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Category: Management

Understanding Natural Language Processing In A Few Minutes

Posted on by Imarticus Learning

In the last few years, Natural Language Processing (NLP) has become the focus of Artificial Intelligence with the introduction of game-changing new applications and models. This article will also provide a brief on AI certification tests. So, keep reading to know more about the current rage.

Technically, Natural Language Processing (NLP) is the union of Artificial Intelligence (AI), Computer Science, and human language (Generally, English). It is the study through which you can teach computers how human beings inherently write, talk, and speak. 

Now that the technical definition is out there, what do we really mean by NLP, which forms an important part of AI and Machine Learning courses? 

Real-world Examples of NLP 

Without realizing it, you’ve come across NLP more often than you’d admit. The virtual assistants on your smartphones like Google Assistant and Siri are the most common examples of NLP. They carefully listen to what you say and process that information in a language intelligible to their systems. 

So, generally, NLP can be used for Voice Commands, Text-to-Speech, Chatbots, Search Engines, Language Translation, Sentiment Analysis, and Spelling Checks.

What is Natural Language Processing? 

Humans generally communicate with each other using natural language. Processing refers to the action of converting data into a form that can be easily understood by machines. Combining these two terms, we get Natural Language Processing which helps computers communicate with people in their natural language. 

How does NLP work? 

We use NLP software for pre-processing sentences in a natural language and structure that can be used for interpretation by machines. 

Must-know Terms in NLP 

Let us understand the most important concepts in NLP through the example of this sentence: “She doesn’t sing, but my son is a vocalist.”

  • Tokenization: In this process, a whole text is divided into tokens. A word tokenizer separates words, and the sentence tokenizer separates sentences. 

Example: Word-tokenize: “She”, “does”, “not”, “sing”, “but”, “my”, “son”, “is”, “a”, “vocalist”.

  • Stopwords: These words don’t add any meaning to the given sentence. The library “nltk.corpus” contains a list of stopwords. By importing this library, you can derive a sentence without stopwords. 

Example: Stopwords: “she”, “doesn’t”, “but”, “my”, “but”, “is”, “a”.

  • Part of Speech Tagging (POS Tagging): Here, the words are tagged based on the part of speech they represent. 

Example: 

  • She: Personal pronoun 
  • Does: Verb
  • Not: Negative particle 
  • Sing: Verb  
  • But: Conjunction
  • My: Possessive pronoun
  • Son: Noun
  • Is: Preposition
  • A: Article
  • Vocalist: Noun

  • Bag of Words: Once the sentence is cleaned, it’s converted into vectors (numerical representation) for feeding into the ML model. We do this using predefined python libraries.

  • Stemming: Here, the words are reduced to the root form. 

Example: In this sentence, only “does” is converted to “do.”

  • WordNet: This is the dictionary for English that is made for NLP. You can use it to find synonyms and antonyms.

  • Lemmatizer: It works similarly to stemming except for returning a word that makes sense. 

Example: 

  • Stemming: Vocalist – vocal
  • Lemmatizing: Vocalist – voice

Importance of NLP for AI Certification 

NLP is essential for AI as it makes human language legible for machines. This process helps in creating structured data for software performing text analytics, speech recognition, etc. 

About AI and Machine Learning Courses 

Imarticus Learning offers industry-ready AI Certification courses. To find out more, visit our centers in Mumbai, Pune, Jaipur, Delhi, Noida, Lucknow, Gurgaon, Chandigarh, Dubai, Patna, Bangalore, Chennai, and other places. 

Debate the usefulness of various tools in data analytics

Posted on by Imarticus Learning

To perform data analysis, professionals use tools & software that ensure the best results. There are many of them in the market, but a few are on the top list for data analysts that need to be chosen wisely to extract the best benefit. 

This article discovers the best data analyst tools and highlights key features of each based on different types of analysis processes. But first, here’s a basic definition & introduction.

What Are Data Analyst Tools?

Data analyst tools are applications & software that data analysts develop & perform analytical processes to make better, informed business decisions while keeping costs low & profits high.

