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Category: Analytics

The Popular Use Cases of Artificial Intelligence in BFSI

Posted on by Imarticus Learning

AI has revolutionized every industry and has changed the way businesses function. Everyone is finding ways to adopt AI into their work. Similarly, the banking, financial services, and insurance sector is also looking to integrate AI into their business and one major reason for doing that is the security of customers.

Customers expect banks to deliver flawless experiences and improve methods of interaction. In the last few years, banks have faced a rise in security threats which is why the banks had to come up with new ways of tightening the security because they were starting to lose clients.

A global study indicates that 85% of respondents have already implemented AI within their organizations and expect to use AI in the new use cases that come and 77% of respondents are anticipating the use of AI processes in their business in the next 2 years.

How is AI strengthening the competitiveness of banks?

Artificial Intelligence and machine learning is the future of banking as it has the power to combat fraudulent activities and improve customer service. Here are some examples of what changes AI has brought about in the banking industry –

  1. Mobile banking – Mobile apps are becoming more advanced and personalized. Banks can generate more revenue with mobile banking services than they generate from customers visiting the branches. This has also saved a lot of time for consumers and improved the quality of services provided.
  2. AI chatbots – In banking, chatbots are used to create an interactive experience for the customers. Bots can communicate with the customers and solve their queries while staying within reason and following the rules. Chatbots can also work 24 hours a day without breaks, which increases the productivity of the banks.
  3. Enhanced security – With the unlimited amount of personal data that is digitized and the number of digital frauds that are happening, it is customary for the banks to keep the client’s money and confidential information safe, and AI helps with that. They have come up with cybersecurity measures like fingerprints, iris, and voice recognition. These measures are almost impossible to forge, therefore everything is safe.
  4. Conformity – It is important to regulate data constantly. There are different processes like “Know Your Customer (KYC)” or “Anti Money Laundering (AML)” that can gather data and transactions digitally, which makes the work faster and easier. If done manually, this process can take up a lot of time. AI algorithms can integrate data very accurately and efficiently.
  5. Financial evaluation – Banks usually earn their profits through the interest they receive on loans. To keep a check that the loans are given back on time with proper interest, they have machine learning algorithms that analyze millions of data and assess whether the client is a risk or not, and then come up with a decision.

Conclusion

People are looking for exceptional services at the click of a button, they don’t want to wait for days for a transaction or money transfer. AI is not only the future of banking, it is also the present. It is advised that all financial institutions start investing in AI right now so that they can optimize their services. With the help of AI certification that is offered by AI and machine learning courses, people can make this revolutionary change in their businesses.

5 Powerful Business Analysis Tools Aspirants Must Learn!

Posted on by Imarticus Learning

The term “Business Analysis” is self-explanatory. It is a system put in place by enterprises to analyze various aspects of their business. To define it more elaborately, it is a research-based practice that drives change in an organizational context by analyzing limitations and loopholes, defining needs, and guiding solutions aimed to deliver value to stakeholders. The reason why some businesses grow exponentially bigger than others is rooted in successful business analysis systems.

Business analysts often rely on software and tools to aid in the process of business analysis. There are several such tools in the market, each with its own unique features. Comprehensive knowledge of business analysis tools is often a key requirement in the recruitment of business analysts.

In this article, we list the 5 most powerful business analysis tools that are a must-learn for a successful business analyst career.

Top Business Analysis Tools

SWOT

SWOT analysis is one of the leading techniques of business analysis, which involves a strategic review of current strengths, weaknesses, opportunities, and threats. There are several SWOT analysis tools available online, but SWOT is perhaps the most comprehensive of the lot. Not only does it make SWOT analysis easy, but also provides a platform to brainstorm and collaborate among teams.

Trello

Trello is a Kanban-based collaboration tool that makes managing and prioritizing tasks incredibly easy for entire teams. Trello is a simple yet comprehensive way for business analysts to track tasks, plan projects, and chart progress. It is an extremely useful tool that every business analyst must master.

