AI Engineer Course: Understand Design Gamification In Grammarly

Posted on July 8, 2022August 29, 2022 by Imarticus Learning

AI Engineer Course: Understand Design Gamification In Grammarly

As an AI engineer, it’s essential to understand the design of gamification in grammar tools like Grammarly. You can create more effective AI applications by understanding how to use grammar in these tools.

Grammarly is a popular grammar tool that uses gamification to help users improve their writing. The tool gives users points for correct grammar usage and provides feedback on their writing.

Understanding how grammar gets used in Grammarly can help you design more effective AI applications. If you can understand how users interact with the tool, you can create AI applications that are more effective at helping users improve their writing.

What is gamification, and how can it help grammar learning?

Gamification is using game aspects to persuade people and solve issues in non-game environments. Gamification, as a creative, productive, and exciting learning activity, may be utilized as an educational tool to improve learning outcomes in the twenty-first century.

The tone of writing is one of Grammarly’s most intriguing aspects. To offer better suggestions, a user may easily customize the tone and audience of their writing.

Grammarly also offers its customers a weekly writing update check-full of writing insights and more. It analyzes its users’ content in real-time to deliver the proper suggestions.

The benefits of using gamification in grammar learning

Communicating clearly and effectively in today’s fast-paced world is more important than ever. Grammar is critical to effective communication, and many people struggle with mastering it. Gamification can be a great way to learn and practice grammar.

There are some key benefits of using gamification in grammar learning:

It can help make the learning process more fun and engaging.
It can help improve retention and understanding by providing a more interactive learning experience.
It can help improve motivation and focus, as the learner actively engages in learning.

Consider gamification if you’re looking for more fun and effective way to learn grammar. It just might be the boost you need to improve your communication skills. Gamification is a fun and effective way to learn grammar. Providing a more interactive learning experience can help improve retention and understanding. Additionally, it can help improve motivation and focus, as the learner is actively engaged in the learning process.

Learn Machine Learning and AI courses with Imarticus Learning.

Become an AI engineer by attending the E & ICT Academy deep learning Artificial Intelligence certificate course. Students will benefit from this AI course as they prepare for jobs as data scientists, data analysts, machine learning engineers, and AI engineers.

Course Benefits For Learners

Students work on 25 real-world projects to get industry experience and prepare for a rewarding career in data science.
You may impress employers and exhibit your abilities with an E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed credential.
This AI Certification will assist students in obtaining lucrative professions in 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.

Understand Quality Metrics Of Chatbot Training Data: Data Analytics Beyond Training In 2022

Posted on July 5, 2022 by Imarticus Learning

Understand Quality Metrics Of Chatbot Training Data: Data Analytics Beyond Training In 2022

A chatbot is a software or a computer program that simulates human communication or “chatter” via text or voice interactions. Chatbot analytics, also known as conversational analytics, chatbot analytics, bot analytics, and chatbot intelligence, is a valuable tool for directing business chatbot trials. This post will help you understand the quality matrix of chatbot training.

What is chatbot analytics?

Users increasingly use chatbot virtual assistants in business-to-consumer and business-to-business environments to conduct simple tasks—chatbot analytics evaluate previous bot conversations to get insights about chatbot performance and customer experience.

The work of a company as a chatbot developer does not finish when their bot goes online. Because of the increased competition in every business, customer experience has become a critical driver in establishing a competitive advantage. After a company introduces a chatbot, it is the right time to monitor how users interact with it.

Understand Quality Metrics Of Chatbot Training Data

Once you recognize how a chatbot works, you can use chatbot analytics and metrics to analyze its success. You can continuously monitor response time, conversion rate, and efficiency enhancement with KPIs to significantly increase it.

Goal Completion Rate: GCR is at the top of our list since it accurately assesses your chatbot’s effectiveness by collecting the proportion of successful user interactions with the chatbot.

Engaged Users: These are active users who have daily or weekly discussions with your bot. The active users recognize the value of employing your chatbot. They enjoy utilizing your bot and continue to patronize your company.

