Contact Us
×

Category: Analytics

7 ways through which you can learn full stack web development

Posted on by Imarticus Learning

A full-stack developer is someone who knows all aspects of a project. They can design, build and market everything from scratch. A full-stack developer can also work on multiple projects by dividing their responsibilities. This post will discuss seven ways to learn full-stack web development.

What is a Full-Stack Developer?

full stack developer course

A web programmer who builds websites and web applications from the ground up is known as a full-stack developer. These experts can specialize in both back-end and front-end web development, and to create a complete website, they need to be knowledgeable in programming tools and languages. 

Front-end development deals with creating a website’s aesthetically pleasing and usable elements, whereas back-end development deals with creating the databases and supporting infrastructure for a website.

How To Become A Full-Stack Developer?

  • Online Courses

An online course is the best way to learn full-stack web development. They allow you to learn new skills quickly. The best part about online courses is that they can be completed on your own time–no need for travel or a classroom setting! 

  • Bootcamps

Bootcamps are a great way to learn full-stack web development. They’re also a great way to learn to program quickly, and they can give you what you need to enter the industry or change your career path. Students will have access to knowledge and mentorship from experts in their field who have already built successful businesses. 

This allows you to get up-to-speed quickly on all things related to coding and gives you confidence and connections with people who can help you move forward once graduation has finished!

  • Study the basic programming languages.

Depending on the project’s needs, a full-stack developer may use different programming languages like JavaScript, SQL, and Python. You can build websites using a variety of patterns and concepts if you are familiar with these front-end applications. You can lay a solid foundation by being proficient in languages like HTML and CSS. You can learn these languages by registering for a beginner’s course, building programs using templates, and watching instructional videos on social media websites.

  • Self Learning

Self-learning is a good way to learn, and it’s also a great way to stay up-to-date on new technologies and languages. You can learn all of this on your own time!

  • Networking and Collaboration

The most important way to learn full-stack web development is by networking with other developers and getting their feedback on your work. You can also collaborate with other developers and try solving problems together. This will help you improve your skills as a developer because understanding others’ points of view is a significant aspect of being a good programmer.

  • Practice and Consistency

As you move along in your learning process, it’s important that each time you learn something new, you try to apply it as well. It’s easy for people who haven’t learned anything about the field to think that their skills are complete if they’ve learned how to build websites using HTML and CSS. 

But this isn’t true–there is no such thing as a full-stack developer! You have to keep learning new things so that when someone asks, “How do I solve this problem?” or “What framework should I use?” or even “What programming language should I learn next?” You can confidently answer those questions because now you know all about these topics.

  • Continual Learning and Growth

Continual learning is the key to success in any industry. It’s important for you to always be on the lookout for new opportunities and learn from them so that you can adapt to new situations or challenges. To keep growing as a developer, it’s also necessary that you learn from your mistakes–and other people’s mistakes as well! 

Learn data structures and algorithms with Imarticus Learning.

Our Full Stack web Development certification course will teach students database architecture and algorithms. During this six-month full stack developer online course, students will learn data structure algorithms and the technical facets of front-end and back-end programming.

Course Benefits for Learners:

  • As part of our career services, we offer resume writing, profile improvement, workshops to help students prepare for interviews, and one-on-one career counseling. 
  • While learning well-known tools like Java, Spring, MongoDB, JavaScript, React, Docker, and Jenkins,  lay a strong foundation in data structures. 
  • With the help of our community project Skillenza, students can now compete in coding challenges to solve complex business problems and stand out on resumes.

Top 8 data science roles in the field of data science

Posted on by Imarticus Learning

Data science is one of the hottest topics to talk about these days, evident by the number of job boards that mention data science as one of the top skills hiring managers seek. As such, there’s a lot of demand for data scientists, so you’ll find many roles across different industries and companies. 

Big Data Analytics Course

A data scientist can keep your business one step ahead by spotting trends, forecasting outcomes, and making data-driven decisions that boost performance. Hire a data scientist right away to take advantage of the opportunity to harness the power of data!

Let’s start by investigating the top 8 Data Science roles!

Data scientist

A data scientist examines data to uncover useful information. One example of a specific task is finding the data-analytics issues that present the organization with the most opportunities—choosing the appropriate variables and data sets.

Data Analyst

Data analysts use tools for data analysis to examine information, and they work with their teams to generate insights and develop business strategies. You will need proficiency with tools for data analytics and data visualization, as well as math, statistics, communication, and working with data. 

Machine Learning Engineer

Machine learning involves training computers to make decisions independently. It’s a crucial part of the field of data science and can be used to solve many problems in business, science, and engineering. Even though machine learning has been around for a while, its significance is only growing as more businesses start incorporating it into their goods and services.

