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Category: Management

IIT Roorkee: Changing The Face of The Supply Chain Management Industry in 2022

Posted on by Imarticus Learning

IIT Roorkee: Changing The Face of The Supply Chain Management Industry in 2022

Supply Chain Management (SCM) is sequentially connected activities that aim to fulfil the demand (product or service) of a client. There are several stakeholders in this process, namely the vendors, manufacturers, whole-sellers, dealers and retailers. All these stakeholders are connected by the most important stakeholder, who is the Logistics Partner. Supply chain management activities essentially involve the flow of information and product or services through several complex networking.

How to Get Started in This Career?

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After completing the UG course in any field, a prospective candidate may enrol himself/herself in a reputed institute. These renowned institutions will pave the path to an excellent supply chain management career. They also provide certifications for supply chain professionals. A prospective candidate must possess the basic aptitude for learning business processes and preferably should have mathematics as one of the subjects in the UG course. Business management, institutional behaviour and management principles, corporate communication, human resource management, statistics and economics are the core subjects that are to be taught in the post-graduate diploma certification courses for supply chain management. 

Several elective subjects are also available to choose from. These include principles of supply chain management and logistics, product and brand management, inventory and warehouse management and international trade and operations.

The Changing Face of Supply Chain Management 

Nowadays, clients have become more demanding than ever, both in terms of quality and promptness in service. To get these on the table, they are even ready to pay a reasonable premium. The spree of purchasing, particularly in the retail sector, has gone up considerably. The purchasing power of an average Indian in a middle-class family has also increased. The supplier-customer relationship in 2022 is not the same as it was a decade back. The concept of supply chain management has transformed enormously throughout the past decade. Previously, the general idea was to consider it as a mere procurement department. In today’s world, supply chain management has taken over marketing or business management, which organisations practised lately a decade back.  

The pandemic has changed our lives forever. Though online shopping was already practised earlier, it became multi-fold during and after the pandemic era. Nowadays, with the introduction of data science and artificial intelligence into the operating system, the organisation gets rated for the product or service it sells. Such ratings depend not only on the quality of the product but also on its payment process, packaging, delivery time and return policy among other points. All these processes are essentially part and parcel of supply chain management. These ratings by customers become a guiding manual for prospective clients, who wish to go for the same or similar products or services. Thus, sellers cannot remain complacent by only maintaining the quality of the product through stringent checks on their vendors; but also, they should have strong and efficient supply chain management and logistics networking so that they may score high in the rating procedure. In fact, in today’s time, those companies are perceived in a good light whose supply chain management is up to the mark.   

New Challenges

There is no denying that the changing demand of customers has paved the way for the rapid transformation of supply chain management and added to its growth trajectory in a significant way. However, all these do not come without their set of challenges, which are new and dynamic, as well. The organisation sometimes fails to make it to a win-win situation in spite of having the best vendors with a strong operation and logistics team. The devil to this effect is the lack of seamless coordination between the different stakeholders in the whole process. Communication within the planning and execution departments within the same organisation gets tricky at times and results in poor results at the bottom line. The correct inventory management by the manufacturers is also a high-risk affair. The inventory should not be too high so that it keeps waiting for a long time to find a taker. It should not also be too low so that a prospective client is directed towards a competitor. De-risking hazards and price volatility are genuine concerns for organisations. 

The Way Ahead

In order to take stock of the situation, organisations must make good use of the history data or past feedback information efficiently to plan their inventory, both for the raw material and the finished goods. Through these data, the organisation may also record the pattern change in demand. So, they may even decide to discontinue a product or a service that the clients do not wish to have anymore.  

Conclusion

As a profession, supply chain management aspirants may surely expect a rewarding career and sustainable growth in the long term. Candidates may even choose to be a Business Analyst and support the overall supply chain management system. The IIT Roorkee supply chain management course at Imarticus is an online course. This course will help you to make a successful career in this field. 

How to pick from myriads of online AI courses

Posted on by Imarticus Learning

As natives of the advanced technological world, we should be aware of all its essential as well as developing features. Adapting to the constant tech-upgrade is very crucial for a smooth transition of lifestyle. Artificial Intelligence is one of the most innovative technologies that has been created to influence our lives. To provide us with better security and comfort, AI has surely changed our lives. This is why it is important for developers and designers to take the AI and Machine Learning course, which will help them understand this concept better.

What is Artificial Intelligence?