Top Tools Used by Data Analysts?

1.) Business Intelligence Tools

BI tools are the most represented means to perform data analysis. Specialized in business analytics, they prove beneficial for every data analyst to monitor, analyze, and report essential findings. Self-service, advanced SQL modes and predictive analytics make them easily adjustable to every level of knowledge without immense IT involvement. 

DATAPINE covers most requirements of beginners & advanced users.

Key Features:

Visual drag-&-drop interface

Powerful predictive analytics & interactive charts & dashboards

Intelligent alarms triggered for anomaly

2.) Statistical Analysis Tools

There exist multiple programming languages that make work easier & effective. With the expansion of languages, some rules and scenarios need special attention for statistical data analysis & modeling.

R PROGRAMMING is the most popular tool for data analysts.

Key Features:

An ecosystem of more than 10k packages & extensions for data analysis

Statistical analysis, modeling, & hypothesis testing

The active community of researchers, statisticians, & scientists

3.) General-Purpose Programming Languages

Programming languages help to resolve a variety of data problems. Tools like C#, Java, PHP, Julia, Ruby, and Python are many reliable solutions.

PYTHON is the most trusted tool.

Key Features:

Open-source solution with simple coding processes

Easy integration with other languages

Advanced analysis processes through ML & text mining

4.) SQL Consoles

SQL is a programming language used to manage data held in relational databases, effectively handling structured data for analysts. Highly popular in the data science community, these tools are used in various business cases & data scenarios. 

MYSQL WORKBENCH is the most popular one.

Key Features:

  • Unified visual tool for data modeling, administration, SQL development, backup, etc.
  • Instant access to the database via Object Browser
  • SQL Editor offers color syntax highlighting, reuse of SQL snippets, & execution history

5.) Unique Predictive Analytics Tools

Predictive analytics is an advanced technique to combines data mining, AI/ML, and predictive modeling to predict future events. It is an essential data analysis tool as it simplifies predictive analytics processes. 

SAS FORECASTING is an analysis software helpful for predictive analytics processes & helps analysts to predict future scenarios.

Key Features:

  • Automatic forecasting for entities or products, including hierarchical forecasting
  • Scalability & modeling to create an ensemble
  • An unlimited model repository including time-series & casual methods

Apart from the tools mentioned above, there are industry-specific analytics tools & data science platforms that assist professionals. A business analytics course can help you better understand what data analytics is!

Build a New-Age Career with Imarticus:

Imarticus Learning offers Data Science Courses, the most extensive, industry-approved experiential learning program ideal for Data Analysts. Industry experts have developed the programs to help students learn real-world applications of Data Science from scratch & build robust models to generate valuable business insights and predictions. Take a giant career leap with this analytics program.

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

7 reasons why you must technologize supply chain using advanced analytics and AI

Posted on by Imarticus Learning

The supply channels of the industry are experiencing a crucial moment in their existence and those responsible for this vital area for any business face the greatest challenge of their careers; managing an innumerable list of suppliers, information and communication flows, technologies, procedures, and levels of demand, as never before in the history of the global industry.

These supply networks have grown in complexity appreciably and have suffered the consequences of the global economic crisis with particular virulence. To help you understand the importance of technologizing the supply chain using advanced analytics and AI, we offer an SCM program where you can obtain a certification in supply chain management. 

Here are 7 reasons why you must consider technologizing the supply chain using advanced analytics and AI: 

  • Agility is key to success, more than ever. Designing supply chain network systems must work like a clock, and take advantage of new technologies, such as IoT, Blockchain, or Artificial Intelligence, to reach new levels of efficiency.

  • Advanced analytics is another alternative high impact in this world, taking into account the permanent state of evolution and change network provision of any business. Evaluating the best options, those that provide the greatest value and margin, and taking advantage of all the data at our disposal has an immediate positive consequence on the results. Thankfully, our professional certification in supply chain management explains how advanced analytics is beneficial for the supply chain management.

