Management - Finance, Tech & Analytics Career Resources | Imarticus Blog - Page 146

Marketing of the Future: How Data Analytics is Changing

Posted on September 27, 2021January 24, 2022 by Imarticus Learning

The corporate industry is ever-evolving, and even more so when it comes to data analytics. From standard out-of-the-box reports to a tool operated by digital mediums, it has come a long way. In the past, it was mostly a way to decipher and keep records of bygone trends, but now it has turned into a tool that helps you predict future trends.

It even helps you understand your target customer better through their online habits. And as daily life gets more and more virtual-oriented, the need for machine learning and AI-oriented data analytics will keep growing. So will grow the number of positions for good data analysts.

Here, you have a chance to learn data analytics with Imarticus Learning’s new PG program to enhance your skills to the max.

Coming back to the evolution of data analytics throughout the years, there are a few major changes that need to be addressed. Such as the shift to digital analytics from standard reports, as well as live AI reports and alerts.

Digital Analytics from standard reports

The major difference that has gained traction in the last few years would be how virtualized the data analytics industry has become. In the past, most of the analysis process was done through tool-generated out-of-the-box reports which today are almost out of date. Now the main focus has shifted towards reading the targeted customer’s habits and needs and forming strategies to cater directly to it.

It becomes a lot less hassling on both parts as instead of guessing you’re actually finding out what your client needs and providing solutions for it. Now with the change in how data is extracted and processed the job of an analyst has also evolved. This is one of the reasons why data analytics courses in India have been getting more and more popular in recent years.

Live AI reports and alerts

Another system that has become immensely popular is live AI reports that alert the clients to any ups and downs in trends. This helps them to develop quick strategies to respond to the changing trends. Not just that, the sources from which data is generated have changed drastically. Not just real-time market trends, data today can be sourced from online retails, social media, intelligence tools as well as pop-ups and advertising platforms.

The bandwidth of data has increased and along with it, the variety, responsibility, and positions of a data analyst job. As this process evolves more the scopes will increase even more in numbers. This is a good time to enhance your skills if you are thinking about career prospects. There are many institutes that offer good data analytics courses in India that might suit your preference. However, there are few things you should keep in mind when it comes to data analytics:

Many companies are venturing into exploring open-source software, but the majority is still using business analytics tools and visual analytics.
Data analysis has become a part of our daily lives. As a result, new and faster ways to generate data are coming out that need higher levels of skills.
The industry is constantly evolving, so it is necessary to always be top of your game as a data analyst.

Conclusion

Data analytics is one of the careers that has a firm base. More and more opportunities are going to open up in the future. This might be a good time to learn data analytics with a proper PG program that will help your career bloom.

A Complete Guide to Data Science, Artificial Intelligence and Machine Learning

Posted on September 27, 2021March 26, 2024 by Imarticus Learning

Data science often referred to as the ‘oil of the 21^st century can be simply defined as the subject dealing with the collection, storage, analysis, deployment, and prediction of data. It collects the clean information from the raw data of the user and uses it for actionable insights. It is also used in predicting certain events in the future. Scientists define it as another form of statistics and YES! IT IS.:-

Data science vs AI vs Machine Learning

Data science obviously has the upper hand when compared with artificial intelligence and machine learning. Indeed machine learning and AI is a subset of data science.

After all data science, machine learning, and AI are associated with each other to build the technology.

By 2013, the total data created was 2.7 zettabytes which 9x times more than it was collected in the previous 92,000 years of humankind combined. And is 90% of entire world data has been created in just 2 years. YEP! That’s amazing.

And it is still growing at a rapid pace. By 2020, the total data created was 44 zettabytes and it is projected to a rise of 175 zettabytes at the dawn of 2025.

Processes in Data science:-

Understanding Business problem
Data Acquisition
Data preparation
Exploratory data analysis
Data modeling
Visualization and communication
Deploy and maintenance

Potential of data science:-

The power of data science is beyond our vision. We use it in our day-to-day life. It made our lives easier. Data science is being currently being used by many companies like Google, Instagram, Apple, etc. Whatever we browse, we watch is everything monitored from second to second.