Data Engineer

Data engineers are a crucial part of the data science team. They design, implement and maintain the infrastructure that enables data analysis. They usually work closely with their colleagues in other departments, such as software development or analytics teams, to ensure that all processes run smoothly.

Business Intelligence Analyst

Data science is a field that encompasses many different types of roles and disciplines. For example, business intelligence analysts focus on doing this effectively; they must understand what makes up a given dataset before working with it.

They might also be called BI developers or BI architects if they are responsible for building new features within their company’s existing reporting systems using SQL databases and NoSQL databases. These experts will also work closely with their team members to ensure that all their processes are aligned with the company’s goals–and since these professionals are often in high demand across industries like retail & hospitality services too!

Data Architect

A data architect is responsible for designing, developing, and maintaining the data architecture of a business. The job of a data architect is to design a system that can efficiently handle large amounts of information. They create a structure of databases, tables, and fields to store your company’s data to perform analyses on it. 

Data architects also ensure that they have good quality control measures in place so they don’t end up with incorrect information in their systems when trying to use them for analysis purposes later down the line.

Data Visualization Engineer

Data visualization is a significant part of data science. It’s transforming raw, unstructured data into information that people can easily understand. Data visualization is also used to create and present information in a way that makes it easy for people to understand.

Data scientists are expected to create visualizations from their research findings and use them to communicate with colleagues and clients alike. Data engineers help create these visuals by building tools like graphs or charts that display relevant data points from different sources.

Statistician 

A statistician is someone who, as the name implies, is well-versed in statistical concepts and methods. In addition to extracting and providing priceless insights from the data clusters, they also aid in developing new methodologies that engineers can use.

Explore your Career in Data Science with Imarticus Learning!

This Data Science certification Course promises to assist you in realizing the full potential of data science and creating models with the greatest possible business impact. This program offers a practical approach to understanding how analytics can drive real results in a business setting, whether you are a recent graduate or an experienced professional looking to advance your career in analytics.  

Course Benefits for Students:

  • Students can study the data science course without ever leaving the comfort of their homes.
  • Gain hands-on experience with data science and analytics codes.
  • PG in Data Analytics Certification provides students with a thorough theoretical and practical understanding of data analytics.

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

How machine learning and analytics have evolved as a career?

Posted on by Imarticus Learning

Data science is the complete range of activities that encompasses artificial intelligence, machine learning, and deep learning. It applies mathematics, statistics and linear algebra to create algorithms that solve diverse business and operation issues in multinational organizations and start-ups alike.

Artificial intelligence is the ultimate goal to be achieved. The very basic purpose of it is to make machines think and act like humans. Artificial intelligence is achieved through machine learning and deep learning techniques. In present times, a career in data analytics and machine learning is seeing an upward trend. 

The Concept of Data Analytics

The foundation of data science is plenty of historical data. Data may be gathered from various sources. Sometimes the organizations provide their own past data along with the data of their competition, if available. Sometimes, the analyst has to gather the data from several resources such as websites and relevant social media or e-commerce platforms. These collected data are raw and need to be cleaned, filtered and segregated. The job of the analyst covers all these activities and then applying proper algorithms to the same.

The knowledge of a programming language like Python or R is essential at this stage. While Python has its own set of algorithms that may be directly applied and thus recommended for beginners, R is an advanced language which will enable the analyst to create his or her own algorithms to extract meaningful insights from the data. When all these activities are complete, the analyst then applies visualization tools like Power BI or Tableau to transform these data into easily understandable pie and bar charts. The sole purpose of all these activities is to enable the management to take important business decisions regarding its products, services and much more.

The Concept of Machine Learning

machine learning course

When we read a machine to respond to situations in a way that a human would have done under similar circumstances, we achieve the purpose of machine learning. Machine learning is generally of three main types – supervised learning, unsupervised learning and semi-supervised learning. 

  • Supervised learning is the process of feeding labelled data as inputs so that the machine may respond to similar situations as per the input conditions. The inputs may be text, images, videos etc. 
  • Unsupervised learning is the case where there will not be any labelled data, but the machine will be programmed to read and draw useful insights from the data they get. This technique is used in clustering group data. 
  • Semi-supervised learning is a mixture of the above two. Deep learning is an advanced form of machine learning where the machine is made to mimic a human brain. 

It is universally true that humans learn from the pages of history. History consists of past data. In earlier days, the quantity of this data was small, and it could be easily managed over manual accounting or, at a later stage, over a simple Excel sheet. Business and Operation Managers made the best use of these historical data to make future decisions. However, with the passage of time, the volume of data has changed, and so has the method of record keeping and analysing. Start-ups and big companies alike need data to predict their next business moves. They would like to know which products and services would remain relevant in business and which ones will fade out. They would also like to know the potential a particular business will have in the next financial year or further ahead. This demand has evolved analytics as a key career subject with the present-day young job searchers.