Conversation starter messages: Interactions between the consumer and the bot are bidirectional, and the number of times the bot begins the discussion serves as the foundation for the next measure.

Bot Messages: This indicates the total number of messages sent by the bot during a discussion. We want this statistic to be high since it measures the length of the dialogue between the consumer and the bot.

In Messages: This category displays the user’s messages. We need to know if the user interacts with the chatbot. We don’t need to utilize a chatbot if this category is deficient.

Miss Messages: These are messages that our chatbot is unable to process. This measure may be difficult to compute. The number of times the chatbot misinterprets the input.

Data scientists and data engineers are now among the most in-demand employment categories worldwide. Finance and insurance, retail, healthcare, information technology, and telecommunications have opened their doors to data analytics specialists.

Discover Data Science Certification with Imarticus Learning

Learn how to apply data science in the real world and create predictive models that improve business outcomes. This data analytics course with placement is suitable for recent graduates and professionals looking to advance their careers in data science and analytics. Students can now master data science skills by participating in 25 in-class, real-world projects and gaining practical experience through hackathons, capstone projects, and mock interviews.

Course Benefits For learners:

Learn the fundamentals of data analytics, machine learning, and the most in-demand data science tools and methodologies to become job-ready.
These concentrated sessions with hands-on exercises make learning more effective and efficient.
Students can clear all of their doubts in live sessions and take part in discussions throughout the course.

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

The best stream to opt for becoming a data scientist

Posted on July 4, 2022August 26, 2022 by Imarticus Learning

The best stream to opt for becoming a data scientist

Data science tops the list of the most wanted jobs in the technology world. Data scientists are highly demanded in all the major industries like retail, marketing, health & medical, manufacturing, and many others.

In a nutshell, any data-centric organization can’t simply operate without a data scientist and hence it is the hottest career option in today’s time. If you want to become a data scientist but don’t know how to become one, this article is for you. Keep reading to learn about the best stream for becoming a data scientist!

Which Stream to Choose for Becoming a Data Scientist?

Data Science is a field that is open to all types of aspirants. Although people with a technology background can have more edge than the others, anyone with the required skills and problem-solving attitude can join the field.

Remember that there is no specific requirement for a degree needed to become a data scientist. All it takes is a specific skill set, interest, and passion to enter this field. A good understanding of the contextual applications around streams like maths, statistics, computer science, physics, engineering, etc. is necessary. However, this doesn’t mean if you don’t belong to these fields, then you can’t be a data scientist. You can because people from fields like commerce or medical have transitioned their careers as data scientists by developing the required skill set.

How to Become a Data Scientist?

To become a data scientist, it is very important to have a solid base of statistical programming skills. Further knowledge in data visualization, linear algebra, and programming is a must. A bachelor’s degree in computer science, maths, IT, physics, or any other related field is also required in the field. Alternatively, you can also become a data scientist by taking the right data science course from a recognized institute.

To become a data scientist you should be analytical, curious, and skilled enough to ask the right questions from the right customers with an aim to extract as much data as possible. The right academic background combined with the right skill set can set you on the right path to joining the data science industry.

Skills Needed to Become a Data Scientist?

The most important skills required for securing a job as a data scientist include proficiency in programming languages like Python and R, among a few others. These skills can be easily developed through training and practice.

Below are the other sought-after skills to become a data scientist

Mathematics
Statistics
Risk management
Cloud tools
Programming languages like Python, R, Java, SAS, SQL, AWS, etc.
Big Data experience
Data Engineering
Software Engineering
Product Management
Neural Networks
Quantitative and Qualitative Skills
Dashboard working experience

These are the main skills that are required for a data scientist job. The best part is, that anyone can learn these skills through a variety of courses and study material available on the internet. Alternatively, you can also learn data science online by taking a data scientist course, which includes all of the above modules.

Ready to Build the Required Skillset

Even if you’re from a computer science and mathematics background, you can’t become a data scientist if you don’t have a passion for data science. This field requires passion and interest more than any specific background, always remember that. When you have passion, your life becomes much more interesting in the data scientist profession.