Some of these determine its potential:-

Genomic data provides a deeper understanding of genetic issues.
Logistics companies like DHL and FedEx have discovered the best time and route to the ship.
Used to predict the employee artition and understand the variables that influence employee turnover.
Airline companies can now easily predict flight delays and notify passengers.

Applications of Data science:-

Data science plays a major role in many fields of the world like health, finance, Entertainment, cyber security, social networking, weather forecasting, etc.

Apps like Instagram Facebook YouTube collect the data from which we are interested and designs a user-friendly profile with recommendations popping up.
Data science is also used in detecting earthquakes’ location and magnitude by Seismograph.
Often used in cyber security and crime-related issues because data science has every single information of a person like his address, phone number, salary, what type of device he uses, etc.
Entertainment sites like Netflix and Prime video analyze the information from the videos which we have watched recently and creates our recommendations.

You might wonder which company has the most data. And the prize goes to google.

Because Google’s entire business is based on data science. Google uses apps like Google Maps to show us the best route in the traffic is an example often build by data science.

Companies like Apple supports the user’s privacy and does not allow the companies to go through our personal information using data science.

A tool like VPN helps in disguising or diverting our IP address from ISP and third parties.

Another segment to know under data science is hacking.

Hacking is done by hackers who are unauthorized users who break into one’s system and steal or destroy their personal information.

Hacking can be prevented by installing anti-software and keeping it up-to-date.

Another way of preventing hacking is setting up two-factor authentication.

Artificial intelligence like Siri, Alexa, etc are designed for user assistance and can be referred to as user-friendly software.

Future outlook:-

In the future foresight for sure, Dada signs will rise rapidly and will make our lives much easier with the better implementation of technology in the upcoming generations. For sure we can see the golden ages of artificial intelligence in the upcoming era.

We will be able to get the use of robots for better development. But how much ever it grows it must be always embedded in the limits because if it overtakes the human race it will be the end of Mankind. But it is difficult to equal the level of human intelligence.

Case Study:- Instagram algorithm

The main objective of the Instagram algorithm is to keep its users online for as much time as possible. Its algorithm works like popping the ads that users might be interested in. Now you might wonder how can Instagram know about its user’s interests.

Instagram algorithm stores the set of information of each user separately like how much time a user spends on a post or a real or what type of post he likes frequently or what type of ads the user visits.

So it analyzes from all these statistics and organizes the homepage and search engine of one account to hold them online for most of the time. It might seem surprising and tactical but at the end of the day, it’s all business.

The ones who are interested in data science is a very good field of the subject to opt for.

One can opt for data engineering at the graduation level. They would have a very good scope of becoming a data scientist or a data engineer. And The mean average salary is around $90,000 to 120,000 $.

And that’s it in today’s blog. Hope you had an informative day.

Hasta la vista.

Article Credit –

“This blog was written and submitted by Ruthvik Rao, Hyderabad as a part of Imarticus National Blogging Contest. All views and opinions expressed within this article are the personal opinions of the author.

Disclaimer:

The facts and opinions appearing in the article do not reflect the views of Imarticus Learning and Imarticus Learning does not assume any responsibility or liability for the same.

What Skills Are Needed to Be A Data Scientist?

Posted on September 27, 2021March 22, 2024 by Imarticus Learning

A career in data science is highly attractive owing to its payment structure, job opportunities, and future career prospects. There is any number of Data scientist courses that you can find and that makes you qualify for the job.
The major criteria for this career are a few skills that one can easily master through the right path.

These skills could very well be different from any former experience in the career thus far. Developing these skills will help the recruiters to identify you as the best option for what they are looking for!

Programming language
A strong knowledge base of any major programming languages such as Python, R, or SQL is the foremost requirement to be an expert in data science. No matter what the company or the job profile is, this is one field of expertise that is non-negotiable.

Statistics
Statistics hold more value in data science since it helps to deal with the raw data of the companies. It helps with the evaluation, designing, and making decisions in the later stages.

Deep learning
This machine learning technology enables computers to work like the human brain.

