

How is RPA impacting the supply chain management and analytics industry?

Posted on by Imarticus Learning

RPA stands for Robotic Process Automation, which is a new system used in supply chain management systems. RPA automates those processes that are otherwise operated manually. This reduces errors and anomalies drastically. It allows the companies to utilize their employees for actual brainstorming rather than correcting the various issues on a regular basis. 

RPA has had a major impact on the daily operations of a supply chain system with its productivity increasing many folds in recent times. If you intend to choose a supply chain management course with analytics, having a general idea about its impact will be beneficial. 

Pros and Cons of RPA in the SCM industry

It has not been long since RPA was used in SCM so it may not be time to judge it to be a good or bad move. But it has been in use for a while to see what are its advantages and drawbacks.

Benefits of RPA in SCM

  • Order processing and payment

Processing the orders and tracking the payments are some of the most difficult tasks in the supply chain system. But automating both of these, companies can save time and effort while making it simple for the customers or the company to keep track. The automation includes timely processing of the orders and sending out bills through emails and text messages. 

  • Communications

It is important to keep track of the processes and inform the involved parties about the progress or delays concerning the shipments, etc. The automated email system sends out emails whenever an order is placed, the product is shipped, or out for delivery. Such automation makes the system transparent and reliable. 

  • Inventory management

Every certificate course in supply chain management teaches that this is the most important department of the supply chain. Inventory management is a major part of the supply chain and by automating this department, companies can ensure the balance of supply and demand. The automated system can send notifications for low levels of stock and reordering processes. It could also use historical data to predict the inventory levels depending on the demand. 

  • Shipment status

 Communication of the shipment status could be completely automated right from the opening line of the email to assessing what the customer expects from such communication. Sending out the regular updates of the shipment is one such example and it will require minimal human intervention and only on some rare occasions.

  • Supply and demand planning

RPA helps gather, compile, analyze, and present the data for the regular planning for supply according to the demand. By using AI and ML, reduces common human errors and makes the system more efficient. 

Drawbacks of RPA in SCM

Rather than considering it as a drawback it would be better seen as a challenge that could have a solution in the near future. The common issues with RPA in SCM are 

  • Standardizing the processes even with proper documentation
  • Need for constant IT support
  • Keeping up with the expectations of stakeholders and gaining their trust to implement the RPA system
  • Engaging the employees and making them accept the system 

Conclusion

The world is moving forward with technological advancements so every industry must keep up with these changes. The SCM system requires professionals having such advanced skills and that is the reason why one should opt for the supply chain management online course such as the Professional Certification In Supply Chain Management & Analytics at Imarticus.

It will help you be a supply chain manager who has a thorough knowledge of the latest developments in this system. 

5 NLP techniques every data scientist should know

Posted on by Imarticus Learning

Have you ever wanted to master NLP? If so, I have five techniques that will change your life! In the last few decades, computers able to understand and process natural language. As a result, many new applications can leverage this technology for more accurate processing of text data.

One of these is Natural Language Processing (NLP). NLP has become an essential part of our lives as it allows us to talk with machines in a way they understand. This blog post will discuss five NLP techniques every data scientist should know. 

1) Tokenization: 

  • A technique that breaks up sentences into individual words or word tokens. 
  • It is the first step in text processing as it gives us a way to deal with each word individually. 
  • Tokenization is either done by splitting up an input string into words or groups of the word. Depending on the application, you might choose one over the other. 
  • For example, splitting words would be the best approach to find new misspelled versions of a known word. 

2) Stemming: 

  • Stemming is a method that reduces words to their root. It allows us to deal with variations of a comment by using its root form instead. 
  • For example, “running,” “runs,” and “ran” would all be reduced to the stem word “run.” Stemming algorithms share the same purpose: to remove the grammatical additions of words to get their root form. 
  • It allows for automatic text simplification, which is essential when condensing the input data into a single searchable string.

3) Lemmatization: 

  • Lemmatization is a process that reduces inflected words to their base or dictionary form. 
  • For example, reduction of “walked,” “walking,” and “walk” to the root word walk.
  • Lemmatization is stemming done right. Stemming reduces words to their root forms, but it does not take into account morphological rules. On the other hand, Lemmatization builds up word knowledge, which allows for base or uninflected word matching.