  • The information must be analyzed comprehensively and quickly, with the powerful support of the cloud. Large corporations are moving quickly so that their supply chains are aligned more with your customer strategy, and are connected more directly, accurately, and flexibly. But, above all, an “always ON” supply chain is sought that responds to commercial needs at all times.

  • The interconnection of all its links is crucial for the machinery to function and respond to the demanding market conditions. Analyzing that information has profound implications for B2B processes. For this reason, one of the fundamental attributes of this supplier ecosystem is its “resilience”, understood as the ability to anticipate and react immediately to any potential anomaly that could endanger it.

  • Staying safe from the unexpected requires intelligent use of multiple data sources, new, traditional, structured or not, of diverse typology, even in natural language, and easy to find or obscure to the provider. And all of them must be leveraged by certification in supply chain management.

  • You need expert staff and precisely the links in the supply chain have long suffered thinning plans that have reduced their workforce like never before. And when older veterans leave the organization, they will carry with them a lot of knowledge and experiences that have been treasured for decades, with the consequent brake on exhaustive analyzes that require intelligence to interpret the information.

  • Designing a supply chain network with full intelligence is capable of managing in real-time large amounts of structured and unstructured data from internal and external sources, including data sets that may previously have been difficult to reach. Precisely anticipating future demand and managing assets, inventory, and shipments in real-time improve the bottom line for any operator, requiring an optimized, near-automatic supply model.

The new forms of commerce that have fostered the Internet, the cloud or connected objects will only gain shape if they have the most efficient logistics processes, a modern supply chain that meets their high demands with a permanent journey to excellence. Professional certification in supply chain management offered by Imarticus can lead to a truly digital supply chain. 

Machine Learning at work: The future of the workplace in 2022

Posted on by Imarticus Learning

Automated algorithms that learn from experience and data are known as machine learning (ML) algorithms. In order to generate predictions or judgments without being exclusively coded or overseen by humans, machine learning algorithms generate a model based on training data. The discipline of machine learning gains new techniques, theories, and application fields from mathematical optimization research. 

When it comes to machine learning, input such as training data or knowledge graphs is used in the same way that the human brain develops information and comprehension. Defining entities allows for deep learning. The Edutech industry nowadays is filled with Machine Learning and Artificial Intelligence courses.

There are several ways to start the machine learning process, such as through looking at examples, direct experience, or even teaching. Data is examined for patterns that may be used to draw conclusions from the instances given. With machine learning, computers can learn on their own, with no help from humans, and then modify their behavior as a result. 

Types of Machine Learning Algorithms

Machine Learning algorithms can be mainly distributed into three categories, they are:

  • Supervised Learning: Supervised machine learning systems use labeled samples to predict future occurrences based on what has been learned in the past. The learning technique uses a known training dataset to build an inferred function that predicts output values based on that dataset. After sufficient training, the system is capable of providing objectives for any new input. It is also capable of comparing the model’s output with the planned, proper output in order to identify problems and make modifications as necessary.

  • Unsupervised Learning: To train an unsupervised machine learning algorithm, you don’t need to classify or label the data. It is possible for systems to infer a function from unlabeled data in order to explain a hidden structure. Throughout the whole process, the machine does not know the right answer. Instead, it uses datasets to make predictions about the result.

  • Reinforcement Learning: A Reinforcement learning algorithm is a way of teaching a computer to do something by causing it to do an activity and then looking for faults or rewards. “Trial and error” and “feedback” are two of the most important aspects of this kind of learning. 

Workplaces Where Machine Learning is Being Extensively Used

Businesses across many industries are already using machine learning to boost innovation and improve operational efficiency

  • Cyber-security firms
  • Finance sectors such as banks and FinTech enterprises
  • Healthcare industry
  • Detection of fraud
  • Retail businesses

Why this Course?

Acquire a firm grasp of the fundamentals of data analytics and machine learning, and learn how to master the most used data science tools and methodologies, to position yourself for employment. Post Graduate Program in Data Analytics & Machine learning by Imarticus comes with a guaranteed placement opportunity. 

In this machine learning course, you’ll learn exactly what the world’s leading employers of data scientists are looking for in their employees. As part of the curriculum, you’ll work on Capstone Projects, real-world business cases, and mentoring from industry leaders that matter.