An enormous amount of data is managed through computing power to make it possible. A career in data science, especially that in the automobile and AI industry requires this particular skill.

Working with unstructured data
Data science is mainly about the gigantic amount of data from various sources. The vast majority of this data is in a raw and unstructured format. A skilled data analyst can easily go through them to find and identify what they are looking for to make it useful.

Appetite for problem-solving
Simply looking at the data is not what makes the analyst skillful. It also calls for the right appetite to identify the problems underneath and finding the ideal solution as well. For which the analyst needs to have the drive for problem-solving and look in the right areas.

Data visualization
This is the skill that enables a data scientist to identify and decode the raw data into an identifiable visual to use it to convey. This skill enables the analyst to see what the data is useful for with the help of the various data visualization tools.

Communication skill
It comes next to the visualization part. The visualized data needs to be explained in a simple and well-constructed plan to the stakeholders. AT this juncture, the analyst must have strong communication skills to convey the key points and make them believe in the same. Polishing communication skills would be an added advantage to improve career prospects.

Familiarity with data science tools
Data science involves various types of tools to help with data processing. An analyst must have a fairly good idea about the working of most of the tools. Since each type of data requires different tools, it is highly imperative to be on familiar terms with these tools. Most of them are pre-programmed, so you just need to know how to use them in the proper way.

Intuition
Last but not the least, having a strong intuition on what to look for, how to use it, and which tool needs when to get the best result out of the data analysis happens to be the strongest point of being a successful data scientist.

Conclusion
Most of these skills are covered in the Online data scientist course in India available from various sources online or otherwise. What needs more work would be on soft skills which also have an equally important role in a successful career. A career in data science does not have refined eligibility criteria, instead, it mainly depends on these acquired skills.

Top Career Options in Data Science!

Posted on September 27, 2021October 20, 2021 by Imarticus Learning

Data Science is an emerging and yet established interdisciplinary filled that makes use of objectively led processes, methodology, systems, and carefully curated algorithms to study data. This file is very close to and often overlaps with Big Data and Data Mining.

By careful study of the Data Science Course, this field aims to extract important information and patterns that can be used for a number of decision making, information gathering, and data collection tasks.

Where is Data Science Used?

Data Science is being used by a myriad of fields ranging from state-sponsored departments, the police, military, private companies, NGOs, marketing experts, researchers, and customer service support groups around the world. Most recent and successful technologies such as face recognition are a product of data science innovation. Cookies that online retail stores and online publications use are based on this field too. Data science has entered almost every aspect of our digital lives in a short span of time.

What are some of the jobs that Data Science has?

Here is a list of top Data Science Career Options in Data Science that are shaping our future:

Data Scientist: This is a highly sought after job in the field of Data Science. A data scientist is expected to study all big and small data that has been gathered. They are also supposed to form the recommender systems and organize the data for analysis. All major corporations like Facebook, Google, Microsoft, Twitter, etc. employ data scientists. This job is better suited for people who are good at mathematics and coding.
Machine learning engineer: A machine learning engineer is entrusted with the job of making data funnels that aid in software creation. They also construct the appropriate and suitable algorithms needed for problem-solving. The machine learning engineers study the systems and its prototypes by running regular tests. They experiment with different problem-solving techniques and modify the current operating steps to improve the current methodology and quality of work. Machine learning engineers are highly paid.
Business Analyst: A business analyst tests data by keeping in mind the requirements of the business house it is serving. One does not have to be specifically from a technical field to perform this job. A business analyst has knowledge about industries like telecom, finance, logistics, marketing, and retail.These people are well informed about government and legal policies related to financial technology. A business analyst helps a company find out what information they need to enhance the company’s consumer behavior, marketing strategies, and relationship with its customers.
Data Analyst: Like the name suggests data analysts are responsible for primarily web tracking, testing, and operating big and large data sets. They use a mix of statistical tests and interdisciplinary methodology made up of qualitative and quantitative tools to study big data.They have to pick relevant patters and form conclusions based on a set of figures available. A good data analyst is equipped with the number of fact-finding and statistical tests that can be applied to a varied set of data packs depending on the availability of the information. A capable data analyst will be perceptive and informed about which tool and method have the best probability of revealing the most reliable information.

