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Category: Management

Visualizing Spotify data with a tableau course

Posted on by Imarticus Learning

Visualizing Spotify data with a tableau course

Data science has emerged as a very demanding trend in the industry. Domain skills bring valuable insights from structured and unstructured data using standard tools and techniques.  One of the aspects of data science is data visualization, which is called the graphical representation of the main information obtained from the processed data.

Tableau 

Tableau is one of the standard tools in business intelligence, analytics, and data visualization.  Tableau (desktop and, more recently, public) versions have changed how we interact with visualization and developed data stories for visual communication aids for our large stakeholders, including non-technical audiences globally. With Tableau, you can visualize Spotify streamed data of your favorite artists, tracks, brands, and more. 

You can create dynamic dashboards for visualizing data by using the streaming data and API requested from Spotify and integrating it into the Tableau tool. 

Tableau to Visualize Spotify Music

Once you connect to the Spotify page, you can download music data from the top charts. Top 200 options get a top track or trending track. Use the pull-down menu to filter by country or select Global Options. Similarly, choose from daily or weekly data for your analysis. Use the “Download to CSV” option at the top right of the screen. Daily data is downloaded in the default Spotify_Daily_Streaming file.

Analyze

Now in the Tableau application, load the data source. To open the latest Spotify CSV file on the canvas, select the “Text File” option in the Connect pane. Use the Tableau options to analyze the uploaded data.

The following sections are summarized to analyze the given clause.

Popular Tracks and Artists

Follow the steps to get the most famous songs.

  • Create a new sheet.
  • Add the SUM to rows.
  • Track URL to columns.
  • Sort the songs in the order of greatest to lowest.
  • Enter a name for the track. It is provided next to the Track URL on columns.
  • Using the pill in the columns hide the Track URL title.
  • Mark the Show Header option unchecked.

  Popularity by country

This option is used to analyze how listening habits vary from country to country.

  • Double-click the Country column in the Data panel. Being a geographical area, it plots data on a map. The tableau indicates the geographical column that placed the data on the map.
  • Drop the Streams column into the color for creating a map. For multiple streams, the color turns black.
  • For less than two streams are indicated in a lighter shade.
  • The right-most side of the screen displays unknown values.
  • Double-click on the error notification to remove the data.
  • Use the filter to get the Global column. 

Streaming songs or artists

  • Add the “Week” to rows.
  • Also, add the SUM to columns.
  • You need to filter the Global data.

 You can also analyze currents over time by adding consecutive “week (date)” in columns and SUM (streams) in rows. Of course, in-depth analysis like “seasonality” can be done in the table and allows customized analysis.

Bring to Dashboard

Just drag the sheets from the above analysis with the default map. Select the “Use as filter” option on the map and bar chart. Finish the map’s visual presentation settings with color, grid, and format options.

Data Analytics Certification

It is convenient for new graduates with nearly 5 years of industry experience to upgrade with Visualizing Spotify Data for new graduates and with a tableau course designed for career professionals in data analytics. Imarticus Learning also offers you a PG degree in Data Analytics and Machine Learning.

 You become stronger with the foundation of data analytics and machine learning concepts and with the most in-demand data science tools and processes to play a better role in the data science domain. With the Data Analytics course, you can master skills in data visualization as well as Python, SQL, data analytics, and machine learning for data visualization. To get more information about courses in analytics, contact us through chat support, or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

Learn Computer Vision: What is Hyberbolic Image Segmentatioan?

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Learn Computer Vision: What is Hyberbolic Image Segmentation?

Currently, we carry out optimization at the pixel level in Euclidean embedding spaces for segmenting images. We do this through linear hyperplanes (2D visualization). Keep reading to clear your concept for the Artificial Intelligence Course regarding a key alternative for image segmentation that is done in hyperbolic space. 

Computer Vision is one of the most exciting topics covered in Artificial Intelligence and Machine Learning Certification. This field allows systems and computers to retrieve important information from digital visuals like images and videos. Based on the received data, computers process information to make suggestions to the user. 