4) Keywords Extraction: 

  • This process finds the most important words when applied to text, phrases, or sentences. 
  • Keywords extraction means finding essential words in a given sentence, and this gets done by using TF-IDF (Term Frequency-Inverse Document Frequency).

5) Sentimental Analysis: 

  • Sentiment analysis is a text mining technique that has applications in many fields. 
  • It can also be helpful when building chatbots as word sentiment can give us an idea of what the user is saying. 
  • Sentimental Analysis helps identify emotional, social, or opinionated aspects within written language.

Explore and Learn Data Science with Imarticus Learning

Our Data Science course details include Capstone Initiatives, real-world business projects, relevant case studies, and mentorship from industry leaders who matter to help students become experienced Data Scientists.

Some course USP:

  • This data science course in India aid the students in learning job-relevant skills.
  • Impress employers & showcase skills with the certification of data science endorsed by India’s most prestigious academic collaborations.
  • World-Class Academic Professors to learn from through live online sessions and discussions.

Contact us through the chat support system or visit Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon training centers.

Why embodied learning is essential to careers in artificial intelligence

Posted on by Imarticus Learning

Technology is now instrumental in every business process and artificial intelligence is the newest tool that companies are trying to implement. Therefore, there is a vast scope for jobs in the field. However, for a career in artificial intelligence, you need to invest in learning about the discipline. Embodied learning or learning that involves both the body and the mind, is crucial in an artificial intelligence course.

This is because the field of artificial intelligence is developed by closely observing and replicating human behavior. If you are looking for such a program that will help you focus on a career, you can choose Imarticus Learning’s AIML course. This course involves the best learning methods and an industry-oriented curriculum to provide the necessary training. 

How Can Embodied Learning Help in an Artificial Intelligence Career? 

If you wish to learn AI and establish a career in that field, you need to invest in the process of embodied learning. This is particularly because embodied artificial intelligence is developing quickly. According to Linda Smith’s 2005 hypothesis, intelligence is a reaction to or a product of the sensorimotor activity, and it is born out of the interaction between the environment and an agent.

While this is true in terms of human intelligence and cognitive function, it is also true for artificial intelligence, which at the most basic level mimics human behavior in a faster and more error-free space. 

Embodied learning is crucial for artificial intelligence because it helps to focus on data or metrics that are generated from a human perspective. Thus, there is a greater chance for that data to be accurate once it is implemented to optimize various processes.

When you participate in embodied learning, you are able to appreciate where artificial intelligence draws from and why it is essential to understand human cognition. Once you become a professional in the field, this same training will prepare you to combine computer vision, Internet AI, and Natural Language Processing to generate outcomes that are more closely related to human patterns. Such AI solutions will therefore have more potential to positively impact the business processes. 

Why is Imarticus Learning a Good Choice for a Career in Artificial Intelligence? 

To participate in embodied learning and to have a better understanding of what embodied artificial intelligence is, you can opt for Imarticus Learning’s certificate course in Artificial Intelligence and Machine Learning. This AI certification program is for students who have completed their Bachelor’s or Master’s in statistics, mathematics, economics, computer science, engineering, or science and have a minimum of 50% in graduation.

If you are eligible you can enroll in our Artificial Intelligence and Machine Learning certificate course. The mode of learning for this training is online and it is done through live lectures so that you can learn, interact and build contacts with academicians and industry professionals.

We have collaborated with the E&ICT Academy and IIT Guwahati to create the course curriculum. Therefore, you will be learning from the best academicians in the field and they will be able to give you a holistic education in embodied artificial intelligence.

You will also be receiving industry certification which will prepare you for interviews with renowned companies in the industry. We at Imarticus Learning ensure hands-on training and experience for all our students. Once you enroll in the Artificial Intelligence and Machine Learning course, you will be able to sit for live lectures every week.

The lectures are held for 8 hours each week and you can interact with your teachers, guest lecturers, and peers. Such interactions will help you develop a complete understanding of embodied learning and its implementation in the field of artificial intelligence.  

The practical training and experience portion of our program is offered through project work and assignments. You will get to participate in 25 industry-related projects and focus on assignments that deal with real-world issues. This will prepare you for the current industry and help you become the best potential employee possible.

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