Conclusion

Data Science is one of the most expansive and quickly growing fields in the world. There has been a steep rise in several Data Science Coursetakers in the last few years. The reason for this recent increase in popularity is the number of jobs that have emerged in this area. Since data science is multidisciplinary, people from different subjects and work fields can collaboratively work in it.

Why Are Companies Considering Candidates With An Artificial Intelligence and Machine Learning Certification?

Posted on September 24, 2021April 1, 2024 by Imarticus Learning

Artificial Intelligence has expanded at an exponential rate in recent years, despite significant progress in the field. In the field of computer science, AI practices can be found everywhere. It provides you with an idea of how many different ways a computer system can be designed.

It is designed to carry out the cognitive functions that humans have specified.

This indicates that the scope of an artificial intelligence and machine learning course is enormous, and AI has potential that is currently beyond human grasp.

Scope of An Artificial Intelligence and Machine Learning Course in India

Artificial Intelligence has enormous potential to transform every sector of the economy for the greater good.

AI encompasses a wide range of technologies, including self-improving algorithms, machine learning, big data, and pattern recognition, to name a few. There will be few industries or sectors left unaffected by this potent weapon in the not too distant future. This is why online Artificial Intelligence courses are becoming increasingly popular in India.

With each passing day, the gap between the number of AI professionals required and those available widens. Corporations are spending money to train their existing employees on Artificial Intelligence technologies. However, the demand is far higher.

Learn AI

Certification In Artificial Intelligence & Machine Learning

Learn AI via 25 in-class, real-world projects focused on offering exposure to various industries. This 9-month program will help you prepare for the roles of Data Scientist, Data Analyst, Machine Learning Engineer, and AI Engineer.

This machine learning certification program was established in collaboration with the E&ICT Academy, IIT Guwahati, and industry professionals to give an optimum learning outcome,

This course will strengthen your core abilities, allow you to take advantage of our Expert Mentorship program, and give you a practical grasp of AI and Machine Learning.

Data Science Prodegree

Develop your knowledge of Data Science ideas and build robust models to generate relevant business insights or forecasts with a working knowledge of critical Data Analytics technologies such as Python, R, SQL, and Tableau in these 14 in-class and industry-oriented projects.

PGP In Digital Marketing

Our Digital Marketing Postgraduate course is meant to provide you with a more in-depth and practical understanding of Digital Marketing ideas. The postgraduate program takes a collaborative approach that emphasizes several Capstone projects, job-specific skills, and guaranteed job interviews.

This course will prepare you from beginning to end to start or advance your career in the Digital Marketing segment, including resume building, mock interviews, job leads, and references,

making it an ideal Digital Marketing course with a strong focus on placements to help you land your dream job.

Post Graduate Program in Data Analytics & Machine Learning

This machine learning certification program is for recent graduates and early career professionals interested in pursuing a career in Data Science and Analytics, the most in-demand job skill.

To become job-ready, master the fundamentals of data analytics and machine learning, as well as the most in-demand data science tools and methodologies.

With this job assured program, you’ll learn Python, SQL, Data Analytics, Machine Learning, and Data Visualization. After completing the course, students are promised interview opportunities.

Takeaway

AI is one of the most popular technologies on the planet because of its diversity and superior solutions. It has been rapidly expanding. As you can see, the scope of AI has broadened to include a wide range of industries, including healthcare, transportation, security, etc. Multiple industries require the expertise of experienced AI specialists as a result of this increase.

Check out Imarticus IT classes, targeted at working professionals, if you want to learn more about AI and machine learning algorithms.

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

Posted on September 24, 2021September 30, 2022 by Imarticus Learning

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

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

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

Data analysis as a tool to ensure happiness

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

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

Hurdles to jump over

There are some evident advantages of exchanging data for the betterment of the employees’ wellbeing, and in turn, increase their productivity. However, it is also a possibility that when it comes to data gathering and analysis, the employees might have some privacy concerns about them.