If we were to simplify the concept, computer vision tries to make computers view images and videos the way humans do. Today, the advancement in deep learning and neural networks has made these systems exceed human performances in some aspects like object detection. 

Today, spherical and Euclidean embeddings dominate the most-used tasks of computer vision like image retrieval and image classification. 

On the other hand, Hyperbolic Image Segmentation is one of the latest standards for segmenting images. It offers multiple practical benefits like: 

  • Uncertainty estimation
  • Boundary information
  • Zero-label generalization 
  • Increased performance in embeddings of low-dimension

Why do we use Hyperbolic Image Embeddings? 

In Natural Language Processing (NLP) tasks, hierarchies are ubiquitous. The widespread presence of these tasks motivates the use of hyperbolic spaces in this field. This is because hyperbolic spaces inherently embed tree graphs and other types of hierarchies with minimum distortion. 

While retrieving an image, you will notice that an overview picture of something can be mapped to the closeups of many unrelated pictures. These pictures might have a wide range of dissimilarities in their details. 

Furthermore, let’s consider classification tasks. For such tasks, an image that contains representations from many classes is generally connected to images that possess the representatives of those classes in insulation. Thus, the process of embedding such a dataset, which contains composite images, into a continuous space is said to be similar to hierarchy embedding. 

There are also some tasks where generic images are used. These images could be related to obscure images because they lack much information. For example, if face recognition software is run over an image that contains a blurry face, the software could match the unclear image with the high-resolution images of many different people. 

There are several inherent hierarchies in NLP that go beyond to reach the visual region. For instance, you can use hierarchical grouping to visually represent different species of plants. 

Collectively, using hierarchical relations in AI increases the demand for hyperbolic spaces for output embedding. As the volume of Euclidean spaces expands, the resulting expansion is polynomial in nature. However, the expansion of hyperbolic spaces is exponential. This results in the generation of continuous tree analogues. 

This information makes it possible to conclude that the unrevealed hierarchy of visual information can be captured by the expanding hyperbolic output embedding. 

Get an Industry-Ready Artificial Intelligence and Machine Learning Certification

During the certification course you will get the insights of the artificial intelligence and machine learning concepts, latest trends and much more to achieve success in the field.  You can become a part of this global institute by joining our centers in cities like Mumbai, Pune, Lucknow, Chandigarh, Hyderabad, Kolkata, etc. Get in touch with our team by emailing info@imarticus.com to know more about the programs. 

Learn The Reason Why Your Fancy Computer Vision App Isn’t Working

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Learn The Reason Why Your Fancy Computer Vision App Isn’t Working

Computer vision is an aspect of artificial intelligence (AI) that allows computers and systems to extract useful information from digital images, videos, and other visual processes. It can help you make recommendations and take action on the basis of that information. If AI allows computers to think, computer vision allows them to see, observe and comprehend. 

A certification in artificial intelligence and machine learning program like the one by Imarticus will strengthen your basic understanding of artificial intelligence and will help you learn computer vision more efficiently. You can get the best benefits from our experienced mentorship facility and ensure that you get a realistic understanding of artificial intelligence (AI) and machine learning (ML). We also have real-world projects from various industries to help you. Overall, this program can be very helpful for you in exploring gainful career opportunities in artificial intelligence and machine learning which are in great demand. 

Why Might Your Computer Vision App Stop Working? 

As per the experience shared by many users, there is one technical glitch that can often be the reason for your computer vision app not working. It is not a complex theoretical cinder or any GPU-related concern. It is the fact that nearly everyone loads their images into memory sidelong without having a hint about it. And, computers are inefficient in the detection of objects or recognizing games in sidelong images. 

Exif metadata is not regarded as an indigenous component of the JPEG file format. It was more of a second thought derived from the TIFF file format and attached later with the JPEG file format. This maintained reverse compatibility with the viewers of old images, but it only meant that a few programs never analyzed Exif data.  