Version One

Version One is a powerful business analysis tool that also allows integration with enterprise and agile software development applications. It is expressly built to allow automation and scale-up project workspaces across teams in multiple locations.

Pencil

Pencil is a free and open-source tool that is used for prototyping and creating mockups. Prototyping is often critical for business analysts to give customers and stakeholders a visual sense of a product. Pencil allows changes and recommendations to be incorporated into the prototype to ensure the best final product.

Microsoft Visio

One of the leading project management and business modeling tools that many big businesses use is Microsoft Visio. Visio is a comprehensive business analytics solution that helps analysts create project flowcharts, schedules, use case diagrams, data models, process flows, etc.

A Career in Business Analysis

Job titles under the business analysis spectrum include business analysts, business systems analysts, requirements engineers, business intelligence analysts, data scientists, and more. Business analysts enjoy a demanded position in businesses of all shapes and sizes. This field of work comes with the guarantee of long-term stability and a lucrative remuneration.

You might be wondering – how to become a successful business analyst? The first step in pursuing a career in business analysis is to get certified. Acquiring certification not only imparts the necessary skills and training required by any business analyst but also gives the candidate a winning edge in the eyes of the recruiting company. Candidates with an MBA or a Bachelors’ degree in Business, IT, or a related field are usually preferred over others. Sound knowledge of business analysis tools is an added plus point.

Conclusion

Business analysis is a profitable career path that guarantees growth, stability, and a high salary. In order to advance your prospects of securing a business analyst role, you could consider signing up for a business analyst course such as a PG Program for Agile Business Analyst that would provide foundational training and knowledge.

What is the best approach to Data Analysis in 2021?

Posted on by Imarticus Learning

As time goes by the approach to any form or strategy of business changes. Even more so when it comes to data, as it is ever-changing. Throughout the years, data analytics has grown from a peripheral part of a business to an integral part of it. It is a prominent tool to not only extract and decipher past records but also predict and develop future strategies.

However, it comes with a little difficulty as most of the time, data analysts have little idea of how to execute a business. And in the same way, executives have little idea of how data analytics works and how to use it.

This is why it is important to have a basic idea of what is business analytics to give you that little edge over others. The best way to do this would be with a data analytics certification course, similar to what Imarticus Learning is providing with their new PG program. However, to make it easier, here we have compiled two successful ways that data analytics can be approached in 2021.

For the long run

In many cases, companies invest a lot in data analytics and focus on building business value around it. This includes training the employees about data analytics, developing company systems and syncing them with data analysis, and finally, discussing more data analysis initiatives. This requires a complete transformation of business values and systems.

Tackling clearly-define high-grade problems

One of the best ways to approach data analysis is by defining a high-grade problem with clear goals. When it comes to high-grade problems, the issue remains in the volume or layers in which a problem is divided. Each of these layers interplays and pile up to end up being a high-grade problem.

So, with data analytics, you can target a small subset of the problem and by getting the numbers right, you can take a sustained route towards growth. Unlike the investment model where too much time could pass before results show, this model seems clearly the best approach in 2021.

Things to keep in mind

One thing to always keep in mind is that data analytics merely show a record of how the past has been and how the future can turn out to be. It is not always possible to meet the exact expectations as the results depend on a variety of things. There are a few other things that everyone should keep in mind when it comes to data analytics, such as:

  • Data analytics need to be made a part of the main wing of a business as without being in the loop it would be impossible for the analytics team to be of any help.
  • Problems should be specified and addressed together with the executives. This will make the process of extracting and deciphering data as well as developing a proper plan to address the specified problems a lot easier on both sides.
  • Executives should have a basic knowledge of what is business analytics. It will make the communication and understanding between the two teams smoother.

 Conclusion

 The process can create disruptions as data tends to create transparency. It can be uncomfortable to face the shortcomings of a business, however, this is also the best way to form strategies to overcome those shortcomings. This is why companies need experts on their teams to help them along the way. You can enhance your skills with a proper data analytics certification course or a PG program if you wish to pursue this career.

What is the job description of a logistics manager?