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Artificial Intelligence constitutes sets of algorithms which can read data activities and generate efficient automated results. They do not need human interference, inputs or any manipulation. Unlike before, where even a calculation from a calculator was considered to be a feature of AI, it has a different meaning now. It is divided into three parts. They are:

Artificial General Intelligence

It is one of the strongest AI categories. Most people are familiar with this feature of AI. It impersonates the human level of intelligence. Various smartphones have the characteristics of speech recognition, face recognition, etc. That is done by AI. Although it has been well-developed, there are a lot of things that still need more updates here.

Artificial Narrow Intelligence

It is considered to be weaker among the three categories. It mostly focuses on the completion of tasks and fulfilling their purpose. Features such as Alexa, Siri, etc., that are present in various electronic devices are a part of this AI category. Machine learning is important to carry out these functions. It caters to providing solutions to problems one at a time. 

Artificial Super Intelligence

This category is more attributed to future achievements. When machines and robots will be able to have emotions, express their opinions, do art, perform sports, etc. This category allows space for innovation and development.

Things That You Must Keep in Mind While Selecting the Right AI Online Course

  • Knowledge of Data Engineering

An Artificial Intelligence course and a Machine Learning course go hand in hand. In order to learn data engineering, you must be well accustomed to Machine Learning. This skill is crucial as it allows developers to store and pre-process raw data. In order to process any website or server tasks the operator needs to have various commands ready for the next step. When a customer clicks on the purchase tab, a new set of data is generated. The process of Extract, Transform, and Load (ETL) takes place, which is crucial to access further steps. While learning about data engineering, you need to have a great understanding of statistics, analytics, predictions, commands, etc. 

  • Programming languages

In order to comprehend and make changes in the system, you need to have the right knowledge of the language of machine learning. Programming languages will help you input commands that are comprehended by the machine and then carried out as per your direction. Following is the list of programming languages that you should be learning. (It is not compulsory to learn them all but a few essential ones must be well understood.)

  1. Python
  2. Scala
  3. Java
  4. C++
  5. JavaScript
  6. Go
  7. Ruby
  8. Clojure
  9. Erlang
  10. Perl

  • Understanding of Data Analysis

As an Artificial Intelligence learner, it is crucial for you to have a good understanding of data analysis. Since you will be surrounded by huge loads of data sets, you need to know how to dissect and analyse them. It will help you observe different patterns of data used as well as help in the identification of anomalies which will in turn help to analyse hypotheses. You should be able to do the following:

  1. Be able to calculate data that are presented in rows and columns. You should be able to calculate the minimum and maximum values, overall percentage, column mean and standard deviation. 
  2. Be able to erase unnecessary outliners from the data as well as any correlatable variables.
  3. Be able to create graphs for a better visual representation of the data.

  • Ability to execute Data Modelling

It is important for you to learn Machine Learning algorithms in your AI and Machine Learning course. Knowing about your machine’s ability to create algorithms is just one part of the process. You need to be able to use it and create data models for accurate executions.

If your data sets have a series of inputs and outputs, you need to create a data model which defines the relationship between the two. If your data entry only consists of inputs then you need to identify the existing pattern used in it and categorise it under a group of similarities and dissimilarities. Therefore, you need to be quite familiar with all the machine learning algorithms. 

Conclusion

It is a hectic task to find the perfect place where you can put your trust in for being trained at your utmost abilities. While searching for the perfect course to learn Artificial Intelligence you must be thinking of an IIT AI ML course but we have better options for you. Imarticus offers the best certification in Artificial Intelligence and Machine Learning for your data science career. You should put your faith in these experienced professionals. 

A practical guide for deep learning in 2022

Posted on by Imarticus Learning

We usually encounter e-commerce sites and web portals that have products we’ve wanted but never found, or one of our favorite songs appears on a Spotify playlist or YouTube video unintentionally. All this is possible through deep learning in action in the back end. Deep learning is driving the smartness of the future of business, which is a strong branch of the machine learning domain we dream of learning about.

Let’s explore ways to get on the right path to mastering deep learning skills.

Deep Learning

Deep Learning (DL) – A subset of machine learning for robotic decision-making operations and the ability to make predictions by learning situations. Artificial neural networks drive deep learning systems. The DL works the same way the human brain works in the learning process. Artificial neural networks learn from data without being explicitly programmed. In short, Deep Learning is used to develop models that will sense patterns in data and help in predicting the most accurate result.

Deep Learning trend

Moving to online platforms is the current industry trend. The transition enhances transparency and provides stakeholders with access to organizational information. This will result in a large amount of data. This data has inherited intelligence that is suitable to be used in deep learning systems. The DL systems, therefore, can derive scalable and adaptable insights for businesses. These solutions are reasonable and help in real-time information processing, enabling businesses to make informed decisions.

