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

Posted on by Imarticus Learning

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).

Learn Machine Learning and AI courses with Imarticus Learning.

This deep learning Artificial Intelligence credential brings together the E & ICT Academy, IIT Guwahati, and the most prominent industry specialists. This AI course will help students prepare for careers as data scientists, data analysts, machine learning engineers, and AI engineers.

Course Benefits For Learners:

  • Students can now participate in 25 real-world projects to get industry experience and prepare for a fascinating future in data science.
  • Impress employers and demonstrate your talents with an E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed certificate.
  • This IIT artificial intelligence course will help students land lucrative jobs in the disciplines of artificial intelligence and machine learning.

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

Covid-19 Data Analysis Using Tableau

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Covid-19 Data Analysis Using Tableau

Tableau is a fast-growing data visualization and data intelligence software used worldwide to drive better data-driven decisions. Dynamic software manipulates updated data as and when it is introduced into Tableau. A simplistic description of Tableau is a pivot table on steroids. But Tableau is so much more than Excel and other software available in the market for analyzing data. 

Today Tableau is at the forefront of data analysis with millions of users globally. Apart from its advanced features, interactive dashboards have the facility to import data from different data systems like Python and R. 

To be up-to-date on data analysis, get a Tableau certification by doing a Tableau course or a data science course in India at Imarticus Learning.

The Covid-19 epidemic has devastated the whole world and resulted in many deaths. It transcended national borders and attacked citizens of all countries without discrimination. 

Many countries maintained a daily tracker of Covid-19 patient statistics to take appropriate action regarding lockdowns, curfew, treatment plans, ensuring availability of medical and health care facilities, availability of oxygen, vaccine production, emission, etc. Tableau software has been handy for all the data at a global level and facilitated decision-making by the governments of the respective countries.

Tableau helped government health organizations and companies in data analysis during the Covid-19 epidemic. Given below is the use of a Tableau to track the progress of the Covid-19 epidemic in the U.S.

Tableau workday data file was used.

The Tableau workday data file was used with Tableau Prep Builder and data from John Hopkins to represent a dynamic data representation. The above is a static view of the Tableau Dynamic Prep Builder. A survey of work from home employees, which was administered on the Salesforce platform, is represented below:

Filters were used to enable analysis by employee’s region, quota responsibility, and previous work experience from home.

Tableau launched the Datahub to make sense of the Covid-19 data.

In India, Covid-19 data was analyzed using Tableau. The analysis of the data focused on the following key data points:

  1. The timeline of the spread in the country
  2. The primary reasons for the spread and the various government responses to it.
  3. Analysis of research and development.
  4. The number of Covid-19 tests carried out and analysis of the same. 

To be up-to-date on data analysis, get a Tableau certification by doing a Tableau course or a data science course in India at Imarticus Learning.

Timelines were plotted, charting the return of tourists from Wuhan and the return of tourists from Italy. The various events which led to the congregation of people were all charted.

Most of the reasons for the spread were the various religious congregations in the country belonging to different faiths. This led to the peaking of the Covid-19 cases, as shown in the above chart.

Government responses can be classified as under:-

  • Thermal screening of patients returning from abroad. This was gradually extended to the various airports in India.
  • By Mid-March, containment measures were introduced to prevent spread through contact.
  • By 22nd March, lockdown measures were introduced in 22 states, followed by inter-state movement restrictions. The gradual nationwide lockdown was also introduced. The data graphs in Tableau show rapidly increasing numbers of Covid-19 patients resulting in further extensions of the lockdown.
  • Research and treatment: India fared better compared to the rest of the world, as shown in the Tableau graph below:
  • Many government facilities such as the DRDO and ISRO started producing protective equipment, PPE suits, and ventilators to fight against Covid-19. Gradually other Public and private sector enterprises were also drawn into the production of equipment to protect against the Covid-19 epidemic.
  • Testing: Covid-19 testing was gradually extended to cover significant population proportions. All pneumonia cases were included in the ambit of testing.

 The testing ambit was gradually widened to include broader testing in all the hotspot areas. The graph below shows the confirmed cases contrasted against the number of deaths in India.

Some of the important takeaways from the above exercise were:

  • Data from Tableau graphs and data visualization models were used for public decisions.
  • The data visualization models were used to communicate the immense scale of the tragedy in a way that mere numbers could not.
  • The summary statistics mask inequalities between regions, states, and groups of people.
  • The data collection itself was a very complex exercise.
  • One measure from the data charts or visualization exercises does not tell the complete story. Many measures had to be taken together to tell the complete story of the progress of the Covid-19 epidemic.
  • Rapid developments of Covid-19 charts happened at the expense of accessibility. The Tableau statistics and graphs were not accessible to those working on the ground.  