Posted on by Imarticus Learning

The logistics manager is an integral part of the supply chain management system. The supply chain management career is an ever-growing field that opens up plenty of job opportunities. Although the logistic manager will be mainly focusing on warehouse storage and the subsequent distribution, it is a job that can offer further growth in their career. There are several who are opting for this field as a career.

If you intend to be such a manager or are opting for a logistics and supply chain management course, you should be aware of the proper job description of the role. 

What is a logistics manager?

A logistics manager will be responsible for the overall management of the warehouse of the companies right from the planning, operating, storing, coordinating, and transporting of the associated materials. The manager would need to keep up with the inventory and the transportation until the products reach the next level in the supply chain. A manager may be responsible for a particular warehouse or multiple warehouses of a particular region as well. 

This is an area that serves as the middle in the overall supply chain. It requires a bunch of skills such as negotiation, analytical, leadership, administrative, organizing, and budgeting powers. This is where the Certificate in Supply Chain Management & Analytics helps. This course covers a wide range of program languages and tools to help candidates prepare for their responsibilities.  

Responsibilities of a logistics manager

  • Managing the warehouse includes organizing the goods, preparing proper inventory, and labeling the goods to ease the process. 
  • Preparing a proper budget for the transportation and negotiating with the carriers to transport it within the budget is another responsibility. 
  • Keeping track of both the incoming and outgoing deliveries can be a daunting task which also requires plotting the routes. 
  • A logistics manager should be aware of the latest shipping techniques to reduce the cost and maintain the goods in their proper shape and quality. 
  • It is also the responsibility of the logistics manager to have in-depth knowledge about the rules and regulations of the transportation, the ISO requirements, or the various guidelines. Managers must ensure that all the laws are properly followed by everyone under them until the goods reach the next level. 

The Certification in Supply Chain Management & Analytics course trains the candidates in the departments such as metrics, planning, designing, coordinating, sales and operations, etc. 

How to qualify to be a logistics manager

The primary requirement for starting a supply chain management career is to find a quality logistics and supply chain management course such as the SCM. Anyone with a Bachelor’s degree can apply for such a course.

Having at least 2 years of experience in the SCM field would be an added advantage. The candidate should have strong knowledge about supply chain, distribution, management, inventory, etc, along with exceptional skills in communication and analysis. A keen eye to observe the minute details would be a huge advantage as the manager is responsible for the daily operations as well as the employees’ performance. 

Conclusion

The role of a logistics manager is demanding as every day comes with a new challenge. It can be exciting or exhausting. This demanding job is not suitable for all. But those who are enthusiastic about such responsibilities can find it exciting. Those who like to solve problems will find such a job description thrilling. If you are among those, enroll into SCM now to have a stimulating career ahead. 

How Can A Supply Chain Management Course Help Professionals?

Posted on by Imarticus Learning

Supply Chain Management is a relatively new concept in the business world, but it has become increasingly important. Supply Chain Managers are responsible for ensuring that items and materials never run out. They work to ensure that their company is profitable by keeping costs low and having enough products to sell.

A supply chain management course can help professionals learn how this process works and give them an edge in the job market!

Supply Chain Management: An Overview

Supply chain management is a profession that has been gaining popularity over the past few years. The supply chain refers to the process of delivering goods from suppliers or manufacturers to customers. The supply chain may also include warehousing, production, and distribution, as well as retailing. This industry encompasses everything from sourcing raw materials for manufacturing products to how those products are marketed and sold at stores after they have been manufactured.

Supply chain management is a process that links the production and distribution of goods, materials, and services. The goal is to deliver what the customer needs as efficiently as possible. The process helps companies to manage the flow to help maximize efficiency.

Supply Chain Management Career: An Invincible Option

Organizations always look for ways to increase production while reducing costs. A supply chain management course can provide professionals with an understanding of how retailers work together to meet consumer needs.

Here is how a supply chain management course can help professionals:

supply chain management and analytics course by IIT, RoorkeeEfficient Collaboration: To swiftly and effectively deal with issues when they arise, it is vital to maintain a smoother flow of information across the supply chain to avoid any miscommunications and confusion.