As long as you’re willing to work on yourself and learn programming and other skills we’ve talked about, you can become a successful data scientist – it will not matter if you’re a teacher or a lawyer!

Sure, studying subjects like maths, computer science, and statistics gives you an upper hand, however, the field of data science doesn’t restrict anyone if they have the right skills.

And that’s all about it.

What stream should I select for becoming a data scientist? The answer is, more than choosing a stream, work on the required skill set for building a successful data scientist career. So, don’t wait anymore and take up the right data scientist course or certification to learn data science online!

Supply Chain Stories: How To Get A Supply Chain Analytics Program Operational In Three Months

Posted on July 4, 2022July 5, 2022 by Imarticus Learning

Supply Chain Stories: How To Get A Supply Chain Analytics Program Operational In Three Months

The market for supply chain analytics is currently booming. What is the cause of this surge, and why should you join the movement? This post will examine the driving factors behind supply chain analytics.

Identify Your Key Performance Indicators (KPIs) and Data Sources

One of the first steps in implementing a supply chain analytics program is identifying your key performance indicators (KPIs). These are the most important metrics for any business, as they are critical for demonstrating value and improving operations. It will automatically capture every sale without requiring people to enter data into Excel spreadsheets manually!

Develop an Initial Strategy and Business Cases for the Program

Before you begin to plan your supply chain analytics program, developing an initial strategy and business cases for the program are essential. This step will help you define your goals and plan for achieving them.

Remember: goals should be ambitious but realistic.

Define the Scope of the Project with an Implementation Plan

When you begin a Supply Chain Analytics program, it is crucial to lay out the scope of your project and who will be involved in each phase. You’ll also need to determine who your stakeholders are so they can be included in discussions about the project during various stages.

Define which systems or processes need to be analyzed (e.g., inventory management)
Decide what data sources need access for analysis (e.g., supplier data)

The industry is growing fast

From 2022 to 2030, the global supply chain analytics market can develop at a compound yearly growth rate of 17.6 percent, reaching USD 22.46 billion. And it’s not just the industry that is growing — the number of available jobs for supply chain professionals is increasing, too!

The supply chain always bounces back.

Indeed, there is always a way to pull back from the edge regarding your supply chain, no matter how bad things become. This is what excellent supply chain analytics programs are all about – anticipating problems before they happen and making sure you don’t fall into a rut by making mistakes you can avoid through better planning.

Many of the ways you can use an analytics program to improve productivity include:

Developing more accurate forecasts of demand (based on historical trends)
Allocating resources more effectively based on real-time inventory data
Finding new suppliers who can provide lower-cost products/services than those currently being used in order/delivery processes

As a result, these supply chains must become more innovative, faster, and more efficient.

Discover a supply chain management career with Imarticus Learning

Students interested in the SCM course can get the most recent information by completing the supply chain management certification online.

Course Benefits For Learners:

To provide students a complete understanding of the sector and position them for a prosperous future as certified Supply Chain analysts, we include them in significant technologies and initiatives, including six real-world projects.
Students may prepare for highly sought-after occupations like demand planner or data scientist, which are in high demand among firms today, by completing supply chain analytics courses!
Aspirants will learn to become data-centric and improve Supply Chain decision-making using the Python programming language.

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

5 Tips And Tricks For A Successful Career In AI And Machine Learning

Posted on July 1, 2022August 24, 2022 by Imarticus Learning

5 Tips And Tricks For A Successful Career In AI And Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are two of the most in-demand skills in the tech industry today. And with good reason, these cutting-edge technologies are transforming how businesses operate.

Learning about these technologies is the best way to prepare and excel in this change.

So, if you’ve ever wondered about making a career in AI and ML, you’re in the right place. Here are five tips and tricks to help you succeed in this exciting field.

1. Define Your Goals and Narrow Your Focus

Do you want to become an expert in a specific area, or do you want to use these technologies to solve particular problems?

Once you have a clear goal in mind, you can start to narrow down your focus area. For example, if you want to use ML to solve problems, you may want to focus on data mining, predictive modeling, or natural language processing.