Most of the Python libraries which work with image data such as Keras, Numpy, Tensor Flow, and Scipy, present themselves as scientific tools to be used by serious people working with generic sets of data. They hardly bother themselves with consumer-related problems such as automated image rotation, even if every image captured with an advanced camera requires it.

This simply means that whenever an image is loaded using a Python library, you will get original and unrotated image data. Are you thinking about what happens if you try feeding a sidelong or upside-down image in an object detection or face detection model? The detector will fail as you have given it bad and useless data. 

Unique AI & ML curriculum – Certification from E&ICT Academy, IIT Guwahati 

By enrolling in this course, you can master the basics of artificial intelligence and machine learning through the most pertinent curriculum planned by E&ICT Academy, IIT Guwahati, and industry leaders. You can create a unique impression on your employers and strengthen your profile with E&ICT Academy, IIT Guwahati endorsed certificate. This globally recognized certificate from one of the most eminent institutions in India will definitely enhance your career.

Campus Immersion By E&ICT Academy, IIT Guwahati 

Get the chance to be a part of a unique Campus Immersion module at E&ICT Academy, IIT Guwahati. This module lasts for three days and it serves as a platform where you can connect with peers and learn AI and ML from the IIT faculty. 

Have you ever imagined the feeling you would have when you acquire analytical skills? This is the objective course that provides you with an opportunity to participate in a top-notch experience of campus education simultaneously learning the practical implementation of AI and ML through live online sessions. 

Learn by First-hand Experience in Real-world Situations 

You can learn what the modern age AI and ML engineers do by solving the issues they face in real life. Industry leaders and experts can make you learn important job-oriented skills through 25 in-class projects which will be based on actual artificial intelligence and machine learning. Grab a chance to participate in a nationwide hackathon to showcase your artificial intelligence and machine learning skills. 

How can you enroll in this AI and ML certification program?

Now that you have known the details of this program, you must be looking forward to getting enrolled in this IIT artificial intelligence course. To get admission, you just need to visit this link and share the details you will be asked for. Imarticus’ team will get back to you and the process will be carried on further. 

So, if you are an aspirant of artificial intelligence and machine learning, then what is stopping you from landing your dream job? Get registered for our certification program and you will have a profound knowledge of AI and ML as well as how you can use them in real-world scenarios. 

The best prediction models that win big this IPL

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The best prediction models that win big this IPL 

The Indian Premier League (IPL) is the most popular and exciting cricket league in the world. There will be ten teams competing against each other this IPL season 2022 for the trophy. Since the start of IPL in 2008, it has grabbed the attention and interest of people from all over the globe. The high level of uncertainty of the matches, and last-minute wins and losses have only increased the viewer count for this cricketing event over the years. And who doesn’t like knowing which team will win that particular match, or even the entire season in advance? Between the matches, you might have also seen a scoreline at the bottom of your television screens showing the winning probability of the two teams. You’d have also seen the probability changing every over for the teams. That is based on the number of runs scored and wickets taken in that particular over. All these predictions are made with the help of data analytics, deep learning, and machine learning. 

Humans cannot analyze extremely huge sets of data, and that is where data analytics and machine learning come into the picture. Predicting the result of an IPL match is a massive work. It includes consolidating the data, analyzing it, and then predicting the result through the number of runs scored, wickets taken, wins and losses of any particular team from the past seasons, and so much more. Imagine the amount of data one would have to analyze for that! Data Analytics makes the work a lot easier.

Data Analytics and Data Science are not rocket science. It only gets easier and more interesting as one starts pursuing it. Doing a data analytics course would help any individual predict the wins of the IPL matches forever! Most of the data science and data analytics courses can also be done online, in the comfort and convenience of one’s own house. Learn Data Analytics online with Imarticus.

STEP-BY-STEP IMPLEMENTATION OF PREDICTION MODEL:

Step 1: Data extraction!

Extract a data sheet that contains all the details of every IPL player from as many seasons as possible.

Step 2: Data cleaning and formatting

Keep the required data sets only.

Step 3: Encoding the categorical data to numerical values.