Quality control improvements: To source better components and services, you must have better awareness & control of different links in the supply chain within your processes.

Keep up with demand: Supply and demand are factors that fluctuate in counter-intuitive ways. Improved data analysis & communication between producers, sellers, and suppliers can reduce the chance of supply hitting a bottleneck.

Cost Reduction: Improvement in quality control and inventory management brings along lower overheads & allows better optimization for profitability.

Mitigate risks:  A supply chain certification helps you figure out how to predict new challenges, for example, a supplier going out of business. Professionals can efficiently prepare for any unpredictable situation and minimize inefficient risk mitigation costs like unnecessary stockpiling.

Transform your SCM Career with Imarticus Learning:

If you are passionate about a supply chain management career, the Professional Certification in Supply Chain Management and Analytics course you need to enroll in today! The program has been designed in collaboration with DoMS and E-learning Centre, IIT Roorkee, and experienced industry leaders. The system provides a cutting-edge experience to candidates who wish to enter the operations and supply chain industry.

supply chain management and analytics courses by IIT, RoorkeeSupply chain certification enables professionals to make data-driven decisions at strategic, operational, and tactical levels. In the Supply Chain Management field, there is a shortage of professionals with process and analytics talents. This certification prepares you for high-demand job roles such as Demand Planner, Data Scientist, Supply Planner, and Supply and Operations Planner.

USP’s of Supply chain Management course

  • Master SCM know-how & much-needed skills in analytics through this cutting-edge curriculum designed by the DoMS & E-Learning Centre, IIT Roorkee.
  • Learn from one of the best faculties in India through live online sessions and discussions.
  • Get an opportunity to participate in the 3-day campus Immersion module to visit the IIT Roorkee campus.
  • Solve complex real-industry problems demanding a thorough understanding of concepts, mastery over a skill, and understanding the business context.
  • Supply chains generate massive amounts of data – Big Data, to be more specific.

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

How can a machine learning and artificial intelligence course help you become a social media analyst?

Posted on by Imarticus Learning

Social media has become an integral part of our lives. It is how we keep up to date with the world, and it is also a way for businesses to promote their products/services. With all of this in mind, many people are looking for ways to get into the social media industry.

One of the popular routes is through a job in social media analysis. Social media analysts are becoming more and more important as time goes on. This position requires you to monitor and analyze data on your company’s various social channels.

Thus, machine learning and artificial intelligence courses are becoming more popular among people looking for a potent solution.

How AI and ML are used in social media?

Social media is a very lucrative and competitive industry. Those who can best analyze data, find useful patterns and insights into the business end up earning the most money. This has led to many big players such as Twitter, Facebook, and LinkedIn investing heavily in AI systems that help them better understand their users’ behaviors without even gathering any specific user information!

Social media marketing agencies also use these analytics tools for understanding consumer behavior around products or services offered on social channels like Instagram & Snapchat. The same technologies are used by internet giants like Amazon and Google to offer seemingly personalized search results with just one keyword input from anyone trying out something new online – be it buying a product or browsing through material freely available on the web!

This ongoing trend of personalization based upon customer behavior and interests has made AI a huge part of our lives today.

How do ML and AI courses help you become a social media analyst?

Many companies are now looking for social media analysts to help them understand consumer insights and market expansion opportunities. If you want to become a successful analyst, it is important that you learn how machine learning and artificial intelligence can aid your efforts as marketers in various ways.

Here’s how ML and AI help you become a social media analyst:

Track consumer behavior patterns. ML and AI help you understand the behavioral pattern of your customers by tracking their social media activity. This information enables you to make a business decision or product development strategy that will help gain customer attention in the future!

Increase ROI with AI-assisted marketing campaigns: ML and AI will help you identify the best marketing campaign to increase your brand exposure. You can use AI-driven tools such as chatbots, ads bots, etc., for effective customer engagement using social media platforms like Facebook or Twitter!