The global deep-learning market is expected to grow substantially over the next five years. A published report titled “Deep Learning Market Size, Share, Analysis Report and Region Forecast, 2022 – 2030,” published by Acumen Research and Consulting, predicts that the adoption of big data analytics will increase the deep learning market size by 51.1% CAGR to USD 415 billion by 2030.

Deep learning is developing rapidly and is poised to bring impressive advances in the field of data science. Deep learning is making amazing progress in the field of natural language processing and image recognition. Going forward, DL will help build more accurate models to predict outcomes and determine appropriate actions. Deep learning has a profound impact on how we use AI and machine learning in the real world. How businesses use AI and its scope in their applications will continue to change in the coming years.

DL does not require coding

Deep learning is effective in uncovering patterns from data. Instead of coding for software programs aimed at solving problems, with machine learning, we develop systems that learn from a set of examples in data to solve the problem. It is, therefore, the learning process that allows algorithms to improve over time and become more accurate. With the learned memory and set of rules, the DL systems get smarter when following the strict instructions fed to the model.

Taking note of DL Trends in 2022

To explore the DL domain, we first need to learn the basic concepts of data science and machine learning. The deep learning trends in 2022 will help us keep abreast with the market demands.

NLP Enhancements – Deep learning algorithms have significantly improved Natural Language Processing (NLP). Corrections are made to help better understand the meaning of words and phrases. Contextual meaning is also provided. Overall, better machine translation and information retrieval are now possible.

Predictive modeling evolved to prescriptive action – Previously, predictive models were often based on shallow ML algorithms that had difficulty learning from high-dimensional data. As predictive modeling has become more accurate, now, DL algorithms can learn from data with multiple features, making them more accurate.

Additional DL Architectures and Algorithms – Deep Belief Networks (DBNs) have been introduced to address some of the challenges facing deep learning. Slow performance and difficulty with large data sets are now addressed. DBNs are designed as multiple layers of neural networks that are constrained to communicate within their layer or horizontally.

Accessibility – Deep learning algorithms were seen as complex and difficult to understand by non-data engineers and were made more accessible. Additional tools and add-on services, such as DALL•E 2 from OpenAI, now facilitate the development of DL models. Reuse of models is possible for different use cases, limiting specific resource requirements.

Scaled-up DL Models – The capacity of deep learning models has been increased in terms of size and manipulation complexity. Added layers and nodes in the DL model will help improve the accuracy and speed with which deep learning models can learn.

Learning Data Science

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Most technical graduates and early career professionals are attracted to step into the data science domain.

Those interested in a data science career are expected to train in one of the prestigious programs. Choosing the right path, such as a deep learning course, will help us gain expertise in machine learning and data science.

The most popular programs offered by Imarticus Learning are the PG Program in Data Analytics &  Machine Learning. It is a specialized data analytics course that assures the participants of a definite career in data analytics.

Conclusion 

Taking the most beneficial Deep Learning Course can provide the necessary education to help develop real-world applications of data science.

Please contact Imarticus Learning to get more information on data science and analytics courses. One can also reach Imarticus through live chat or by simply sending a message, or by visiting the nearest training centers located in major cities like Pune, Mumbai, Thane, Gurgaon, Delhi, Bangalore, Chennai, and Ahmedabad.

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Natural Language Processing Course in India

Posted on by Imarticus Learning

Natural Language Processing Course in India

If you want to expand your expertise in natural language processing (NLP), a course in India can be a great way to do so. NLP is the process of teaching computers how to interpret, analyze, and understand human language. 

As this technology is becoming increasingly important for improving our interactions with machines and understanding human language’s complexities, understanding its applications is essential. 

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This blog will provide an overview of what an NLP course in India looks like and why it benefits those interested in pursuing this field. 

What Does an NLP Course Entail? 

A natural language processing course in India typically covers basic concepts such as syntax and semantics, machine learning algorithms for text analysis, and natural language processing techniques used for text mining and information retrieval. 

Students will also learn about the fundamentals of artificial intelligence (AI), deep learning algorithms, natural language generation techniques, and speech recognition systems. 

The course may also cover chatbot development, automatic summarization techniques, sentiment analysis tools, text-to-speech systems, question-answering systems, and more. 

Why Should You Take An NLP Course? 

 This course provides students with a comprehensive understanding of how these technologies work together to improve our interactions with digital devices and make sense of large amounts of data. 

Additionally, you will be able to develop your skillset by gaining experience working on projects related to natural language processing. This can help open up opportunities within the tech industry or become a stepping stone if you want to start your own business using these technologies. 