Encode the raw data into numerical values that make sense to the computer.

Step 4: Feature Engineering and Selection

Divide the data into train sets and test sets before using a machine learning algorithm. Also, scale the data before processing it to make the model less complicated.

Step 5: Building, Training & Testing the Model

Building the correct prediction model using a computer language is crucial. The model can use functions like Sequential and mean squared error, and algorithms like Adam Optimizer, etc. The prediction models can be of a wide range, and multiple kinds of functions and algorithms can be used.

Step 6: Prediction

Create a data frame that shows the actual values and the predicted values. If done correctly, the model will predict the results of the IPL matches at maximum accuracy. It will give almost similar scores. To find out the difference between the actual and predicted scores more accurately, performance metrics will show the error rate using mean_absolute_error and mean_squared_error. 

 Imagine how much time it would have taken us to do all this! But as it can be seen, the above steps in a procedural manner can simplify problem-solving and are generally preferred in the industry. Predicting an IPL match can be as easy for you too! Learn Data Science and Data Analytics courses online with Imarticus. 

7 Benefits of a Supply Chain Analytics Certification That May Change Your Perspective

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7 Benefits of a Supply Chain Analytics Certification That May Change Your Perspective

Introduction

Due to the complexity and growth of supply chain operations as a result of globalization, firms are increasingly adopting analytical standards to improve their decision-making capabilities and supply chain efficiency. A business needs supply chain managers to respond to disruptions efficiently and sustainably if they want to survive a competitive market environment and achieve qualitative improvement.

When catering to ever-changing client expectations, a well-functioning supply chain assures timely fulfillment of goods and services.

There are numerous advantages of incorporating supply chain management into an organization, including lower costs, higher efficiency rates, higher profit margins, higher outputs, and so on. Therefore, companies are continuously on the lookout for personnel who have studied SCM courses and have relevant expertise. In this article, we will go over seven benefits of studying a supply chain analytics course and recommend one of the top SCM courses to start your supply chain management career. 

Benefits of Completing Supply Chain Analytics Course

Studying SCM courses has a number of advantages for both the organization and the employee, some of which are stated below:

 

  • Improve the firm’s profitability

 

One of the most significant benefits of a supply chain analytics course is that it can help a company’s performance and profitability. It aids in the understanding of logistics management, numerous methods for obtaining raw materials, and the best markets for selling goods and services. This allows a company to boost its profit margins and overall sales.

 

  • Well-informed decision-making

 

The need to make well-researched decisions has become critical as the global supply chain becomes more complex. A well-informed decision will help your company achieve its goals of increased efficiency, improved profit margins, and higher sales. People who have completed a supply chain analytics course can identify problems in decision-making and use market data to their advantage.

 

  • Higher employment opportunities

 

Companies are increasingly interested in investing in personnel that can help their company stay on top of market trends, make more informed business decisions, and identify ideal markets to offer their products in. In this regard, those who have completed SCM courses are in higher demand and have more job options.

 

  • Customer Retention

 

A good supply chain analytics course will show you how to build a solid reputation in the marketplace and improve a system’s ability to respond to client needs. It teaches you how to attract new customers and retain existing ones. It also helps in maintaining an efficient flow of services and goods for both companies and customers.

 

  • Keep up with market trends

 

When you study supply chain analytics courses and logistics management, you will learn how to deal with industry trends. Furthermore, you will learn how to deal with client requests. It is always beneficial to keep up with new technology in the market and lead the charge within your company. You can maintain a close check on each new development and provide good communication to clients, vendors, and the firm this way.

 

  • Supply chain management careers

 

After completing a supply chain analytics course, you will be able to work in a variety of areas and supply chain management careers.

  • Supply chain business manager
  • Operations manager
  • Supply chain analyst
  • Purchase manager, and more
  • Proper system implementation

 

 

By taking supply chain analytics classes, you will be able to use the most cutting-edge technology and will benefit from learning how to incorporate this new technology into an organization’s current processes. It helps in proper system implementation, allowing firms to make the best use of technological advancements.