Use Sentiment Analysis: You can easily understand consumer sentiment by tracking what they say about a product on different platforms with ML assistance. This information is crucial in understanding their needs so that you can provide them with better quality products/services!

These were just some of the many ways how ML & AI courses can help you become a successful Social Media Analyst!

Elevate your social media analyst’s profile with Imarticus Learning

Imarticus Learning offers Machine Learning and Artificial Intelligence courses. The comprehensive curriculum of these courses will help you build a strong foundation in machine learning, data analysis, deep learning, and artificial intelligence to take on complex problems for social media strategies.

What’s unique about this AI ML certification course?

  • Cutting-edge curriculum and certification by E&ICT Academy, IIT Guwahati
  • Opportunity to participate in campus immersion module
  • Learn what new-age AI & ML Engineers do in a real-world scenario
  • Build an impressive AI & ML project portfolio for future employers

This comprehensive program can take your career a step ahead towards rewarding opportunities in this domain.

Why Should Engineers Learn Data Science Differently?

Posted on by Imarticus Learning

Why Should Engineers Learn Data Science Differently?

Data science and engineers have a lot in common. They both need to know how to collect, store, analyse and visualize data. Engineers are taught these skills as part of their curriculum; however, they may not learn them as they would if they were learning Data Science from the start. The following is an overview of why engineers should learn Data Science differently than other disciplines.

A blog post intro paragraph engages professionals about why engineers should learn data science differs from other disciplines. Engineers are taught these skills as part of their curriculum but may not understand them simultaneously or efficiently without exposure to them earlier in life.

Why is Data Science important for Engineers?

Engineers always like to think about their work in processes and systems, also known as Systems Thinking. It is what enables them to build more efficient products by efficiently running those processes. By thinking of the world in this way, engineers can quickly solve data-related problems because they see all sides of an issue that deals with data.

It’s important to remember that engineering can be applied in any industry, including Data Science. As a data scientist, it’s often necessary to run specific processes and analyze the results. Engineers excel as they can take these processes and incorporate them into the current system that the company may already have set up, saving time and money in some cases.

Benefits of Learning Data Science for engineers.

Therefore it is necessary to run specific processes and analyze results where engineers excel in taking these processes and incorporating them into current systems that a company may already have set up.

Learning Data Science is important because of the benefits that engineers will gain. Engineers overall will be able to learn more efficiently about their field and how it fits into the bigger picture. By taking this information, they will be able to make smarter decisions in data-related situations.

Engineers should learn Data Science differently from other disciplines because it will make them understand better and more thoughtful about their field and how it fits into the bigger picture, enabling them to make smarter decisions in data-related situations.

Why Enrol in the Data Science program at Imarticus learning

Industry specialists created this postgraduate program to help students understand real-world Data Science applications from the ground up and build robust models to deliver business insights and predictions. The Data Science program is for recent graduates and early-career professionals (with 0-5 years of experience) who want to pursue Data Science and Analytics, one of the most in-demand fields.

Twenty-five in-class real-world projects and case studies from industry partners will help students become masters in data scientist careers. Exams, hackathons, capstone projects, and practice interviews will help students prepare for placements.

Some course USP:

  • The course lets the students learn job-relevant skills that prepare them for an exciting Data Scientist career.
  • Impress employers & showcase skills with a certification endorsed by India’s most prestigious academic collaborations.
  • World-Class Academic Professors to learn from through live online sessions and discussions. It will help students understand the practical implementation of real industry projects and assignments.

Contact us through the live chat support system or schedule a visit to training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

What Are the Algorithms in Machine Learning? How Does It Work?

Posted on by Imarticus Learning

Machine learning is a vast field comprising of various data related operations such as analysis, prediction, decision making and much more. These applications require a set of well-defined steps to proceed with the idea designed for model construction. A set of well-defined instructions that produces some output or accomplishes a particular task is called an algorithm. The machine learning algorithms are broadly classified into 3 categories – Supervised, Unsupervised and Reinforcement Learning.