Conclusion:

While many might say that employment is being lost to AI at a far faster rate than in prior industry-changing events, the numbers so far do not stack up. Rather than eliminating employment, artificial intelligence in the workplace is enhancing people’s skillsets, and hence their compensation, across a broad variety of sectors.

So without any delay, get your machine learning certification now and pave your own path to becoming a successful Data Science Professional with Imarticus’ Post Graduate Program in Data Analytics & Machine learning.

Modern Face Recognition: The Marvels Of Deep Learning

Posted on by Imarticus Learning

You can say you’re living in an exciting time when a phone can recognize your face; even social media can help you automatically tag your friends without having to look for them. It’s so convenient; no one has to search for a name anymore! Face recognition does the trick. 

Modern Face Recognition technology is a marvel of deep learning. As one dives to explore Machine learning and Artificial Intelligence, it becomes easier to understand how facial recognition technology uses deep learning algorithms to identify and match the face with a database. It is here to solve the modern-day problem!

Deep learning enables individuals to use massive datasets of faces to their advantage. It allows one to learn how to represent faces richly and compactly. One has the agency to allow modern models first to perform and even surpass the face recognition capabilities of human beings. If you’re interested in deep learning, you can consider undergoing a Deep Learning Certification Course.

A Deep Learning Certification Course teaches the learner to chain together several machine learning algorithms. Even today, recognizing facial images acquired in an outdoor environment and with changes in illumination pose remains an unsolved problem. 

There is a great leap when it comes to detecting faces automatically. 

Whether it is face detection, face alignment, feature extraction, or face recognition: all systems have a different module or a program for each step. The thing with deep learning is that it becomes more accurate with increasing databases. 

For those planning to pursue a career in deep learning and are intrigued by the modern face recognition features, the fascinating thing about deep learning courses is that it counts data as experienced within their field, and the marvellous thing is that it works like a human brain! It is all about gaining experience with the new datasets and the accumulated past. 

Profound learning benefits include presenting factual responses to real-time data and making reliable predictions. The data faceprint is often used and compared with facial recognition software to present factual responses to real-time data.

Hence, modern face recognition relies on four established Deep Learning systems that work together. They are as follows:

  1. DeepFace has an accuracy of 97.25% and relies on digital images to detect an individual’s identity.
  2. DeepID- is known as reported to be more successful than human beings and is the first model of deep learning developed for facial recognition.
  3. FaceNET helps in getting state-of-the-art results and is known to use the triplet loss function, resulting in better feature extraction.
  4. VGGFace is a series of models developed for face recognition and helps recognize faces.

best data science courses with placement in IndiaThose interested in Certification in Artificial Intelligence & Machine learning have a chance to upskill themselves and immerse themselves in the latest and ever-evolving face recognition technology.

Get ready to explore deep learning methods and gain an in-depth knowledge of multi-tiered courses and an algorithm that is bent on creating statistical inputs unless one reaches an acceptable level of precision.

So, those who are interested in facial recognition technology can enrol for Certification in Artificial Intelligence & Machine Learning from Imarticus Learning. With deep learning techniques, you can achieve superhuman performance and solve problems related to face recognition. 

To enrol in a deep learning certification course that can transform one’s future, contact Imarticus Learning through chat support. One can drive to the training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

Kick-start your career with the program that is the most sought after by technocrats today and can provide you with a well-paying job.

What are the responsibilities of a certified supply chain analyst ?

Posted on by Imarticus Learning

Supply chain analysts are the backbone of every organization. They take care of all logistics, from managing inventory to ensuring that products get to the right place at the right time.

Supply chain analysts are in charge of ensuring that products and services get to their destination on time. They also ensure that these items are handled with care, which means they have to work closely with suppliers. Supply chain analysts need to be responsible for everything from knowing how much inventory is required at each location to ensuring the correct product arrives at the right store. 

Who is a Supply Chain Analyst?