Professional Certification In Supply Chain Management & Analytics Course By IIT Roorkee

The Professional Certification in Supply Chain Management and Analytics was developed in conjunction with IIT Roorkee, CEC, and industry professionals to equip individuals interested in a supply chain management career with cutting-edge experience.

At the operational, strategic, and tactical levels, the Professional Certification in Supply Chain Management and Analytics empowers professionals to make more data-driven decisions. This credential prepares you for high-demand jobs like Supply Planner, Demand Analyst, and Operations Planner, among others.

  • IIT Roorkee will award a certificate to students who finish the Professional Certification in Supply Chain Management and Analytics.
  • It allows you to attend one-on-one mentorship sessions conducted by industry leaders and IIT faculty.
  • It’s the ideal combination of practical and theoretical knowledge for learning new competitive supply chain abilities.

Conclusion

Due to the interrupted supply chain during the epidemic and because of globalization, supply chain management is a rapidly rising sector. The Professional Certification in Supply Chain Management and Analytics is a 6-month SCM course that helps people keep up with market trends, learn vital skills from the IIT Roorkee faculty, and participate in a 3-day campus visit at IIT Roorkee.

Contact us now or visit one of our training centers in Mumbai, Thane, Pune, Bengaluru, Delhi, Chennai, and Gurgaon. 

Here’s why you should learn Python for your first programming language

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Here’s why you should learn Python for your first programming language

Python is a widely used high-level interpreted language known for its ease of use and readability. It was released on February 20, 1991, by Guido van Rossum, who wanted to create a language accessible to everyone. 

There are so many opportunities in the job market for programmers, and Python is one of the most popular languages out there. It’s also relatively easy to learn, which makes it perfect for beginners!

Why Python?

Python is a widely used high-level interpreted language with many modules and libraries, making it an excellent choice for your first programming language. It is easy to learn for beginners due to its simple syntax, and you can use it on Windows, macOS, or Linux operating systems. Additionally, you can use Python in web development, scientific and numeric computing, and software development.

Here are the reasons why you should Learn Python as your first programming Language:

 

  • Python is highly readable

 

Python is easy to read and understand, making it suitable for beginners. Since the instructions are straightforward, there’s no need to memorize complex syntax rules or learn new programming concepts from scratch. As long as you know English, learning Python will be pretty fast since you will spend most of your time understanding the code, not figuring out how to write it.

 

  • Python is versatile

 

You can use Python for various purposes, from developing desktop applications to creating websites and web applications. Python has modules and libraries to do complex tasks with relative ease. It made Python an excellent choice for both beginner and experienced programmers alike.

 

  • Python is one of the fastest-growing programming languages

 

Python has a straightforward syntax for beginners while still allowing developers to write code that runs incredibly fast. 

In addition to its popularity, Python is also one of the most commonly used programming languages in AI and machine learning projects. It means that if you’re looking to get into either of those fields, learning Python is a must. 

 

  • Career-Opportunity

 

 Python skills are sought by employers all across industries, making it an excellent language to learn for career opportunities. Additionally, Python offers a wide range of libraries and modules that ease you to do complex tasks. So if you’re looking for a powerful and versatile programming language, Python is a great choice.

So, there you have it! Four reasons why Python should be your first programming language. It is a universal language that you can use for various purposes, from web development to scientific computing. 

Explore and Learn Analytics Program with Imarticus Learning

Industry specialists created this Machine Learning with Python course to help students understand real-world applications from the ground up and construct strong models to deliver relevant business insights and forecasts. 

Course Benefits For Learners:

  • This Python tutorial is for recent graduates and early-career professionals who want to further their careers in Analytics, the most in-demand job skill. 
  • Students can participate in fascinating hackathons to solve real-world business challenges in a competitive scenario.
  • The case studies cover many aspects of the analytics and python tutorial to help students grasp real-world business challenges.

Contact us through chat support, or drive to one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

How Credit Management courses online are changing the future of Credit Risk Management?