To choose an appropriate algorithm in machine learning, identifying the kind of problem is very necessary as each of these algorithms obeys a different plan of attack to deal with the proposed problem. Supervised learning uses an approach where the output is already known to the user or the individual while unsupervised learning concentrates on the concept of similarity in properties of the objects. Reinforcement learning differs from both of them and uses the art of learning from experiences.

Supervised learning

Supervised learning is used in machine learning tasks such as classification, regression, and analysis. It is considered as a concept that deals with labeled values. This means that the objects are categorized or assigned to different classes based on their properties. The algorithm implementation in supervised learning is done by a two-step procedure namely model construction and model utilization.

Firstly, the given data is cleaned and divided into training and testing sets. The model gains the ability to produce output by learning from the instances contained in the training set. The test set gives a measure of the model performance by producing accuracy. The accuracy indicates the amount or rather the percentage of unseen data that was computed correctly by the applied algorithm.

There are several metrics to determine the performance of the model and improve it if the performance is not up to the mark. This includes performing tasks like cross-validation, parameter tuning, etc. Hence, we can conclude that supervised learning uses labeled classes and target values to classify an unseen data point.

Unsupervised learning

In contrast to the supervised approach that already knows the predicted outcome, unsupervised learning uses the basis of similarity in properties to classify the unseen data points in the given n-dimensional space.

The main idea is to take a data point that is new to the given space, extract the behaviors of the data point, compare it with the already existing properties of the other objects and accordingly classify or categorize them into the appropriate group. The common examples of unsupervised learning are clustering, Apriori and K-means algorithm.

Reinforcement learning

Reinforcement learning is very similar to the animal kingdom where the animals do not train their offspring to perform a particular task but they leave them out in the ecosystem to learn from the experiences that it gains while struggling to accomplish a particular task.

The basic idea of performing reinforcement learning is to let the model learn on its own. It uses a trial and error strategy to gain knowledge from the available environment. According to the experiences gained from the conditions, it is exposed to, appropriate predictions and decisions are made. Markov Decision Process is an example of reinforcement learning.

Conclusion

Because of the wide variety of applications offered by machine learning, there are several Machine learning courses dedicated to offering the training in machine learning algorithms so that an individual can recognize the problem efficiently and work towards building an appropriate solution. Learning and understanding of machine learning algorithms are very easy. It just needs a proper classification of the interest in performing the desired operation.

Why Big Data Analytics Is a Good Career Move?

Posted on by Imarticus Learning

Data is wealth, this doesn’t sound hyperbole in the modern-day scenario. A data analyst turns raw data into meaningful information that enhances the business and market share and who doesn’t want to grow? Let us look at the key points discussed in the article justifying Big Data Analytics as a good career choice.

Statistics indicate that the average salary of a data analyst in India is 10 lakhs per annum and this salary will keep on growing as you level up. There is a demand for candidates in this corporate world who have good command over big data and its analytics.

Big data analytics is trending globally, surveys show that the USA will have around 2.7 million job postings in big data analytics by 2020. If you are going for big data as your career choice, not only will you gain knowledge over a variety of languages, applications, and strategies, you will also have a chance to grow as the flow of data is never going to stop.

Big data analytics closely works in coordination with the Internet of Things and the outcome of big data analytics helps in business development and predicting trends. Big data also supports various other streams. It is a vast field full of opportunities. Big data analytics is not all about programming languages and statistics, it is also a way of providing solutions to existing problems. It is a way of providing strategies that help in the growth of businesses.

You will have to convey your point of view in your workspace and how it will help in enhancing the business. These things will help you to grow as a good orator and leader. You will also make a lot of business relations in this career. Business intelligence (BI) will also come into play if you work as a data analyst. So, there are a lot of parallel fields if you are a data analyst, such as the importance of big data and its analytics nowadays.

Surveys show that there is a huge demand for big data analysts but there is not enough skill set in individuals to meet the criteria. If you have studied well then you should go in the field of big data analytics as you would be valued and respected there. This deficiency of good data analysts and data scientists are faced in all countries and that is why education centers are providing quality education on big data and related fields.