Similarly, machine learning also has its own application domain. We are privileged to the benefits of robotics. Machine learning has other applications in different services. For instance, a reputed spectacles merchant often uses this technique to enable its customers to understand which frame would best fit their face contour. A user of a social site is often recommended as per his or her earlier choices. 

Course Details of Machine Learning And Data Analytics

The contents of the Data Analyst training course are very similar to those that are covered during Machine Learning as well. The courses are available in both online and offline modes. However, it is important for an aspiring candidate to join a reputed institute with credibility among employers. Furthermore, students should choose those courses which give them ample opportunity to enhance their practical experience with projects. The following topics are generally covered in data analytics certification courses –  

  • Advanced Microsoft Excel, basic mathematics, statistics, and linear algebra. 
  • Data analysis and project cycle life.
  • Techniques of evaluation, exploration, and experimentation.
  • Segment analysis using clustering and method of prediction.  
  • Data visualization with Tableau or Power BI.
  • Analytics and recommender systems. 

Both of these subjects have evolved as very demanding careers amongst the present job-seekers. A prospective candidate can learn data analytics from the postgraduate program in data science and analytics course taught at Imarticus. The duration of the course is 6 months. This course will help you achieve your dream and establish a career in sync with present requirements. 

10 best tools that lead machine learning projects

Posted on by Imarticus Learning

The world of machine learning is always expanding and changing. As such, there are many tools to aid you in your quest for knowledge. 

Most likely, you already have some knowledge of machine learning and its potential to revolutionize industries. But when it comes down to building a successful project, there’s no escaping hard work, expertise—and picking the right tools.

Data Science Course

The size of the machine learning market has been rising steadily. The deep learning software category, expected to reach almost $1 billion by 2025, is the most significant subsegment of this market. According to recent machine learning market research, the demand for AI-enabled hardware and personal assistants is anticipated to grow rapidly.

The following list offers 10 of the best tools for machine learning projects. The selection is based on their usefulness and versatility in various contexts, including training models, deploying them at scale and analyzing data.

TensorFlow

Google Brain’s engineers and researchers initially created an open-source machine learning framework called TensorFlow. The library was initially created for ML and deep neural network research. 

Sklearn

One of Python’s most well-liked and reliable tools for carrying out machine learning-related tasks is sklearn (also known as scikit-learn), first created by David Cournapeau in the 2007 Google Summer of Code (GSoC) program. 

Shogun

Shogun is an open-source machine-learning framework built on C++. It offers a broad range of complete machine-learning algorithms that are both efficient and optimized. Support vector machines are among the kernel machines in Shogun that are used to address regression and classification problems.

Colaboratory

Google Colab, also known as Colaboratory by Google, is a free cloud computing platform for data science and machine learning. It eliminates any physical restrictions that might exist when using machine learning models. Run complex models and algorithms. 

Weka

Weka (Waikato Environment for Knowledge Analysis) is an open-source toolkit that can be used to create machine learning models and use them in practical data mining scenarios. It is available under the GNU GPL (General Public License) and includes tools for data preprocessing, the implementation of numerous ML algorithms, and visualization.

IBM Cloud

More than 170 products and cloud computing tools comprise the entire IBM cloud services stack for business-to-business (B2B) organizations. Like many other all-encompassing cloud computing services like AWS, Microsoft Azure, and Google Cloud, IBM Cloud includes all three of the primary service models (or varieties) of cloud computing. 

Google ML kit for Mobile

Google offers the ML Kit to mobile app developers with machine learning know-how and technology to build more reliable, optimized, customized apps. This toolkit can also be used for barcode scanning, landmark detection, face detection, and text recognition applications. It can also be used for offline work.

Apache Mahout

The Apache Software Foundation’s open-source project Apache Mahout is used to creating machine learning programs primarily focusing on linear algebra. With its distributed linear algebra framework and mathematically expressive Scala DSL, programmers can quickly implement their algorithms. 

Amazon Web Services

Amazon Web Services has a wide range of machine learning services. For companies and software engineers, AWS offers a wide range of tools and solutions that can be used in server farms across more than 190 nations. Government agencies, educational institutions, NGOs, and companies can all use the services. The end-users needs can be taken into account when tailoring its services.

Oryx2

Built on Apache Kafka and Apache Spark, it is a realization of the lambda architecture. For large-scale, real-time machine learning projects, it is frequently used. It also serves as a framework for creating apps, including complete packages for filtering, regression analysis, classification, and clustering. 

Learn Data Science and machine learning with Imarticus Learning. 