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How Credit Management courses online are changing the future of Credit Risk Management?

The chance of loss, owing to a borrower’s inability to make payments on any sort of loan, is referred to as credit risk. Credit risk management is a means of reducing damage by evaluating the sufficiency of a banking institution’s capital and loan loss resources at a moment.

A strong credit management plan involves a continuous, proactive process of identifying risks, analyzing the probability of loss, and mitigating against the inherent hazards of credit extension. Hence, enrolling yourself in a good credit underwriting training course can give you a fair idea of the aspects associated with it and help you in becoming a successful professional in the field of credit risk management. 

 Here are the elements of successful credit management:

KYC is a regulatory requirement enforced on banks and financial service providers in order to avoid money laundering and terrorist funding. Furthermore, it provides the possibility to construct a full customer profile which, if correctly managed, includes all necessary information required for regular sanction list and PEP screening, as well as periodic credit rating update. Digitization and automation have the potential to significantly increase efficiency, particularly in the KYC and onboarding processes.

Annual financial statements and quarterly reports do give substantial data about a company’s financial position, but obtaining and analyzing this data can be difficult. Slow manual procedures cause credit judgments to be delayed and expenses to rise.

 With artificial intelligence (AI), financial data from financial statements is gathered and allocated to the proper categories using automatic spreading. This implies that all client data is available in a single, consistent format and can be readily processed further.

Many banks still use a ‘one size fits all approach when determining lending terms, which can only be varied from within tight boundaries. As a result, creditworthy consumers must pay a premium to compensate for riskier clients.

 Meanwhile, machine learning has already established itself as the preferred technique for pricing a wide range of financial goods. It can also be put to better use in the loan industry. It enables the borrower’s individual default likelihood and overall repayment performance to be assessed quite reliably. This gives an opportunity for banks and financiers to move away from the traditional fixed pricing system and toward dynamic risk-based pricing.

  How are Credit Management courses online changing the future of Credit Risk Management?

  1. The lending environment, credit underwriting and administration, legal and regulatory requirements, and the influence of technology innovation in credit risk management are thoroughly taught in credit modelling courses these days. This gives students a chance to understand the problems of the real world and solve them efficiently.
  1. A good credit underwriting training course must lay a strong emphasis on digital developments that are disrupting the loan industry.
  1. Many positions have been transformed by ‘big data,’ and credit risk jobs are no exception. It’s a position that’s always been ruled by information, and the more you have, the better tactics you’ll be able to devise. Credit risk underwriting courses these days are making sure that topics like big data are dealt with.
  1. Industry-focused practical curriculum that adheres to globally accepted standards and includes the most recent global trends and best practices are being incorporated in credit risk underwriting courses online, which give them an environment to deal with real-world problems and solutions.

Conclusion

Risks are an unavoidable part of banking operations, however, that doesn’t indicate they can’t be reduced. Commercial banks and private lenders must lower the risk of fraud and cybersecurity risks on a regular basis in order to secure their clients’ financial data; they must also protect their treasury from untrustworthy borrowers. Even if the security is accepted, the time and money necessary to convert it into dollars may result in a negative return for the lender. This is the primary reason why financial institutions extensively assess each borrower’s credit risk. 

Unleashing the Potential of a Supply Chain Analytics Certification

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Unleashing the Potential of a Supply Chain Analytics Certification

Supply chains form the heart of the working of all organizations. It involves the flow of goods and services from the origin point to the consumption destination. However, intense global competition has made these networks complex, generating a massive amount of data. Supply chain analytics works on this data to uncover patterns and generate actionable insights to maximize efficiency and profitability.

Supply Chain Management training has been in demand to keep up with supply chains’ new trends and challenges. Undertaking a Supply Chain Management Certification Online (SCM Certification) course has helped upskill employees, contributing to enhanced logistical and decision-making capabilities. However, one must find the right fit with multiple certifications.

Why is Supply Chain Analytics important?