A supply chain analyst works for a company to improve its bottom line by looking at the complete picture of its operations. A certified supply chain analyst will understand how all aspects of production and distribution affect profitability and how operational changes can be made to increase profits. It is imperative to explore what a supply chain analyst does and what responsibilities they have to answer the question “what are the responsibilities of a certified supply chain analyst?” Becoming a supply chain analyst is an excellent way to enter the field of business. 

best supply chain management and analytics coursesKey roles and responsibilities of a Supply Chain Analyst:

  • Work with the management team to identify areas for improvement and implement changes 
  • Analyze data, ensure that processes are efficient, monitor product flow (location of goods), inventory levels, etc. 
  • Collaborate with other departments within an organization to achieve common goals. This may include working closely with the supply chain managers to determine how best to allocate resources based on production schedules or shipping deadlines; understanding facility layout to avoid making it difficult or inefficient for employees; ensuring worker safety by analyzing equipment effectiveness and ergonomics. 
  • Supply chain analysts are responsible for keeping track of all aspects of how goods are created, transported, sold, and delivered. They make sure that businesses have everything they need before it becomes necessary to order more. These professionals need to keep up with new technological advances to be prepared for what comes next in business.

Grow and Transform with Imarticus Learning:

Future-proof your career with the new-age curriculum with the supply chain analyst course offered by Imarticus Learning. The Certification Course is designed with DoMS and E-learning Centre, IIT Roorkee & industry leaders to provide a cutting-edge experience to candidates who wish to enter the operations & supply chain industry.

Supply Chain Analytics enables management to make data-driven decisions at strategic, operational, & tactical levels. This certification prepares you for high-demand job roles such as Demand Planner, Data Scientist, Supply Planner, and Supply and Operations Planner.

Supply Chain Management Online Course USPs:

  • The six-month program is uniquely designed by IIT faculty & industry leaders.
  • With the ever-increasing trend of e-commerce, the amount of movement of goods has been ever-increasing. The program prepares you to gain from this opportunity.
  • Learn from one of the best faculties in India through live online sessions and discussions.
  • Solve complex real-industry problems demanding a thorough understanding of concepts, mastery over a skill, and understanding the business context. 
  • Boost your resume and stand out with these real-world SCM projects.

9 trends in the data visualization job market

Posted on by Imarticus Learning

Do you love to solve problems by going through huge amounts of data? Do you dream of coming up with strategies and tactics that could take businesses and companies to new heights? If the answer to these questions is yes, then a data analytics course is rightfully suited for you.

When you enroll for a data analytics certification you will oftentimes come across the term data visualization. Before we understand data visualization and what some of the hottest topics trending are, let us quickly browse through the basic idea of data analytics. 

business analytics certification courseWhat is Data Analytics?

Data analytics is the process by which one analysis raw data to draw conclusions about the acquired data. Most of the processes and methods that go into the science of data analytics have been automated into algorithms that analyze data quickly and efficiently for ready human consumption.

The word data analytics is an all-encompassing term that includes diverse data types. The technique of data analytics is useful to reveal metrics and ongoing trends that would at other times be lost in the vast ocean of existing information. The ocean accumulated can aid in optimizing processes for greater efficiency and productivity.

There are 4 types of data analytics explained briefly for your better understanding:

  1. Descriptive Analytics:

Evaluates and describe what has occurred over a fixed time

  1. Diagnostic Analytics:

Focuses on the why with greater emphasis on the diversity of data inputs

  1. Predictive Analytics:

As the name suggests, it tries to predict what is going to happen in the coming term

  1. Prescriptive Analytics:

Makes a suggestion about the possible course of action

9 Trends in Data Visualization Currently

Once you have acquired and analyzed your data, you need to be able to graphically and pictorially represent it in a way that is easily understandable. Data visualization presents you with the technologies and tools required to analyze a massive corpus of data. Here are a few ongoing trends in the field of data visualization that can help you get greater clarity on things:

  1. Big Data

This kind of data visualization will need high-performing devices that will be able to gather data, process it, and transform it into graphical representations that people can quickly draw insights from.