 Do you want to improve your machine-learning abilities? Certificate Program in Data Science and Machine Learning from IIT Roorkee is now available!

Start your journey with iHUB Divya Sampark from IIT Roorkee! As you build on the fundamentals, our esteemed faculty members will instruct you on crucial ideas like mining tools and how to apply insights to create practical solutions using Python programming.

 Course Benefits For Learners:

  • In this IIT Roorkee machine learning certification course, learn from renowned IIT faculty and gain a fascinating perspective on India’s thriving industry.
  • You will have the advantage you need to advance your career in the data science field with the help of our data scientist careers.
  • Learn the fundamentals of AI, data science, and machine learning to build skills that will be useful in the present and the future.
  • With the help of our IIT Roorkee data science online course, you can give yourself a career edge by learning about cutting-edge technology that will lead to amazing opportunities.

How SQL and Excel are right for tableau

Posted on by Imarticus Learning

SQL and Excel are powerful tools that complement Tableau’s data visualization capabilities. Tableau is a data visualization software or application that allows users to connect to and visualize data from various sources. You can integrate SQL and Excel with Tableau to enhance functionality and allow users to work efficiently with data. 

Reasons behind the growing hype of Data Visualization:

  • Data visualization tools and techniques allow for the quick and easy interpretation of complex data sets, helping businesses and individuals to identify trends, patterns, and outliers that you might otherwise miss.
  • Visualization tools have become more user-friendly, and cloud-based platforms have made it easier to share and collaborate on data visualization projects.
  • Infographics, charts, and interactive visualizations are more likely to be shared and engaged than traditional data reports or spreadsheets.
  • Finally, data visualization is an effective way to communicate data-driven insights to a broad audience. By presenting data visually appealing and engagingly, businesses and individuals can share complex information in a way that is easy to understand and memorable.

Here are eight points that explain how SQL and Excel are right for Tableau:

  • Data Preparation: Excel and SQL can help prepare data before feeding data into Tableau. Excel is an excellent tool for cleaning up and formatting data, such as removing duplicates or fixing formatting issues. SQL can filter and sort data and perform calculations before importing it into Tableau.
  • Data Connection: Both Excel and SQL can be used to connect to Tableau data sources. Excel can import data from various sources, such as spreadsheets, databases, or other files, which you can use in Tableau. Similarly, SQL can connect to multiple databases, and you can use SQL queries in Tableau.
  • Data Aggregation: SQL is a powerful data aggregation tool, allowing Tableau to work with large datasets more efficiently. SQL queries can summarize and group data, making it easier for Tableau to work with large datasets.
  • Data Blending: Tableau’s data blending feature allows users to combine data from multiple sources. Excel can blend data from multiple spreadsheets, while SQL can integrate data from various databases. This feature enables Tableau to create more complex visualizations incorporating data from different sources.
  • Data Analysis: Excel is a popular tool for data analysis and can be used in conjunction with Tableau. For example, Excel can calculate statistics or perform regression analysis, which can then be used in Tableau. SQL can also be used for data analysis, such as computing averages or creating complex queries you can visualize in Tableau.
  • Data Exploration: Tableau is designed to help users explore data visually. However, SQL and Excel can also explore data before visualizing it in Tableau. You can use SQL to query databases and explore data in a more structured way. You can use Excel to create pivot tables, which can help users explore data quickly and efficiently.
  • Data Validation: Excel and SQL can validate data before visualizing it in Tableau. You can use Excel to perform data validation checks, such as checking for missing data or identifying outliers. SQL can also validate data by checking for duplicates or identifying inconsistencies.
  • Data Maintenance: Excel and SQL can be used to maintain data integrity over time. Excel can create templates or dashboards updated regularly with new data. You can use SQL to create stored procedures that you can use to edit or delete data in a database. This functionality allows Tableau to work with more up-to-date and accurate data.

SQL and Excel are powerful tools that can enhance Tableau’s data visualization capabilities. You can use them for data preparation, connection, aggregation, blending, analysis, exploration, validation, and maintenance. By leveraging these tools, users can work with data more efficiently and create more sophisticated visualizations. 

Explore your career in Data Analytics and Machine Learning with Imarticus Learning!

best big data analytics course

This Data Analytics Certification Course promises to help you realize the full potential of data analysis and create models with the most significant business impact possible. Whether you are a recent graduate seeking to make a career in data analytics and machine learning or an experienced professional looking to advance your career in analytics, this program provides a practical approach to understanding how analytics can drive actual results in a business setting.

Course Benefits for Students:

  • Students can benefit from data analyst training while staying in the comfort of their homes.
  • Learn by doing with Data Analytics codes.
  • Students who complete the PG in Data Analytics Certification Course will have a thorough theoretical and practical understanding of data analytics.