The significance lies in integrating supply chain management training and data analytics for data-driven, innovative, and result-oriented decision-making. Some critical benefits include:

  • Improvement of profitability

Incoming data from multiple sources provides real-time insights into pain points and drivers to enhance cost efficiency, establish competitive advantage, and maintain proper inventory levels.

  • Risk management

Supply chain analytics also helps discover patterns to predict risks and trends for a planned approach to tackling them to avoid disruptions or breakdowns.

  • Developing value for the customers

Another critical aspect of Supply Chain Management Training is big customer data, which provides a predicted map of future demands. A better analysis provides a better prediction and will help improve organizations’ response to changes in demand patterns and better service to customers. 

  • Implementation of a proper system

Data and its associated analysis will help incorporate new technologies for streamlining supply chains, reducing costs, optimizing product cycles, and improving the operations of businesses. Such a system will be resistant to cyber-intrusions, automated, and comprehensive. 

Why is Professional Certification in Supply Chain Management & Analytics needed?

Professional Certification in Supply Chain Management & Analytics is a professional certification provided by DoMS and E-learning Centre, IIT Roorkee – helping build conceptual understanding and providing industry-oriented exposure. Professionals will be able to learn the following:

  • Recent trends in the supply chain, including analytics
  • Supply chain strategies and their responsiveness and efficiency
  • Drivers and metrics of supply chain performance
  • Ability to design global supply chain networks along with network optimization
  • Introduction to Python programming for forecasting in supply chain
  • Implementation of sales and operations planning in real scenarios
  • Understanding and managing uncertainties in the supply chain
  • Determination of optimal levels of product availability and improving supply chain profitability 

What value addition will the Professional Certification in Supply Chain Management & Analytics certification bring?

  • Cutting-edge curriculum designed by the E-learning Centre in IIT Roorkee to help master the basic fundamental concepts and industry-required skills in analytics
  • A certification from IIT Roorkee provides the advantage of learning from the best faculties
  • Engaging live sessions from industry experts and distinguished trainers will help professionals to apply theoretical concepts practically
  • A campus immersion experience at IIT Roorkee will provide an opportunity to interact with peers and IIT faculty
  • A hands-on approach to solving real-industry issues that will help in understanding the business context of concepts and sharpening skills
  • Mentoring sessions from industry stalwarts
  • Career development sessions and career assistance services like resume building, interview preparations, placement opportunities, etc.

Final Words

Professional Certification in Supply Chain Management & Analytics designed by IIT Roorkee allows learners to take a leap in their careers. The certification enables professionals to secure heavily demanded job roles like demand planners, supply planners, data scientists, etc.

For further queries, contact Imarticus Learning through chat support or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

Enabling a Smarter Technology with Machine Learning Courses

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Enabling a Smarter Technology with Machine Learning Courses

Machine learning has become more prevalent in enabling smarter technology in a technology-driven era. Many renowned companies worldwide heavily invest in machine learning technologies for an Artificial Intelligence (AI)-powered manufacturing process.

For instance, AI and machine learning have reduced labor costs and downtime with the industrial IoT. In addition, many companies have experienced better quality control with the advancement in machine learning. 

Today, you can grab many opportunities by polishing your skills in this field. According to O’Reilly’s Machine learning Adoption Survey, job titles related to machine learning are widely used in organizations: data scientist (81%), machine learning engineer (39%), and deep learning engineer (20%). Whether you opt for a post-graduation in machine learning or seek deep learning training, let us become more familiar with the industry. 

5 Ways Machine Learning Courses Help You Enable Smarter Technology

Here are a few examples of machine learning implementations that enable smarter technology.

Product Development

Planning and designing new products and updates usually requires extensive research and information, which can be time-consuming, thereby affecting the final product. In this phase, machine learning is chiefly implemented and helps you yield potential results. 

It helps gather customer data, analyze it to meet customer demands, and find business opportunities. Moreover, machine learning can help execute a flawless evaluation of the risk of developing new products. 

Smart Manufacturing

Another significant impact of machine learning is the daily improvement of processes throughout the manufacturing cycle. This technology has helped manufacturers detect their weak points, such as bottlenecks, unprofitable product methods, etc.