Which in turn, might make them unwilling to participate actively in the bandwagon. This is why, there are a few things that should be kept in mind when it comes to the interrelation of wellbeing and productivity of the workers, such as:

The first and most important thing is to make sure the workers consent to the exchange of data for the company’s use, as many might have privacy concerns relating to that.
Companies will need to have experts in the analytics team to properly extract and use the data and make it a priority for both the main wing of the business and the analytics team to prioritize the employees well being.They need to communicate properly to the workers how it benefits them and the company both at once.
The key is to recognize what the employees want and be able to cater to it. Otherwise, even after using data analytics to define the workers’ needs, it will be utterly irrelevant.

Conclusion

Using data analytics as a mode of communication between the employer and employee needs time and expert skills. And it can only come if you learn data analytics from a good place. Many institutes in India offer a data analytics certificate course. Imarticus Learning is one of the topmost among them, so do check out their PG program of data analytics and machine learning.

Which Is Better For Machine Learning R or Python?

Posted on September 24, 2021October 15, 2021 by Imarticus Learning

Machine learning is not a single science. It comprises a blend of fields such as analysis, recognition, prediction and decision making. There are several open-source tools available for machine learning out of which R and Python are the most demanded or rather the most popular ones. The main difference between the two languages has been seen in the fields of analysis and data science.

Both the languages provide open source tools and support from a wide variety of libraries for machine learning but because of the high degree of robustness provided by the python packages such as Scikit-learn built on numpy and Scipy, Python is preferred more for machine learning. According to a recent survey, Python had an increment in its popularity and use from 53% to 69% within two years.

Several machine learning courses aim at delivering courses dedicated to R and Python. The question as to whether an individual should learn both languages depends highly on the field of application and interest of an individual. Both languages have highly efficient ecosystems for machine learning tasks.

The difference in popularity and use is because of the comfort of an individual with the programming language, interest and application needs. Also, job opportunities can be one of the deciding factors whether an individual should learn Python or R for machine learning.

Provided below is a comparison of Python and R which could help an individual decide whether they need to learn both languages.

R:

R was developed by the statisticians primarily for analysis. The programming language is based on the mathematical calculations comprising machine learning and hence forms a really important part of the statistics involved in the project. Thus, a project which is largely dependent on statistics should use R as a programming language.

Advantages:

Highly suitable for data analysis and visualization.
Support from the libraries
Highly robust
Highly suited for exploratory work

Disadvantages:

Scarcity of expertise in the language due to low learning rates.
The algorithms in R comes primarily from the third parties and hence, it is not very consistent to build the models.

Python:

Python came into existence in the ’80s. Today, it forms a core of the machine learning operations being performed by Google. It has extended its roots in the field of artificial intelligence as well and is being widely used in almost every possible domains whether technical or non-technical.

Advantages:

In contrast to R which provides support for only statistics, machine learning has extended beyond just statistics.
Python unlike R provides a smooth learning curve and is more consistent than R.
Huge support from libraries such as numpy, pandas, OpenCV, sklearn, etc.
Simplicity in the syntax making it easy to learn the language.
Highly robust models and boosting techniques.

Disadvantages:

Less support for statistical models due to the non-availability of suitable packages.
Multithreading is Pyhton is not generally preferred as it is difficult to implement.

From the above comparison, it can be seen that both the languages having their advantages and disadvantages. But the key point that differentiates them is the use and library support. R and Python in machine learning have succeeded in their way. One has left footprints in the field of analytics while the other has emerged victorious in the field of data science.

Conclusion

To choose the right language, the right strategy is needed. For a person stepping into the industry as a fresher, Python is preferred as compared to R because of its simple syntax and ease of learning.

Also, if an individual is looking for a career in the field of data science they should go for Python as the programming language and if they want to handle the huge data-related tasks such as analysis and prediction making, no doubt that R is a better choice.

R is closely related to analysis and Python is closely tied to huge tasks such as object detection, disease prediction, computer vision and so on. Hence, we can conclude by saying that an individual needs to rightly assess their needs before choosing one of them and should master only one trade.

What Are the Characteristics of Big Data?