How life-changing lessons can be learned with deep learning

Posted on by Imarticus Learning

Are you prepared to witness the power of algorithms that can interpret massive amounts of data, identify patterns, and generate predictions that can resolve complex issues? In that case, you’ve found the right place. In this post, we’ll examine the mind-blowing potential of deep learning and how it might completely alter how we live and work.

Think of it this way. Deep learning algorithms are like a superpower for the 21st century, one that can turn big data into actionable insights, drive innovation, and improve the quality of life—the secret ingredient powers cutting-edge technologies like self-driving cars, virtual assistants, and predictive analytics. 

The potential of deep learning is vast and limitless, and it’s only a matter of time before it becomes an integral part of our daily lives. As we explore the incredible power of deep learning algorithms, buckle up and get ready to be inspired. The future is now, and deep learning is leading the way!

The power of deep learning algorithms

Welcome to the exciting and transformational world of deep learning! Imagine a world where computers can quickly process enormous amounts of data, identify intricate patterns, and make incredibly accurate predictions.

A world where artificial intelligence has the power to revolutionize industries, solve difficult problems, and enhance the quality of life for people all over the world. This world is not a distant future but a reality that we are living in today, thanks to the power of deep learning algorithms.

Artificial Intelligence and machine learning course

Deep learning algorithms are the backbone of artificial intelligence and are responsible for creating intelligent systems that can perform tasks that were once only possible for humans. These algorithms use a combination of mathematical models, data, and powerful computing power to learn, adapt and make predictions. The result is an algorithm that can process vast amounts of information, recognize patterns, and make accurate predictions that surpasses human capabilities.

The power of deep learning algorithms is immense, and the possibilities are endless. This technology is changing the world as we know it, and it’s up to us to harness its power for the greater good. So, embrace the future and embrace the power of deep learning algorithms. 

Personal growth through deep learning

Deep learning has the potential to impact personal growth in a profound and meaningful way. 

  • Improving critical thinking and problem-solving skills: Deep learning algorithms require individuals to think critically and solve complex problems. The process of training algorithms and making predictions requires individuals to think outside the box and come up with creative solutions. This, in turn, helps individuals develop better critical thinking and problem-solving skills.
  • Developing a growth mindset: Deep learning encourages individuals to embrace challenges and view failures as opportunities for growth. Learning and improving algorithms requires individuals to experiment, make mistakes, and learn from their failures. This fosters a growth mindset, where individuals see challenges as opportunities to grow and improve.
  • Enhancing creativity and innovation: Deep learning algorithms can process vast amounts of data, recognize patterns, and make predictions. This process encourages individuals to think creatively and come up with innovative solutions. Individuals can enhance their creativity and foster innovation by exploring new ideas and approaches.

Deep learning has the potential to help individuals grow and develop in ways that are essential for personal and professional success. By improving critical thinking and problem-solving skills, developing a growth mindset, and enhancing creativity and innovation, deep learning can help individuals reach their full potential and achieve their goals.

Discover IIT artificial intelligence and machine learning course with Imarticus Learning.

Are you prepared to advance your career in a new tech-focused field? Enroll at the E & ICT Academy for their comprehensive IIT AI ML course! You can get ready for the roles of Data Scientist, Data Analyst, Machine Learning Engineer, and AI Engineer with this intensive 9-month program. 

Through real-world projects from various industries, you will develop a solid foundation in data science concepts and work with industry experts to learn how to apply machine learning, deep learning, and AI techniques practically. 

Course Benefits For Learners:

  • Students work on 25 real-world projects to develop real-world business experience and prepare for a rewarding data science career.
  • With a deep learning certification recognized by the E & ICT Academy, IIT Guwahati, and a credential supported by Imarticus Learning, students can attract employers’ attention and demonstrate their skills.
  • Students who complete this IIT artificial intelligence course land lucrative jobs in the machine learning and artificial intelligence sectors.

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

Our review: Best certificate programs in data science

Posted on by Imarticus Learning

Are you prepared to launch a data science career? Keeping up with the newest trends and techniques in the data world can be challenging because it is constantly changing. Fortunately, there are lots of certificate programs out there that can keep you competitive and help you stay ahead of the curve.

We searched the internet to compile the top data science certificate program for you in this review. These programs provide a wealth of information and real-world experience to help you succeed in your career, whether you’re just starting or looking to upskill.

In our in-depth guide, we’ll walk you through all the important things to consider when selecting a program.

Therefore, let’s sit back, grab a cup of coffee, and explore the world of data science. After reading this review, you will have all the knowledge necessary to make an informed choice and advance your career.