  1. DataOps and Self-Service BI

The term coined by Gartner enhances the quality and reduces the cycle time that goes into the operational aspect of data management. Together, these two tools aid in the smooth flow of information/data across pipelines over the entire supply chain system.

  1. Hybrid Enterprises

After the pandemic hit the world, more and more businesses are opting for cloud-based computing which signals the fact that there is an emergence and rise of product features that is hybrid in nature.

  1. Data Storytelling

This is a crucial angle of business intelligence wherein data analytics helps to revolutionize the art of data storytelling. As organizations strive to build a thriving culture, data storytelling methods enable conversations to be nurtured around data.

  1. Adaptable BI Ecosystem

Developers have made it easy to personalize experiences with respect to a company’s flow of data. Analytic apps have enriched the system reducing the time required for data-based actions over BI loops. With the help of the BI ecosystem, the workflow would run more smoothly making it feel as if it were a unified system.

  1. Agile Strategies

As data is moving at a break-neck speed, firms and organizations would need to re-evaluate how they can strategize data to make it more agile and flexible. Cloud computing can be highly useful in this regard.

  1. Non-Technical Professionals

Non-Technical Professionals also referred to as Citizen Data Communicators, are scientists who can communicate with data effectively and easily. Post-2021 will see an epic rise in data scientists as data visualization becomes the norm and the universal language across business ventures.

  1. Operationalized Data Lake

Data Lake is a popular concept that acts as a storage area for enterprises. A data lake is highly preferred because it offers an economical way of storing a massive amount of data similar, yet, different from the cloud.

  1. Personalized Conversations

Updated NLP systems help data owners to engage with data in a more economical and direct manner.

Benefits of Data Analytics Course

Now that we have gone over in a concise manner what is data visualization, data analytics, and the various trends of data visualization, let us see how a business analytics course can be helpful in the current job market:

  •         It is highly in-demand
  •         The job opportunities are immense
  •         Big data analytics is very important these days
  •         You can explore new revenue streams
  •         Opens up wider freelancing opportunities

These are the various ways data analytics certification can help you in your professional life.

Data Analytics, Productivity and Well-being: Are they inter-related?

Posted on by Imarticus Learning

Forms and benefits of data analytics have shifted majorly in the last few years. Major firms have also been using it as a way to decipher the habit patterns of their employees to take care of their well-being. Needless to say, their well-being directly relates to their workplace productivity. However, with the evolution of data analytics, data analysts also have to be able to evolve constantly.

And that is only possible when they have the proper training to adapt to situations, and that can only happen if they learn data analytics from a proper institution. Imarticus Learning has come forth with a great opportunity for people who would like to polish their skills with their new PG program with data analytics certification. 

Coming back to the impact of the well-being of employees on company productivity, studies have found that being comfortable in their workplace can make the workers about 12% more productive.

Data analysis as a tool to ensure happiness

Major firms have been trying to gather and decipher the patterns of their employees’ behavior to provide a personalized experience to them for some time now. There are a lot of ways companies have decided to approach it. Some offered wearables to their employees that will teach how much time they spend, sitting, talking, writing, or moving about. Some have chosen the company intranet to trace their online tracks.

Now it falls to the data analytics team to extract, and decipher these patterns. It is fruitful in the sense that these patterns always give indications of not only their physical health but also their mental ones. This is also a way where companies can provide personalized suggestions for their well-being. And the employees get benefitted from it in a way that impacts their daily life. As a result, they feel more loyalty to the company.

Hurdles to jump over

There are some evident advantages of exchanging data for the betterment of the employees’ well-being, and in turn, increase their productivity. However, it is also a possibility that when it comes to data gathering and analysis, the employees might have some privacy concerns about them. Which in turn, might make them unwilling to participate actively in the bandwagon.

This is why, there are a few things that should be kept in mind when it comes to the interrelation of well-being and productivity of the workers, such as:

  • The first and most important thing is to make sure the workers consent to the exchange of data for the company’s use, as many might have privacy concerns relating to that.