You can find a lot of online certified course on big data analytics by trusted sources. Every company is trying to gain an edge ahead over others in this competitive era by predicting smart trends and business ideas using big data analytics. There are a lot of companies that consider big data analytics as a topmost priority as it helps them in increasing the efficiency and quality of their business. Why would you reject to be a part of this cutting-edge technology?

Big data analytics is quite versatile, you can choose among prescriptive, predictive and descriptive analysis depending upon your interest and work environment. You can also choose among a variety of job designations such as big data analytics business consultants, big data analytics architect, big data analytics, etc.

Whatever smart solutions analytics is providing today, there is always a scope of improvement and a need for human intelligence. There is a lot of requirement of people in current days who can think out of the box, who can understand and analyze big data and help in improving the business. This was all about the pros of joining the field of big data analytics.

Why the IIT supply chain management program the best of 2021?

Posted on by Imarticus Learning

The supply chain encompasses all of the actions, people, organizations, information, and resources required to transport a product from conception to client. In the consumer goods industry, this is likely to include raw materials, production, packaging, shipping, warehousing, delivery, and retailing. The end goal is straightforward: fulfill the customer’s desire.

Further, supply chain management is the process of combining supply and managing demand not only within the firm but also across all of the supply chain’s innumerable units and channels so that they function together quickly and productively.

 Supply chain management is critical for any firm since it can introduce various benefits. But, inadequate supply chain management can result in very expensive delays, quality concerns, or reputation issues. Poor supply chain management can also lead to legal concerns in some circumstances if vendors or processes are not compliant. Technology advancements have opened enormous possibilities for supply chain management, allowing supply chain managers to collaborate intimately and in real-time with supply chain participants.

 A certified supply chain analyst has a very important role in every industry that involves the supply chain. A supply chain management career can guarantee you a high-salary job in various sectors. The IIT Supply Chain Program is the best and comes with some exclusive benefits.  

supply chain management and analytics coursesThis 6-month supply chain management online course has been specially prepared by IIT faculty and industry professionals to assist you in learning. With the ever-increasing trend of e-commerce, the number of products in transit has also increased. The number of supply chain management employees has increased disproportionately across industries. This training will prepare you to capitalize on this opportunity.

 Why Pursue IIT Supply Chain Management Course?

The benefits of IIT certified supply chain analyst course are as follows:

  1. Discover supply chain management knowledge and much-required analytical skills with this program built by IIT Roorkee’s DoMS & E-Learning Centre. This course will assist you to become more data-centric and improve supply chain selection by using the strength of Python.

    SCM courses
  2. This supply chain management online course will assist you to learn from one of India’s greatest faculties via live online sessions and conversations. IIT faculty workshops will help you construct essential concepts in SCM, while industry specialists will provide hands-on learning for SCM processes, tools, and strategies. This course will teach you how to construct a solid SCM foundation and use analytics through engaging live sessions with renowned trainers and industry professionals.
  3. Participate in a three-day campus immersion session to tour the IIT Roorkee campus. During the campus immersion, you will connect with your peers and learn from IIT academics. You will get the opportunity to go to the Delhi or Noida campus and work on the Capstone Project with the help of expert mentors.
  4. Tackle tough real-world challenges that necessitate a full understanding of principles, mastery of skills, and comprehension of the business context. With these real-world SCM projects, you can boost your resume and stand out. You will be able to create your own project portfolio and dazzle potential employers. Through rigorous in-class exercises and SCM projects, industry experts teach you crucial job-relevant skills.
  5. Massive volumes of data are generated by supply chains – Big Data, to be more explicit. Prepare to participate in the creation of smarter, more strategic, and tactical global supply chains of the future by merging traditional supply chain methodologies with data-driven judgment.It is very evident that the demand for a certified supply chain analyst is increasing by the day. In such a situation, certification can give your career the right boost and help you bag your dream job in your desired company. Enrolling in this course can be a game-changer for you!

supply chain management and analytics courses