Posted on September 23, 2021April 25, 2024 by Imarticus Learning

Big data is the next big wave that is shaping the corporate sector today. Big data gives an idea about the size of data but there are various aspects associated with it. It is also driven by various other factors apart from the size of data such as the sources of data, various formats in which it is available, chunking and extraction, etc.

Big data has managed to find space in all sectors of the market – technology, retail, telecommunications or any other broadly recognized field. It makes use of the available data to derive conclusions.

Need for Big Data

Organizations have huge data resources in an unstructured format. Mostly this data is stored in various devices and is never brought to any use. Data can prove to be a mega resource for the growth of any company as it can equip the company with numerous insights thus acting as the steering wheel of the company. Traditional tools such as Excel are not that efficient in extracting information and putting it to any relevant use. Big data comes into the picture here.

When you have a huge amount of data, it needs to be sorted and then classified under various heads so that the important fields can be easily recognized and brought to use. This space is getting bigger with every passing minute as we are becoming more and more data-oriented.

The volume of data is huge. With the increase in the number of internet users, more data and information are coming into circulation and this has given rise to the value data holds today. This data is produced through various channels like search engines, social media networks, business informatics, etc. It makes use of various tools to summarize information.

Learning Big Data and Hadoop can pave a great career path for someone who wants to have a career in data analytics.

Characteristics of Big Data

The 4 Vs of Big Data characterize big data. Data needs to be classified and organized for better understanding. The 4 Vs of Big Data are:

Volume
Velocity
Variety
Veracity

These characteristics form the essence of Big Data. It gives insights on how the data should be dealt with and how can the insights from that data can be put to good use.

Volume: Volume defines the size of the data which in today’s time is exploding and increasing exponentially. To be precise, this defines the quantity of data available for the extraction of information. Based on the volume of data, various tools are applied for the segregation of information.
Velocity: Velocity refers to the speed in which the data is processed. The speed of data processing plays a very important role in Big data as a lot of data has to be analyzed and insights have to be drawn within a stipulated time frame, thus making the velocity of data an important feature of Big Data.
Variety: Variety refers to the various types of data from which the relevant information has to be extracted. It is important as data collected from different sources are diverse in many aspects. Big Data makes use of various tools to integrate the diversified data and draw insights for the business.
Veracity: Veracity refers to data accuracy and its relevance with the business information we require or the business decision that has to be made. Veracity helps in the identification of relevant information and hence saves a lot of time.

Conclusion

Big Data today has various dimensions and has opened a new world for data harvesting and extraction. With the help of the Big Data Analytics course, one could gain expertise and in-depth insight into the field.

Enrol for the best artificial intelligence and machine learning course from E&ICT Academy, IIT Guwahati

Posted on September 22, 2021March 21, 2024 by Imarticus Learning

The most important question to any student these days would be what to study that will tremendously benefit his/her career, and where to study it from. Numerous courses are offered by several institutions, and choosing the best option for yourself in such a scenario can be very confusing. This is why we are here to shed light on possibly the most relevant course right now.

That is, of course, the artificial intelligence and machine learning course. It is one of the most versatile courses out there that lets you work in almost any field you want. That is because all the major sectors now need the help of artificial intelligence and machine learning to optimize their business and keep the customer and employee-friendly. A lot of institutes in India provide AI ML courses. Imarticus Learning is one of the best in this field with its certificate course.

However, if we are to talk about the best institute to learn an artificial intelligence and machine learning course from, then it would undoubtedly be an IIT. Here, we are going to take a look at why an AI and ML course might be one of the most relevant courses out there that will benefit your career. And, why an AI and ML course from an IIT is the best.

Benefits of an AI and ML course

Data analytics basically uses numerous tools to extract and analyze data in a way that helps to detect patterns from past records. It also analyses where the company is now and predicts where it can go from here. All of it is done through analyzing market trends, the company’s financial condition as well as the customer’s online habits. The main benefits of this course are:

It is one of those jobs that is applicable in any given field, from the health sector to finance to marketing. This means that you can land your dream job from the get-go or if you feel like it, then you can even change your sector without much thought.
It is one of the highest-paying jobs in the country right now, which, of course, means a stable future.
Expert reports state that in the near future, there are going to be even more positions opening up in all corporate sectors.