The Importance of Data Science: Uncovering Hidden Insights and Transforming Industries

Data Science Course

If you’re interested in data science, you may wonder what it is and why it’s so important. Data science can be defined as the process of analyzing data to discover hidden patterns and trends. 

This field is growing rapidly thanks to businesses looking for ways to improve their operations through machine learning (ML), artificial intelligence (AI), natural language processing (NLP), computer vision, and many other fields that make up this rapidly expanding field of study.

Data scientists are also essential for research because they help researchers understand how people think or make decisions based on their own experiences or those they have observed in others’ behavior patterns; they also help them create algorithms that can provide insight into these processes through simulation tests using real-world examples instead of simply relying on theory alone.

Why are certificate programs an excellent way to gain skills in data science?

Certificate programs in data science are a great way to learn the skills you need for a career in this field. They also provide an excellent base for further study and professional development, as well as giving you experience working with real data sets and building solutions from scratch.

A certificate program can help you get a job or promotion if you want to enter the industry as an entry-level employee or a recent graduate looking for options outside academia.

A certificate program in data science is a great way to gain skills in data science. This is an excellent place to begin if you are interested in entering the field and want to start building your resume.

Certificates are also good stepping stones into other industries, such as healthcare and finance, where they can be used as an advantage over those without them. In addition, they provide students with tangible proof that they have mastered core concepts of data science and are ready for more advanced subjects such as machine learning or AI.

With these programs, you will be able to learn from professionals who have been doing this for years and from industry leaders who know what it takes to succeed in this field. Adding a certificate to your professional resume is a fantastic way to demonstrate your data science expertise.

Discover Certificate Program in Data Science and Machine Learning with Imarticus Learning.

By taking the IIT Roorkee machine learning certification, you can begin your journey into data science and machine learning. This program, created with iHUB DivyaSampark @IIT Roorkee, will instruct you on the fundamentals and features of data science and machine learning and give you the skills necessary to put these ideas into practice and apply them to real-world issues. 

You will learn Python-based data mining and machine learning tools in this 5-month program designed by eminent IIT faculty members and how to use data-driven insights to promote organizational growth. Students can gain a solid foundation in data science through this program and can focus on Python machine learning for making decisions using data. IHUB DivyaSampark supports an innovative ecosystem for modern technologies.

Course Benefits For Learners:

  • In this IIT Roorkee data science and machine learning course, learn from renowned IIT faculty and gain a fascinating perspective on India’s thriving industry. 
  • You will have the advantage you need to advance your career in the data science field with the help of our data scientist careers. 
  • Learn the fundamentals of AI, data science, and machine learning to build skills that will be useful in the present and the future. 
  • With the help of our IIT Roorkee data science online course, you can give yourself a career edge by learning about cutting-edge technology that will lead to amazing opportunities.

How is the supply chain management course from IIT Roorkee different from other institutes?

Posted on by Imarticus Learning

Supply chain management is now a critical component of business operations and is a major factor in determining an enterprise’s success. Thus, there is an increased need for qualified individuals who can efficiently manage intricate supply chain networks. 

The global supply chain has experienced disruptions over the past few years. Manufacturing facilities struggled to keep up with the rise in demand for delivered goods. Restrictions slowed transit, and worker shortages resulted in a backlog of port deliveries.

A CAGR of 11.2% is anticipated for the global supply chain market between 2020 and 2027. Therefore, the market value will rise from $15.85 billion in 2019 to $37.41 billion in 2027. 

Given the constantly changing landscape of technology and data, staying current with the most recent trends and developments in your chosen field is essential. So, if you are looking for a training program that will help you to develop an idea about the dynamics of an industry and help you understand how businesses operate, IIT Roorkee’s supply chain management course will get your mind working! 

Explore Your Career Potential: Join the Fascinating Field

IIT Roorkee is one of the best universities in the country. The institute has been imparting high-quality education for over five decades, producing some of India’s most distinguished engineers and scientists. In the list of Best Global Universities, the Indian Institute of Technology (IIT) – Roorkee is ranked #896. 

With the help of this program, you will have the knowledge and abilities necessary to succeed in the operations and supply chain sector and to excel in positions that are in high demand, including demand planner, data scientist, supply planner, and supply and operations planner. You can also gain a competitive edge in the job market by using Supply Chain Analytics to teach you how to use data to make strategic, operational, and tactical decisions. 

What Makes IIT Roorkee’s Supply Chain Course So Impressive?

  • Curriculum

The curriculum is based on the latest industry standards and has been designed to give you a good foundation in supply chain management. This includes core topics like operations management, inventory management, procurement, and sales.  

The IIT Roorkee curriculum also ensures that students understand how their knowledge applies to real-world business problems today. In this sense, students need to learn how best to use their skillset when they leave the institute–and you can only achieve this by studying in an environment where there is a constant focus on the practical application of theory into practice!