Some of the most exciting applications of NLP 

  • Speech Recognition/Synthesis 

One of the most common uses of NLP is speech recognition or synthesis. Speech recognition is when a computer can take spoken words as input and convert them into text or digital formats. 

Examples include dictation software like Dragon NaturallySpeaking and voice-activated virtual assistants like Amazon Alexa or Apple Siri. Speech synthesis is when a computer takes text as input and converts it into spoken words. 

Text-to-speech software such as Google Translate can generate human-like voices from written text in various languages. 

Speech recognition and synthesis have become increasingly important tools for accessibility, allowing people who are visually impaired or deaf to interact with technology in ways that were not possible before. 

This technology has also opened up new business possibilities, such as contact centers accepting voice commands from customers over the phone or automated customer service agents providing timely responses to customer inquiries via voice chatbots. 

  • Natural Language Understanding (NLU) 

Natural language understanding (NLU) is a field within NLP that focuses on enabling computers to interpret meaning from natural language inputs such as text or speech. NLU algorithms allow machines to understand the context behind spoken words so they can accurately respond with relevant answers. 

NLU is becoming increasingly important in fields such as healthcare, where accurate interpretation of medical reports is critical to patient care decisions; finance, where banks need accurate interpretation of financial news to make informed investment decisions; and law, where lawyers need access to correct legal documentation at all times to provide quality legal advice quickly. 

You will gain valuable insight into how these technologies work together and develop skills that could lead to exciting opportunities within the tech industry or even start your own business focused on AI-based products or services. 

So if you’re interested in furthering your understanding of human language or want to become part of this rapidly growing field – taking an NLP course might be the perfect place to start!

Explore PG in Data Analytics with Imarticus Learning

Imarticus Learning offers a comprehensive data science course with placement. With our experienced instructors and interactive lessons, you will learn Python programming fundamentals quickly. Our course covers everything from basic Python concepts to advanced data analysis techniques, giving you valuable insights into data science and analytics.

Course Benefits for Students:

  • Students can learn data analytics online without leaving their home comfort.
  • Gain hands-on experience with data science and analytics codes.
  • PG in data analytics certification provides learners the complete theoretical and practical knowledge of data analytics.

Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or contact us via the chat support system.

Is an engineering background essential to becoming a data scientist?

Posted on by Imarticus Learning

Data science is one of the most popular career options at present. It is one of the rare fields that offer a combination of both exciting and challenging job profiles. What is best about data science is that it does not restrict. Whether you’re from a science, commerce, or arts background, if you’re good at programming and statistics, you can become a data scientist.

Now coming to the big question, is an engineering background essential for becoming a data scientist? The answer is no, it is not at all necessary to have an engineering background if you want to be a data scientist. 

Although being from a technical background gives a lot of edges, this job profile doesn’t necessarily ask for a degree from a particular stream, be it engineering or some other. Instead, data science recruiters always look for candidates which have strong problem-solving and analytical skills along with a good knowledge of programming languages such as R, Python, Java, AWS, etc. 

How to Become a Data Scientist Without Engineering? 

If you’re not from an engineering background and want to pursue a career in data science, then it is definitely possible to do so. The job of a data scientist doesn’t discriminate on the basis of educational background and degrees that one has. In fact, an engineering degree is of no relevance in the field of data science unless it is computer science. 

Below are some tips that will help you set your foot in the data science industry and build a successful data scientist career:

Have a Basic Understanding 

The very thing you should do is have a basic knowledge of what exactly is data science, what skills it requires, and what job profiles it offers. Here are some common streams in data science:

  • Business Analyst 
  • Data Analyst 
  • Data Engineering 
  • MIS Reporting Executive 

A good idea is to learn about all the job roles and profiles in this sector and then try to figure out what roles you’re interested in. It is recommended to have a clear mindset of the industry or business sector that you want to work with, especially when you don’t belong to a technical background. 

Learn Programming Languages and Mathematics 

When you finally decide to switch your career path, then the first skills you need to acquire to become a data scientist include programming languages and mathematics. 

If you haven’t done engineering, then learning mathematics and programming languages can sound a bit tough at first, but always remember that nothing is too difficult to learn. You can easily gain these skills with practice and the right guidance. 

Programming languages such as Python, SQL, R, etc. are the prerequisites in data science. And believe it or not, these languages are much more comfortable and easier to learn than other languages like Java, C, and C++.

However, remember that learning only the programming languages is not enough. You also have to brush up on your mathematics and learn statistics very thoroughly. 

Take Data Scientist Course 

If you don’t know where to get started, then the best option is to take the right data scientist course. The best course from a reputed institute can help you learn data science online in the most effective and convenient way. 