Why IIT is the best choice

As we all know, IIT is an unparalleled choice when it comes to courses in any sector of business. There are few reasons for that, such as:

It teaches you deep skills that are most popularly used in AI and ML.
The opportunity to learn from actual corporate cases, that too from the top-level industry professionals of AI and ML.
Overall excellent vocational training, as students experience hands-on learning with lab-based cases related to the most high-level industry problems.
Another thing that IITs are most known for is excellent industrial exposure.
The opportunity to learn AI and ML from any IIT will immediately put you leagues beyond your peers.
An excellent package right from the beginning in your preferred sector.

Conclusion

The opportunity to learn AI ML courses from an IIT is the best thing that can happen to your career. It is an academic investment that will be paying off throughout your life.

So, prepare hard enough to give yourself that edge over others. Also, do check out Imarticus Learning’s AI and ML certificate course as we have one of the best-planned courses in this field.

How to Start a Supply Chain Management Career?

Posted on September 22, 2021March 28, 2024 by Imarticus Learning

How to Start a Supply Chain Management Career?

A supply chain management career is the best choice for those who are interested in research and logistical development. Students with a basic knowledge of programming and operations management can opt for the certificate course from Imarticus Learning.

This course will prepare students for a career as production planner, purchasing and warehouse manager, logistics resource planner, and maintenance supervisor. There are many more jobs in inventory control, procurement, and logistics administration.

Get a Degree in Supply Chain Management

To start a career in supply chain management, aspirants should opt for an SCM course. Imarticus Learning offers professional certification in supply chain management & analytics.

The certification is provided in collaboration with IIT Roorkee. Live lectures are organized by industry professionals and academicians. Students are encouraged to participate and interact with their peers and instructors.

The supply chain management course from Imarticus Learning requires students to complete projects that are based on real industry issues. These projects help students develop strategic planning skills at operational levels. For students aspiring to become data scientists, supply planners, demand planners, or supply and operations planners, this certificate course is the best choice.

Mentoring sessions are held frequently. These sessions are great for building networks and gaining hands-on experience. The campus immersion program at IIT Roorkee is a great opportunity for students to interact and develop soft skills.

Things to Know Before Starting a Career in Supply Chain Management

A supply chain management career is very rewarding and provides many opportunities. Students who wish to study supply chain management and build a career should keep in mind the following points.

Supply chain management is data-centric.

In supply chain management, professionals focus on data-driven decisions. A large volume of data is processed on a daily basis and analyzed to generate actionable insights. The extraction of relevant data needs to be accurate in order to create an efficient supply chain.

Supply Chain Management includes more than storage and movement of products.

The storage of products and movement from supplier to manufacturer, then to wholesaler to retailer, and finally to the consumer.

But the job also includes supply chain planning and monitoring of finances.

The certificate course from Imarticus Learning on supply chain management and analytics will help students learn every aspect.

Supply chain managers require soft skills for networking.

Supply chain managers need to collaborate and communicate with clients and other teams. This is why it is essential to have soft skills that include communication, people skills, and social intelligence.

To have a successful career, new professionals in the field should develop connections. Networking is essential to expand the knowledge base. Imarticus Learning helps students develop such skills through interactive sessions and project work with industry experts.

The supply chain management industry is competitive.

While there is scope for advancement in supply chain management, the industry is very fast-paced and challenging. The competition is intense and managers need to be able to process the planning and movement of goods quickly and efficiently.

The supply chain needs to be environmentally sustainable.

A supply chain manager should focus on creating an efficient supply chain. Such chains can optimize the movement of products which reduces wastage. This makes it more sustainable and environmentally friendly.

The professional certification in supply chain management & analytics from Imarticus Learning is ideal for learning relevant skills. This is a 6-month long program and prepares students for a lucrative career in supply chain management.

A supply chain management course can help candidates start and continue a successful career. Since there are many job opportunities in the industry, certification from a leading institute like Imarticus Learning allows students to create an impressive portfolio and get jobs in their fields of interest.