 To be up-to-date on data analysis, get a Tableau certification by doing a Tableau course or a data science course in India at Imarticus Learning.

Visit Imarticus Learning to learn more. Contact us through chat support, or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

6 Trends Shaping the Future of Data Science

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6 Trends Shaping the Future of Data Science

Introduction

The data science industry is rapidly evolving. The field is changing from the types of data collected to the tools and techniques used to analyze it. More and more companies are using these insights as part of their business strategies. As the world becomes more digitally adept, data scientists are in high demand to help businesses make sense of the information they collect.

At Imarticus, we offer data science courses as we are always on the lookout for what’s next in this rapidly changing future of data science. 

Here are six predictions for trends shaping the future of data science:

1. Data Collection Becomes More Ubiquitous

As companies become more comfortable with data to improve their business performance, they will likely collect more data about their customers and employees. In particular, we expect to see an increase in the amount of location-based information that companies collect about their customers’ movements (and even their emotions).

We are still in the early stages of understanding how to use data to make better decisions, but we are beginning to understand which best practices are most effective. For example, there’s a growing consensus that it’s essential to train your models on as much data as possible—not just large datasets but a variety of datasets representing different data types and problem areas.

2. Data Scientists Become More Valuable

As companies start collecting more data types, they’ll need to hire people who can help them make sense of it all. They will be willing to pay top dollar for those people because they know how important it is to access insights from every corner of their organization. There will also be an increased demand for people training in applied statistics or machine learning to apply those skills broadly across all areas. 

Data democratization: Data scientists are not just going to be working in corporations anymore—anyone with an internet connection can harness the power of data science.

3. The Internet of Things 

IoT is already changing/defining how we interact with our environment, and it will continue to change how we interact with data. As our physical world becomes increasingly connected, we can analyze our surroundings better and understand what they mean.

4. Machine learning

ML is becoming more accessible than ever before. Thanks to cloud computing and powerful open-source tools like TensorFlow and Keras, even non-coders can create powerful models without needing a Ph.D. in mathematics or computer science.

Additionally, there is a growing awareness regarding the importance of machine learning algorithms that can handle complex tasks with no human-defined solution. It means creating systems that can learn from their users’ behavior over time and use this information to solve new problems. It is similar to how Google Search knows what you want when you type in “tacos” or “puppies” while providing recommendations based on your previous searches.

5. Deep learning

Deep learning helps us understand language at a deeper level than ever before. By analyzing a text at various levels—from individual words up to sentences, paragraphs, and entire documents—we can extract information that would otherwise be impossible to find using traditional keyword search or keyword matching algorithms.

6. The growth of Big Data

As more people start using personal data to make discoveries, we’re going to see a lot more information about human behavior emerging—and as it becomes easier for people everywhere to collect this information and share it with others, we’ll see even more discoveries made through crowdsourcing efforts than ever before.

The future of data science will also be shaped by developments in automation technology, including AI assistants like Siri or Alexa. These technologies allow us to interact with computers in new ways. For example, they can understand natural language input like commands or questions and provide answers quickly without requiring us to learn programming languages.

Conclusion

The future of data science is an exciting one. We’ve already seen some incredible advancements and more to come. Now is the best time ever to enrol in data science courses and build a career for a digital future.

Imarticus learning offers a Certificate Program in Data Science and Machine Learning to guide and train you with the best resources to prepare you for this data journey.

Get in touch with us and find a detailed analysis of how this program can potentially revamp your career. Contact us through chat support or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon for more information.

Learn Python Online: Things that non-programmers must know

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Learn Python Online: Things that non-programmers must know

The developer of Python, Guido V Rossum, created it as a hobby project back in 1989. Today, Python has become one of the few official programming languages of Google due to its ease of use paired with efficiency. Python won the position of most popular programming language in 2020, as put forward by a joint survey of Google Trends and GitHub. In terms of programming language usage by global developers, Python has secured the third position in 2021, following JavaScript and HTML/CSS. Are you a non-programmer? Then Python can be your ideal starting point. And, here are a few things that you should know about this programming language.

Python: What is it?

It is an object-oriented, high-level programming language. It is a general-purpose, interactive programming language, the name of which is based on Rossum’s favorite TV series, “Monty Python’s Flying Circus.” The language is known for its versatility and simplicity, making it ideal for beginners and non-programmers.

What are the features of Python? 

Do you want to learn Python? Here are a few features to know about.

It can be integrated: 

Python can be integrated with an array of programming languages like C, C++, and Java.

Python is interpreted, and interactive:

Python can be processed by interpreters while they run it and a learner does not need to compile the program before execution. It is interactive because you can interact with the interpreter directly.