With better data analysis and IoT, manufacturers could develop efficient production methodologies and take an in-depth look into inventory, assets, logistics, and supply chain management. Thus, a data analytics course with placements can help you understand how the analysis works and supports the overall production line.

Quality Control

Machine learning helps improve quality control in two ways. First, it can easily find defects in the final product and packaging. Second, one can use machine learning to increase the quality of the manufacturing process, thereby laying a solid foundation considering the quality aspect. With this automated testing process, manual processes and errors can be avoided, requirements can be predicted, and fast and reliable answers can be obtained.

Cybersecurity

With the increasing cybersecurity concern of the digital world, machine learning has come to the rescue. This is because most apps and devices are dependent on on-premise platforms, operating systems, cloud, networks, and applications. Fortunately, with the Zero Trust Security (ZTS) plan, you can easily regulate and control users’ access to data and information.

Robots

Eventually, companies are using their best machine learning techniques to approach the innovative technology of robots. Robots are quite helpful as they can handle dangerous tasks that humans cannot. With a fast pace of innovation, robots nowadays use their machine learning technologies and capabilities to efficiently tackle complicated and complex processes, quickly surpassing the outdated thresholds. Furthermore, industrial AI-powered robots are more aware of people and surroundings.

Final Thoughts

With excellent solutions and practical applications in today’s world, machine learning plays a crucial role in enabling smarter and better technology. If you are planning to boost your technology career by pursuing machine learning courses, a post-graduation in machine learning can help you.

We at Imarticus Learning provide professional courses that make you industry-ready. Choose from a range of technology, finance, data analytics, and marketing courses that offer top-tier collaborations, qualified faculty, and more! 

Contact us today or visit your nearest training center in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

The 6 Computer Vision Techniques That Will Change How You See The World

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The 6 Computer Vision Techniques That Will Change How You See The World

Computer Vision is a branch of artificial intelligence. Computer vision involves the automated extraction, analysis, and understanding of useful information from images and videos using computational methods. 

It has many applications in daily life like image recognition, image processing, video processing, etc. This blog post will discuss five computer vision techniques that will change how you see the world.

Face Detection

Face detection is the process of finding faces in images and is a subset of image classification, applying computer vision and machine learning. It is a critical component in facial recognition and other computer vision applications like object tracking, scene understanding, etc.

Facial Recognition

Facial recognition is a type of biometric authentication. It’s used in security systems to identify people, and it’s also integrated into social media platforms like Facebook and Snapchat.

Facial recognition is also a hot topic in the advertising industry. These industries use real-time emotion analysis to help advertisers better understand what kind of ads consumers respond to best.

Image Classification

Image classification is classifying an image into one of several categories. For example, you can build a model that will be able to classify images as “cat,” “dog,” or “bird.” You can then use this model to identify pictures labeled as cats and dogs on the internet.

Image classification is significant for pattern recognition problems and object detection because it allows computers to understand what’s in an image by implementing machine learning techniques.

Semantic Segmentation

It is the task of assigning each pixel in an image to a class. For example, given a picture of a kitchen, semantic segmentation allows you to label every pixel with such information as “ceiling,” “floor,” or “stove.” If that seems easy enough for you, keep in mind that this process is not as simple as it sounds.

Segmentation requires the detection of object boundaries and their classification using machine learning algorithms like neural networks. One popular way to do this is by using convolutional neural networks (CNNs). CNN’s are particularly effective at finding boundaries between objects because they can learn patterns from visual data without prior knowledge. They do this by mapping out where pixels belong relative to one another to make more accurate predictions on what’s happening within the scene getting analyzed.

Object Tracking

Object tracking is the process of automatically following a moving object through a video. It’s useful for surveillance, sports, and other applications.

The two main types of object tracking are active and passive. Active object tracking uses a target-detection algorithm to detect objects that move in front of the camera, while passive object tracking tracks objects by analyzing changes in pixels over time (i.e., motion blur).

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