Practice with Real-world Projects 

Once you’ve enough knowledge of mathematics and programming, you need to start practicing with real-world projects to enhance your practical knowledge. Always remember, data science doesn’t require any bookish knowledge, it requires the candidates to be exceptional at problem-solving, instead. 

Working on real projects not only helps you gain more expertise but also helps you build a strong portfolio to get a good job. 

Be a Part of the Data Science Community

Always keep looking for conferences, events, and summits related to data science. By attending these events, you get a great chance to network along with an opportunity to learn more about the field. Not just offline, you can join such events online as well. Furthermore, for networking, a good idea is to stay active on platforms like LinkedIn. 

Finally, Prepare to Face the Interviews

Once you’ve understood data science, acquired the right skills, and taken the right course, you can start applying for data science jobs and prepare for the interviews. Build your resume, write cover letters, and start contacting the network you’ve built by highlighting the projects you’ve worked upon. 

Conclusion

Is an engineering degree necessary for becoming a data scientist? The short answer is, NO! 

Anyone from any field, be it science, commerce, or arts can become a data scientist. More than the educational background and degree, data science recruiters look for the right skills such as programming and mathematics. By gaining great proficiency in these skills, you can definitely build a successful data scientist career. We hope the information provided in this article helps you in taking the right direction! 

The best Python online course for beginners

Posted on by Imarticus Learning

No doubt that Python programming is gaining tremendous popularity, and it’s no surprise that more and more people are searching for the best way to learn Python online. Python is a highly versatile language that can be used for data science and analytics, web development, game development, and more.

For those who are new to Python programming, an online course is an ideal way to learn! By signing up for a comprehensive online data science and analytics course or Python course, you can learn the fundamentals of the language without ever having to leave your home or office.

In this post, we will discuss the rise of Python programming. We will also cover some of the benefits of learning Python and how this language can help you in your career choice.

The rise of Python programming

Python programming is quickly becoming a must-have skill set for data science and analytics jobs. Companies are looking for developers who have experience manipulating data and creating meaningful insights from data sets. And in order to learn the skills required for these jobs, programming knowledge is essential.

Not only is Python an excellent language to learn for data-related tasks, but it’s also becoming increasingly popular with web developers due to its simple syntax and readability. As a result, many tech companies are investing in Python courses and tutorials to ensure their employees have the necessary skills.

Benefits of learning Python

Python programming offers numerous benefits when compared to other languages. 

Here are 7 of the most notable advantages of learning Python:

  • Easy to learn and use – Python is an ideal language for starters because it is easy to learn and use. It has a simple syntax that makes coding fun and intuitive.
  • Highly versatile – Python can be used for almost any project, from web development to data science and analytics.
  • Scalable – As your projects grow in complexity, you can easily scale up your code using the powerful features of Python programming.
  • Flexible – The language is flexible enough to make changes without any need to rewrite the entire program from scratch.
  • Portable – The same code can be used on various machines, making Python portable.
  • Open source – Python is open source, meaning the code is free to use, modify, and distribute.
  • Supported by a large community – With a massive online community of users and developers offering support, it’s easier than ever to learn Python programming and find help when you need it!

How can it help you in your career?

Python programming is an incredibly useful skill for data scientists, web developers, and software engineers. It’s a highly versatile language that can be used to create powerful programs and applications.

Those with knowledge of Python programming can easily learn the fundamentals of data science and analytics as well as web development. This skill set will open up new career opportunities in a variety of industries and help you stand out amongst your peers.

By learning Python online through an interactive course, you will gain valuable knowledge that will help you succeed in the modern tech industry. The best part is that you don’t need to leave your home comfort to learn this powerful language! With the right online course, you can learn Python wherever or whenever you like.

So, Start your journey today by signing up for the best Python online course for beginners!

Explore Data science and analytics course with Imarticus Learning

Imarticus Learning offers a comprehensive data science and analytics certification course. With our experienced instructors and interactive lessons, you will learn the fundamentals of Python programming in no time. Our course covers everything from basic Python concepts to advanced data analysis techniques, giving you valuable insights into the world of data science and analytics.

Course Benefits for Students:

  • Students can learn Python online without leaving their home comfort.
  • Gain hands-on experience with data science and analytics codes.
  • PG in data analytics certification provides learners the complete theoretical and practical knowledge of data analytics.

Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or get in touch via the chat support system.