It is object-oriented:

Python is an object-oriented programming language and has code reusability. Designing an application with Python is easier with minimal coding.

Ideal beginner’s language

Python is characterized by the simplicity of structure, clear-cut syntaxes, and less number of keywords, thus making it simple to learn for any non-programmer. Furthermore, it is an open-source software freely accessible to all.

Why learn Python?

Tons of career opportunities:

The popularity of Python has contributed to the rising demand for Python programmers. Certification in data analytics can promise you an array of career choices.

Active community:

Program learning is not a solo sport. A massive community for providing the required learning support is vital to proper learning. Python has a considerable community backup which helps non-programmers in their learning.

Highly versatile:

It is a highly adaptable programming language that is used in multiple fields like web development, data science, software designing, and gaming. Python’s versatility is further enhanced by its ability to sync with a variety of other programming languages. Thus, it is a ‘cross-platform’ language.

Which fields use Python?

Python’s simplicity and ease of use have granted it access to a variety of fields like:

  • Web applications
  • 3D CAD-based applications
  • Software development
  • Auditory applications
  • Machine learning
  • Visual applications
  • Artificial intelligence

 Tips to keep in mind

Now that you know what Python is and what its features are, here are a few tips to keep in mind before opting for certification in data analytics:

  • Being consistent in code-making always helps to learn better. Are you making mistakes in coding? They are the stepping stones to your proper learning. So, code every day!
  • An interactive Python shell can be your ideal learning tool.
  • Opt for the pair programming technique, where you will pair with another developer. This way, you both will switch between writing codes and reviewing and problem-solving. Now, you can learn both sides of Python.
  • Opt for data analytics certification courses online, which can offer you the best possible resource to learn Python faster.

Conclusion

Are you looking for data analytics certification courses online? If yes, then you must check out the one offered by Imarticus Learning. With a fully online learning mode, this course is ideal for future data science experts and is backed by case studies, real-life business projects, and mentorship sessions.

Beyond The Hype: Learn Computer Vision

Posted on by Imarticus Learning

Beyond The Hype: Learn Computer Vision

Computer Vision is a subfield of artificial intelligence. One day it’ll be our go-to method for identifying objects and faces in the world around us—one way or another, if you’ve ever tried Google Photos’ facial recognition feature, it’s where computer vision work. It uses mathematical models to identify people’s faces in images (and tag them automatically). This blog post will explain what computer vision is and why you should learn it.

Why should you learn computer vision?`

It’s a highly sought-after skill, and it’s easy to understand because computer vision is a practical skill that you can use in real life. Not only that, but it’s also an interesting subject matter with lots of potential for growth and development. 

Some apps already use computer vision we use every day—like Snapchat filters, which use face-tracking technology to make you look like a cat or dog when taking photos with friends.

What is the application of computer vision?

You can use computer vision in countless applications, including:

  • Image recognition involves the ability to identify objects or scenes within an image, as well as the ability to track things over time. In the coming years, you could use these technologies in retail stores where customers can scan their items at a self-checkout station and then be billed immediately by their mobile phones—no need for cashiers!

  • Image classification involves categorizing images into different groups according to what they depict (e.g., dog vs. cat) or what part of the human body they represent (e.g., face vs. hand). For example, Amazon uses image classification algorithms on its website to automatically understand which products are shown in each image so that when you search for something similar online. It can give you suggestions based on previous searches made by other customers who clicked through from Google Images links before coming back later with those same results still ready for consumption! 

It also helps retailers build better recommendation engines based on user feedback after making purchases or browsing various pages on eCommerce sites like Amazon’s own interface. But these systems aren’t perfect yet because they require millions upon millions of training data points before making accurate predictions about new ones that may contain unusual patterns not seen before. 

How can you start learning computer vision as a beginner?

There are many resources for learning about computer vision. The best way to start is by understanding the basics of computer vision and then learning about the different algorithms used in computer vision. You can also learn how these algorithms work.

You can use many resources to learn more about computer vision, including books and online courses.

Learn AI and Machine Learning courses with Imarticus Learning.

This deep learning Artificial Intelligence credential brings together the E & ICT Academy, IIT Guwahati, and the most prominent industry specialists. This AI course will help students prepare for careers as data scientists, data analysts, machine learning engineers, and AI engineers.

Course Benefits For Learners:

  • Students can now participate in 25 real-world projects to get industry experience and prepare themselves for a fascinating future in data science.
  • Impress employers and demonstrate your talents with an E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed certificate.
  • This IIT artificial intelligence course will help students land lucrative jobs in the disciplines of artificial intelligence and machine learning. 

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