  • Faculty

The faculty at IIT Roorkee is a mix of industry practitioners, researchers, and academic experts. They have been part of the supply chain management course for several years and have developed much expertise in this field.

The faculty members at IIT Roorkee are experts in their respective fields who can teach you about various topics related to supply chain management so that you get a good grounding before moving on to your internship.

  • Industry Interaction

Industry interaction is a significant part of IIT Roorkee’s curriculum. The students get to interact with big companies and small businesses in their area, which helps them gain real-world experience.

The faculty members are also involved in these interactions, so you can expect them to actively engage in discussions with your classmates on a range of topics related to supply chain management. 

  • Placements

Placements are a great way to get your foot in the door, learn about the industry and company, and network with professionals. In this course, you will be placed in companies across India interested in hiring you for your skills and knowledge. 

Discover IIT Supply chain Analytics Course with Imarticus Learning.

Students can prepare for in-demand positions like demand planner, data scientist, supply planner, and supply and operations planner with a logistics and supply chain management course. Supply chain and logistics management professionals should pursue certification to give leaders the tools to drive tactical, operational, and strategic decisions.

Enroll in our supply chain management course with analytics now if you don’t want to miss out on this wonderful chance to advance your career!

Course Benefits For Learners: 

  • You can get ready to assist in developing more creative and tactical global supply chains by combining a logistic management course.
  • You can advance your career and become a supply chain analyst through IIT’s supply chain program. Take advantage of this opportunity to launch a successful demand planner or data scientist career!
  • Students who study Python acquire a data-centric mindset, which will enhance their supply chain decision-making.

A beginner’s guide to a successful career in data analytics

Posted on by Imarticus Learning

Data analytics is a field that has become increasingly famous recently due to the massive amount of data that is being generated daily. To respond to particular inquiries and address issues, data analysts gather, clean up, and interpret data sets. As such, it also presents a vast opportunity for individuals who want to pursue a career in this field. However, breaking into the industry and becoming successful can be challenging. 

Why start your career in Data Analytics?

become a Data Analyst

Data Analytics is a rapidly flourishing field that has become essential for businesses across all industries. The ability to collect, analyze, and interpret data is crucial for making informed decisions and staying competitive in today’s market. This is why starting your career in data analytics can be an excellent choice.

  • One of the key reasons to pursue a career in Data Analytics is the high demand for skilled professionals. As more companies recognize the value of data-driven insights, the need for experienced analysts grows.
  • Finally, Data Analytics can also provide opportunities for meaningful work. By helping organizations make data-driven decisions, you can contribute to solving real-world problems and positively impacting society.
  • Overall, starting your career in data analytics can provide you with a challenging, rewarding, and high-paying career path with ample opportunities for growth and development.

This guide will provide some tips to help you start a successful career in data analytics.

  • Understand the fundamentals of data analytics: Before beginning a career in data analytics, it is essential to understand the fundamentals. It includes knowledge of statistics, programming languages, and database management. You can also start by taking courses in statistics and programming languages.
  • Choose your niche: Data Analytics is a broad field with many specialties. Determining the area of Data Analytics you want to focus on is essential. It will help you develop specialized skills that make you an expert. Some popular specialties in Data Analytics include business intelligence, predictive analytics, data visualization, and machine learning.
  • Gain practical experience: One of the best ways to learn and gain valuable experience in Data Analytics is by doing projects. Projects can help you to develop hands-on experience and showcase your skills to potential employers. You can start by looking for online resources where you can find data sets and work on real-world projects.
  • Build a strong portfolio: A portfolio is a collection of projects you have worked on, essential in Data Analytics. Your portfolio should demonstrate your skills and highlight your strengths. When creating a portfolio, include a description of the projects you have worked on, the problem you were solving, and the techniques you used. A strong portfolio can help you stand out from other candidates when applying.
  • Network: Networking is essential to any career, and Data Analytics is no exception. Attending industry conferences and events can help you to meet people in the field and learn about new trends and developments. You can also join online chat communities to interact with other professionals.
  • Continuous learning: Data Analytics constantly evolves, and keeping up with new trends and technologies is essential. Continuous learning can help you to stay relevant and develop new skills. You can achieve this by taking online courses, attending workshops, and reading industry publications.
  • Apply for internships: Internships are an excellent way to gain practical experience and get your foot in the door in the industry. You can look for internships at companies specializing in Data Analytics or apply for positions that use Data Analytics in their operations.

Starting a career in Data Analytics requires dedication, hard work, and continuous learning. However, by following these tips, you can build a successful career. Remember to stay focused, keep learning, and look for new opportunities.