  • Companies will need to have experts in the analytics team to properly extract and use the data and make it a priority for both the main wing of the business and the analytics team to prioritize the employees well being.
    They need to communicate properly to the workers how it benefits them and the company both at once.

  • The key is to recognize what the employees want and be able to cater to it. Otherwise, even after using data analytics to define the workers’ needs, it will be utterly irrelevant.

Conclusion

Using data analytics as a mode of communication between the employer and employee needs time and expert skills. And it can only come if you learn data analytics from a good place.

Many institutes in India offer a data analytics certificate course. Imarticus Learning is one of the topmost among them, so do check out their PG program in data analytics and machine learning.

Is omnitude the solution to supply chain planning?

Posted on by Imarticus Learning

Omnitude is a blockchain platform that improves supply chain planning. It allows businesses to connect with their suppliers and customers securely and transparently. Omnitude has the potential to revolutionize the way companies operate, and it could be the solution to supply chain planning in 2022. This blog will discuss the benefits of using Omnitude for supply chain planning and how it can help your business grow. 

Omnitude is a blockchain platform that enables businesses to solve problems in the supply chain. It provides a transparent and secure way of recording data, which you can use to verify the authenticity of products and track them through the supply chain. 

Why is Omnitude a good solution for supply chain planning?

Omnitude is a good solution for supply chain planning because it offers a blockchain platform that you can use to connect various parties in the supply chain. It allows for greater transparency and trust between all parties involved.

Omnitude also offers smart contracts, which can help automate the entire supply chain planning process. It helps speed up the process and reduce the risk of human error.

Omnitude is also a secure platform that offers encryption and authentication features. It helps ensure that all data transmitted on the network is safe and confidential.

Finally, Omnitude is an open platform that anyone can use. It means that businesses can benefit from its features.

How to get started with omnitude?

There is a lot of excitement around omnitude and its potential to revolutionize supply chain planning. However, many businesses are unsure how to get started with the platform. Here are three steps to help you get started:

Step One: Identify Your Needs

The initial step is to identify your needs and requirements. What challenges are you facing in your supply chain? What areas would you like to improve? Omnitude can help with various issues, such as inventory management, tracking deliveries, and reducing waste.

Step Two: Choosing the Right Implementation Strategy

The second step is to choose the right implementation strategy. There are two main options: self-hosting or cloud-based. Self-hosting allows you to install and manage the omnitude platform yourself, while Omnitude provides cloud-based solutions. 

Step Three: Getting Started

The final step is to get started! Once you have identified your needs and chosen an implementation strategy, it’s time to start using Omnitude. There are a variety of tutorials and resources available online to help you get started. Don’t be afraid to ask for help if you need it.

By following these three steps, you can get started with Omnitude and begin experiencing the platform’s benefits.

Explore Supply Chain Management Course with Imarticus Learning

The supply chain certification provides cutting-edge expertise to those interested in entering the operations or supply chain analytics course. Across industries, there has been a dramatic growth in the number of SCM jobs. A career in SCM can be enriching, both financially and professionally. 

best supply chain management and analytics coursesCourse Benefits For Learners:

  • We immerse students in in-demand technologies and projects, including six real-world projects that will give them a complete grasp of the industry to prepare them for a satisfying future in Supply Chain Management and Analytics.
  • Students who complete a supply chain management online course will prepare for competitive careers such as Demand Planner or Data Scientist, which are in great demand among companies today! 
  • This supply chain management career will help students become more data-centric and improve Supply Chain decision-making by harnessing the power of Python.

Python certification: Do not use print for Debugging anymore

Posted on by Imarticus Learning

About Python Language

Want to learn how to make your work productive and easy even though it is time-consuming? Python programming is a high-level programming language used by big organizations around the world such as NASA, National Security Agency, Bit Torrent, Netflix, and more to conduct data analysis and automate tasks. It is used widely by software developers to build their website effectively in alignment with the domain because of its features like object-oriented language which helps to break down tasks and gain clarity.

Before we delve into the features and benefits of Python programming, let us understand briefly what is meant by the programming language. 

Continue reading “Python certification: Do not use print for Debugging anymore”

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