The evolution of Machine Learning courses in 2022

Posted on by Imarticus Learning

Machine Learning is a field of study that involves using data for automating various tasks and improving the efficiency of systems or machines. It is identified as a component of artificial intelligence. Machine Learning algorithms can develop a model based on sample data, called training data for making decisions. These algorithms also help in predicting an outcome without being exclusively dedicated to doing so. Machine Learning algorithms are used in various applications like email filtering, computer vision, and medicine where creating traditional algorithms for performing the required tasks seems challenging. We are here with this IIT AIML course that can help you in taking a huge step closer to your dream career. 

Importance of Machine Learning

The main importance of Machine Learning is that it helps enterprises visualise the patterns of business operation and customer behaviour. It also helps in developing new products. Many reputed companies like Google, Uber, and Facebook have made machine learning an integral part of their operational wing. Machine learning has also become a major differentiating point for several companies with their counterparts. 

What are the Different Types of Machine Learning? 

Conventional machine learning is often determined by how an algorithm achieves higher accuracy in its predictions. There are four major approaches namely, Unsupervised Learning, Supervised Learning, Reinforcement Learning, and Semi-supervised Learning. Data scientists have to choose a suitable algorithm type based on the type of data that they predict. 

  • Unsupervised Learning: This is a type of machine learning involving algorithms that work in unlabelled data. The algorithm scans data sets searching for a useful connection. These algorithms can help in predetermining the output of these predictions.
  • Supervised Learning: In this category, data scientists provide algorithms with determined training data and assess the variables which have to be checked for correlations. Both the input and output of the algorithm are mentioned here.
  • Reinforcement Learning: Data Scientists mostly use this type of machine learning to help a machine learn how to complete a process that involves multiple steps and pre-defined rules. Data scientists create an algorithm to accomplish a task and provide positive or negative prompts on completing a specific task. Mostly, the algorithm on itself can decide what steps must be taken along the way.
  • Semi-supervised Learning: This type of machine learning is a combination of two supervised learning and unsupervised learning. Data scientists mostly feed only labeled training data in algorithms but the model can freely investigate data by itself and create its apprehension of the data set. 

About this Artificial Intelligence and Machine Learning Certification Programme 

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This certificate program in Artificial Intelligence and Machine Learning is one of the best machine learning courses you can go for. There are numerous advantages to enrolling in this program. It has been introduced in partnership with E&ICT Academy IIT Guwahati and industry giants to deliver effective learning to those who want to build a career in Artificial Intelligence and Machine Learning. It is a 9-month long program that prepares you for high-paid job profiles like Machine Learning Engineer, Data Scientist, AI Engineer, and Data Analyst. 

This course can effectively boost your basic concepts and skills in Machine Learning and Artificial Intelligence. Get benefits from our Expert Mentorship service and acquire hands-on experience working with real-world projects. Many realistic projects from different industries have been added to the curriculum to strengthen your knowledge and guide you on how to implement your skills practically. Not just that, but this course can also take you a long way in grabbing profitable career opportunities in all fields related to Machine Learning and Artificial Intelligence. 

Why Should You Enrol in This Programme? 

If you’re interested in Data Science, you need to learn Machine Learning thoroughly as it is an important tool used in data science. However, if you’re still not sure about why you should enrol for this artificial intelligence certification course, here are some major highlights of this program for you: 

  • World-class academic faculty 

By enrolling in this program, you can learn machine learning from top-rated faculty in India as they content group discussions and live online classes. These sessions also help you in improving your basic concepts of Data Science and industry giants will guide you on the practical use of Machine Learning techniques through various projects. 

  • Flexible learning 

The curriculum of this course has been designed based on NEP 2020 and it ensures to give a lot of flexibility for the students. You can transfer the program credits for 1 year. 

  • Acquire job-required skills 

Lastly, this program helps you in acquiring skills that are in great demand and are required by every aspirant of Data Science. 

Conclusion 

That’s all you need to know about our certification program in Machine Learning and Artificial Intelligence. There are so many remarkable aspects of this program that make it highly useful for all those who are willing to build their career in Data Science. This program can only help you in learning the concepts of Machine Learning but it covers all the relevant fields. This, in turn, prepares you for all job opportunities related to the field of Data Science. 

Getting a Certification In AI? Here’s What You Need to Know

Posted on by Imarticus Learning

It is a commonly known fact that the popularity of artificial intelligence and machine learning courses is gaining pace with each passing day. Thanks to the interest of people in this field and the necessary impetus by the education sector in India, AI and ML courses are available at almost every technological institution in India. 

Resultantly, students, especially if they are from the Computer Science or Computer Applications stream, are leaning towards AI certification because of the rich pool of jobs in this sector.