Explore your Career in Data Analytics with Imarticus Learning!

This Data Analytics Certification Course promises to help you realize the full potential of data analysis and create models with the most significant business impact possible. Whether you are a recent graduate seeking to make a career in Data Analytics or an experienced professional looking to advance your career in analytics, this program provides a practical approach to understanding how analytics can drive actual results in a business setting.

Course Benefits for Students:

  • Students can benefit from the Data Analytics course while staying in the comfort of their homes.
  • Learn by doing with Data Analytics codes.
  • Students who complete the PG in Data Analytics Certification Course will have a thorough theoretical and practical understanding of data analytics.

How is supply chain analytics important for a business in 2023

Posted on by Imarticus Learning

Supply chain management includes managing the flow of goods, services, & information from suppliers to customers. It is a complex process that requires careful planning, coordination, and execution. In past years, businesses have increasingly turned to data analytics to help them effectively manage their supply chains.

Businesses can identify trends & adjust their production schedules to meet demand more effectively by analyzing customer demand data. By analyzing transportation data, companies can identify the most cost-effective shipping options and reduce transportation costs. Businesses can locate the most reliable and cost-effective suppliers by analyzing supplier data and building stronger relationships.    

What is Data Analytics, and How Can They Help Supply Chains?

globa supply chain analytics course

Data analytics uses statistical & computational methods to analyze large datasets and extract insights from them. In supply chains, data analytics includes collecting and analyzing data related to various aspects of the supply chain, such as transportation costs, inventory levels, production schedules, and customer demand.

Data analytics can help supply chains in many ways:

Demand forecasting

By analyzing historical sales data, businesses can forecast future demand and adjust their inventory levels accordingly. This can help reduce the likelihood of stockouts and overstocking, improving customer satisfaction and cost savings.

Inventory optimization

With inventory data analytics, businesses can identify slow-moving or excess inventory and take steps to reduce it. This can reduce inventory holding costs and free up warehouse space.

Transportation optimization

Businesses can identify the most efficient modes of transportation and routes to minimize costs. This can help reduce transportation costs and improve delivery times.

Supplier performance monitoring

By analyzing supplier data, businesses can monitor supplier performance and identify opportunities to reduce costs and improve collaboration. This can build stronger relationships with suppliers and reduce the risk of disruptions in the supply chain.

Quality control

With it, businesses can identify areas for improvement & take steps to reduce defects and waste. This can help improve product quality and reduce costs.

Why Is Supply Chain Analytics Important for Businesses?

Supply chain analytics is vital for businesses because it can improve efficiency, better decision-making, enhance customer service, & increase competitiveness. Businesses can gain insights into their operations using data analytics and take proactive steps to optimize their supply chains. 

Supply chain analytics can help businesses streamline operations, reduce costs, & improve customer service. With the help of data analytics, businesses can gain a competitive edge in an increasingly complex and competitive marketplace. Supply chain analytics is essential for businesses because it can lead to several benefits, including:

Improved efficiency

By analyzing supply chain data, businesses can identify areas where they can improve their operations, reduce wastage, & optimize their resources. This can also lead to significant cost savings and improved efficiency.

Better decision-making

Supply chain analytics can give businesses real-time operations visibility, enabling them to make better decisions based on up-to-date information. For instance, companies can quickly adjust their production schedules or find alternative suppliers to minimize disruptions if a supplier faces delays.

Improved visibility

With supply chain analytics, businesses can gain greater visibility into their processes, which allows them to identify bottlenecks, inefficiencies, and areas for improvement. This visibility can help enterprises to optimize their operations and make better decisions.

Better forecasting

Businesses can use supply chain analytics to improve forecasting accuracy by analyzing historical data and current trends. This will help them better anticipate demand and ensure proper inventory levels to meet customer requirements.

Enhanced customer service

Supply chain analytics help businesses improve their delivery times & reduce the likelihood of stockouts, leading to happier customers. By analyzing data demanded by customers, businesses can adjust inventory levels and production schedules to meet customer needs effectively.

Discover Supply Chain Analytics Course with Imarticus Learning: 

If you want to become a supply chain professional, registering for the supply chain analytics certification course from Imarticus Learning can be a great idea to advance your job in the supply chain and operations industry. 

A complete set of skills, including strategic, operational, personal, and technological knowledge, are offered in the program at IIM Raipur for senior supply chain employees to assist you in succeeding as an SCM manager. Students connect with other business professionals throughout the supply chain analytics course and set out on a successful career in supply chain and operations.

Course USPs:

  • Provide students with the learning they need for a successful Career in logistic Management.
  • Learn from innovative leaders.
  • Networking opportunities with former IIM Raipur students
  • Become a member of the IIM Raipur Alumni Professional Group.