To become an expert in a specific area, you may want to focus on research or developing new algorithms. Whatever your goals, it is essential to choose a focus area you are passionate about to stay motivated and succeed in your AI and ML career.

2. Build A Strong Foundation

A career in AI or ML can be enriching, but it requires a strong foundation in both theoretical and practical skills. It is essential to work with data and have strong math skills.

You’ll need to understand algorithms and data structures well and experience working with large data sets. Familiarity with popular AI and ML libraries and frameworks will also be helpful.

Plenty of resources are available online in the form of courses and in libraries to help you get started. You can also consider an AI or ML certification to dig deeper into the subject.

3. Develop A Portfolio Of Projects

One crucial aspect of any successful career in AI and ML is having a solid portfolio of projects. This portfolio can showcase your skills and abilities to potential employers and help you land your desired jobs.

When developing your portfolio, choose projects highlighting your strengths and showcasing your skills. If you’re starting, you may want to consider choosing smaller tasks that you can complete quickly. As you gain experience, you can add more complex projects to your portfolio.

There are a few things to keep in mind when developing your portfolio of AI and ML projects:

Make sure to choose projects that are interesting to you and that you can complete within a reasonable timeframe.
Try to choose projects that will showcase your skills in both AI and ML.
Don’t be afraid to ask for help from others when needed.With these tips in mind, you’re well on your way to developing a solid portfolio of AI and ML projects.

4. Find A Mentor

Finding a mentor is critical for anyone wanting a successful career in AI and ML.

A mentor can provide guidance, support, and advice regarding career choices and opportunities. Having a mentor can also help you stay motivated and focused on your goals. It allows you to navigate the often-complex world of AI and ML and can provide invaluable insights.

Your mentor is someone who has already made the journey you’re looking to complete. You can find your mentor in your workplace, social media platforms, communities, etc.

5. Network

In today’s competitive job market, having a solid professional network is more critical than ever.

A strong network can provide access to mentors, colleagues, and collaborators who can help further your career in AI and ML. In addition, networking can help you find a job, get promoted, and advance your AI and ML career.

By networking with other AI and ML experts, professionals can stay up-to-date on the latest trends and developments, share ideas and best practices, and find new opportunities.

You can get involved in the ML community, whether attending meetups or conferences or participating in online forums.

You can look for online platforms and communities to find enthusiasts like yourself and network with them.

Conclusion

The field of AI and ML is constantly evolving, so it’s essential to keep updated about these changes.

But if you’re starting, learning the basics will require you to enroll for AI and ML certification. And if you wish to learn from the best of the best, check out Imarticus Learning’s dedicated Artificial Intelligence and Machine Learning course in collaboration with the Indian Institute of Technology.

Imarticus Learning offers chat support and has excellent training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. Please reach out for further clarity.

A Tale Of Tech: Become A Qualified Data Scientist

Posted on July 1, 2022August 24, 2022 by Imarticus Learning

A Tale Of Tech: Become A Qualified Data Scientist

Are you searching for an exciting career opportunity in a profession that is expanding daily? Consider working as a data scientist. Nowadays, most businesses use critical information gathered from their data to monitor success, make educated decisions, plan for the future, and so on.

Data science is among the most buzzed-about fields, and data scientists are in high demand. For a reason: data scientists are working on everything from self-driving vehicles to automatically captioning photographs. Given all the exciting applications, it’s no surprise that data science is a highly sought-after vocation.

Why should you opt for a data science course in 2022?

As the data science field grows, more individuals realize the importance of having a trained data scientist in their team. To undertake data science, you must be able to discover and handle enormous amounts of data. You will frequently be required to grasp and use programming, arithmetic, and technical communication abilities.

How to Become a Data Scientist?

If you do not have any data-related job experience, you can still become a Data Scientist; nevertheless, you will need to establish the necessary foundation to pursue a data science profession.

Data Scientist is a high-level profession; before achieving that level of expertise, you need to broaden your knowledge in a related topic.