Before enrolling in a course in artificial intelligence and machine learning, you need to be aware of some trends in this sector. They will help you make the right decision and choose a course that suits your requirements.

5 points to know about AI and ML certification

Here are 5 points that you should keep in mind when looking for a course in AI and ML –

Python is the predominant language in AI and ML

In an artificial intelligence and machine learning course, Python is the only language you need to master. So if you have a background in C, C++ or Java, then you need to add one more programming language to your list. Don’t worry; the basics of all these languages are the same, with some minor differences in syntax and some concepts. If you have a programming background, then you will pick it up easily, and with regular practice, you will master it.

Knowing Mathematics and Statistics is important for AI and ML

An extensive knowledge of various mathematical concepts like Linear Algebra, Calculus and Probability is required for a student to know. They also need to know the in-depth concept of statistics like accuracy, precision, correlation, recall, variance, f-score, simple linear regression, root mean squared error and basic hypothesis testing like p-values and test statistics.  

There are multiple types of AI certifications that you can acquire

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You might get an AI certification majorly in two or three combinations. The first one could be an artificial intelligence and machine learning course. In this course, the focus could be to learn machine learning fundamentals like Python Programming, Supervised and Unsupervised learning. You also need to learn computer vision, natural language processing, speech and Neural Networks.

There is also the Artificial Intelligence and Data Science Certification. Although it could set you off in a different direction than expected, it is relevant to this field. It is more suited to people who would love to be involved in projects to extract insights. The third type, of course, could be AI and Analytics. However, it is a distant cousin of sorts. So, it makes no point in pursuing it.  

Capstone projects make all the difference while you are seeking a job  

Without a capstone project, an AI certification course is incomplete. It gives you a whiff of what you might have to face after you are hired as a professional in a company. Most employers love a job-ready employee, i.e. a professional who does not need to be trained.

It is illogical to think a student would be prepared for a job beforehand. But with the aid of these capstone projects, they get enough experience and skills to land a job. They are also aware of all challenges they would have to face when facing different real-life situations. They will have a problem-solving approach rather than being in panic mode. So the students will be mentally prepared beforehand.

Institution and certification matters

The biggest problem the students face when they are in AI and ML is that there is no dearth of colleges, universities and institutes that are offering it. There are even courses that are available online. Even the topmost software companies are offering it. Some of these are auditing courses, and others give you a certification.

But do they hold value? Will a student be able to gain the requisite knowledge and land a real-life job with these certifications? For that, we can only tell the institution’s reputation and credibility matter big time when it comes to the value of the certification. This is why Imarticus Learning has collaborated with E&ICT and IIT Guwahati to provide a certification course in AI and ML from the most prestigious technological institute in India. The course has substance and holds enough value to land you a job.

To sum up, these are some points you need to keep in mind while researching for an AI certification. It will help you make the final decision and select a course that will fit your career goals, ensuring success in the coming years.

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Learn supply-chain compliances and leverage a competitive advantage

Posted on by Imarticus Learning

Learn supply-chain compliances and leverage a competitive advantage

It’s no secret that supply-chain management is a complex and ever-changing field. With new regulations and standards being enacted all the time, it can be hard to keep up. But if you want your business to remain competitive, it’s important to stay on top of the latest changes. One area that has seen a lot of recent activity is supply-chain compliance. Understanding the various compliance requirements and how to meet them can give your business a significant advantage. In this blog post, we’ll look at some of the most important compliance issues to be aware of and how you can ensure your supply chain is up to date.

Significance of Supply Chain Management for new-age businesses

The internet has disrupted nearly every industry, and the business world is no exception. In the past, businesses could get by with a linear supply chain, taking raw materials, turning them into products, and then selling them to customers.

However, the internet has made the world more connected than ever before, and customers now expect businesses to be able to meet their needs on a more personal level. This means that companies need to have a more complex and efficient supply chain to succeed.

Supply chain management coordinates all the different moving parts of a business’s supply chain to ensure everything runs smoothly. This includes everything from sourcing raw materials to manufacturing products to distributing them to customers.

There are many benefits of having a well-managed supply chain. Perhaps most importantly, it can help businesses save money. A well-run supply chain can source materials at the best possible price and then get them quickly and efficiently to where they need to go. Additionally, a well-managed supply chain can help businesses respond quickly to changes in customer demand.

In today’s business world, having a strong supply chain management strategy is essential for any company that wants to be successful. By taking the time to understand all the different aspects of supply chain management and putting together a solid plan, businesses can put themselves in a great position to succeed in the years ahead.

Leveraging competitive advantage through supply-chain management?

To leverage a competitive advantage through supply-chain management, businesses must ensure compliance with all relevant regulations. This includes rules governing the procurement of materials, the transportation of goods, and the disposal of waste. By complying with these regulations, businesses can avoid costly fines and penalties and improve their overall efficiency. In addition, by maintaining a compliant supply chain, businesses can build trust with their customers and partners, leading to improved relationships and increased sales.

What are the basic skills needed to be a Supply Chain Manager?

To be a successful supply chain manager, certain basic skills are needed. These include strong analytical and problem-solving abilities and good communication and interpersonal skills. The ability to effectively manage and motivate teams is also essential. Additionally, supply chain managers need to have a good understanding of technology and how it can be used to improve efficiency and effectiveness within the supply chain.

Learn and Grow with Iamrticus Learning:

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Future-proof your career new-age curriculum offered through professional certification in the supply chain & Analytics program from Imarticus Learning.

Industry leaders have designed this IIT Roorkee supply chain management course to provide a cutting-edge experience to candidates willing to make a career in operations and supply chain. The course makes you an expert in managing uncertainties in a Supply Chain system. 

Supply Chain Analytics enables management to make data-driven decisions at strategic, tactical, and operational levels.

Certifications for supply chain professionals are significant with increasing need for professionals with process and analytics skills. This course prepares you for high-demand job roles such as Data Scientist, Demand Planner, Supply and Operations Planner, and Supply Planner. 

Course USPs:

  • Learn in-demand tools and projects with six real-world projects.
  • Master new-age SCM and Analytics skills
  • Best trainers and faculty in India
  • Attend 1:1 mentoring sessions with industry stalwarts 

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

Want to master ML (machine learning) and AI to supercharge your career? Read on

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Want to master ML (machine learning) and AI to supercharge your career? Read on

Artificial intelligence (AI) and machine learning (ML) are the two hottest topics in the tech world. Companies like Google, Facebook, and Amazon are all investing heavily in these cutting-edge technologies, and they’re always searching for talented engineers who can help them push the envelope even further. If you’re looking to supercharge your career, mastering ML and AI is a great way to do it. Here’s what you need to know.

What are AI and Machine Learning?

Before we dive into how to master ML and AI, it’s essential to understand what these terms mean. 

Artificial intelligence is a broad field that deals with creating intelligent machines that can react and work like humans. This can be anything from teaching a computer how to play chess to building a self-driving car. 

On the other hand, machine learning (ML) is a subset of AI that allows computers to improve and learn from experience without being explicitly programmed. So instead of programming a computer to do something specific, you feed it data (known as “training data”), and it figures out how to do it. 

For example, if you wanted to build a system that could automatically identify cats in images, you would give it a bunch of images containing cats and images that don’t include cats. The ML algorithm would then learn from this training data and be able to identify cats in new images automatically. 

How to Become an AI/ML Expert?

 

  • Get a degree 

 

Although you don’t need a degree to get started in ML or AI, having one will give you a solid foundation of knowledge to build upon. Plus, degrees from top schools are highly respected by employers in the tech industry. If you’re unsure which route to take, consider getting a degree focusing on data science or artificial intelligence.

  • Take online courses from leading providers. 

There are many online courses available that can teach student’s the basics of machine learning and artificial intelligence. Courses from leading providers are respected by employers and will give you the necessary skills to get started in the field.

  • Participate in open-source projects. 

There are several ways to get involved in the machine learning and artificial intelligence community. You can join open-source projects, make contributions, or collaborate with others on their ideas – all of which will give you invaluable experience for your future career!

  • Stay up-to-date on the latest developments. 

Machine learning and AI constantly evolve, so staying updated on the latest developments is essential. Attend conferences, read blogs and whitepapers, and follow leaders on social media to ensure you’re always learning new things.

Following these four steps, you can master machine learning and artificial intelligence and embark on a rewarding career. With the right skills, you’ll be in high demand by businesses across all industries that are looking to harness the power of these transformative technologies. So what are you waiting for? Start learning today!

Discover IIT artificial intelligence course with Imarticus Learning

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Enroll in the AI and machine learning courses program at the E & ICT Academy to learn more about machine learning.

Course Benefits For Learners:

  • Students work on 25 real-world projects as part of the IIT AI ML course to gain practical business experience and prepare for a rewarding data science career. 
  • Students can grab employers’ attention and showcase their abilities with a certificate recognized by the E & ICT Academy, IIT Guwahati, and a credential supported by Imarticus Learning. 
  • Students who pass this deep learning certification may find lucrative employment in the artificial intelligence and machine learning fields.

Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or get in touch via a chat support system.

Get a free 1:1 Imarticus counselling
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