Data Scientist Skills

Mathematics
Engineering
Programming
Statistics
Data analysis
Information technology

Data science training is an excellent approach to improving essential data science skills. Expect to master the fundamentals of data science, such as gathering and storing data, analyzing and modelling data, and displaying and presenting data using every tool in the data science toolbox, including specialist applications like visualization packages Tableau and PowerBI, among others.

It is significant to make an excellent first impression in any industry. However, this is especially vital when starting a new job. Everything begins with your portfolio and CV.

Your portfolio must contain the following characteristics:

Your portfolio should emphasize your most successful work.
It must be well-designed and convey a compelling tale about who you are outside of your work.
You should add value to your visitors’ experiences by emphasizing any effect you’ve had via your job.

Data Science Programming Languages and Tools

Python
RStudio Server
R
Hive
Jupyter Notebook
h2o.ai
Tensorflow
Apache Mahout
SQL

Data science is increasingly using machine learning – methods that use artificial intelligence to offer systems the capacity to learn and grow more accurately without being explicitly programmed.

Learn Data Science Courses with Imarticus Learning

Learn how to apply data science in the real world and create predictive models that improve business outcomes. This data analytics course with placement is suitable for recent graduates and professionals looking to advance their careers in data science and analytics.

Course Benefits For learners:

Learn the fundamentals of data analytics, machine learning, and the most in-demand data science tools and methodologies to become job-ready.
These concentrated sessions with hands-on exercises make learning more effective and efficient.
Students can clear all of their doubts in live sessions and take part in discussions throughout the course.

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

From zero to research- An introduction to IIT AI/ML course

Posted on June 30, 2022August 29, 2022 by Imarticus Learning

AI & Machine Learning in Everyday Life

The importance of Artificial Intelligence (AI) is constantly on the rise and so is its involvement in our everyday lives. Although we don’t often think about it, AI is everywhere.

From chatbots that communicate with us on various online shopping platforms and websites to social media platforms that target audiences and advertise products based on our searches, AI is encoded everywhere. Being such a pertinent part of business, these days makes enrolling in an artificial intelligence and machine learning course a viable option to ensure a lucrative offer in the job market.

Here are 8 ways AI is present in our everyday lives without us even noticing:

Face recognition locking on our phones
Friend suggestions, product/service advertisements based on searches on social media
Spell checkers and Grammarly tools installed on emails and messaging portals
Google searches
Voice assistants such as Siri and Alexa
Smart home devices such as air conditioning machines, electrical switches, refrigerators, and so on
Google maps and other satellite-based trackers
Content suggestions on Netflix based on your watching history

IIT AI/ML Course

Given the way AI is becoming a part and parcel of our lives, the Indian Institute of Technology (IIT) is offering AI/ML specialized courses so that you can gain in-depth knowledge and skills in the applications and techniques associated with machine learning. The idea is to upskill professionals and train them in a manner so that they are ready to take on high-paying jobs in the world’s most demanding computer language.

These are certificate courses that span over a period of 6 months and during this time you will be taught the following subject areas:

Basics of Python
Mathematical Background
Introduction to Machine Learning
Regression Analysis
Optimization in ML
Unsupervised Learning
NLP and text analysis
Feature Selection and Dimensionality Reduction
Reinforcement learning

Outcomes of the Program

Are able to quickly and relevantly gather insights by analyzing data
Are able to come up with predictive models that use decision trees and neural networks
Can carry out mathematical operations on an array of data
Are skilled enough to operate Pandas so that you can manage data, rearrange them and carry out various kinds of analysis
Can create text classifications systems making use of learning methods and linear classifiers
Professionals can compare optimization techniques and how they effectively solve learning issues across platforms and models to reduce the extent of errors

Who Can Apply for the IIT AI/ML Course?

The artificial intelligence and machine learning course is perfect for anyone keen on learning about machine learning.

Additionally, this program is the right fit for professionals who understand computer programming language and has completed their graduation with preferably a year of practical experience in the industry. You will find this course if you:

Are tasked with machine learning projects or software development
Wish to be at the helm of machine learning projects or want to work in this field
Already have practical knowledge of programming languages such as C, C++, and java

Why Should You Go for this Program?

When you enroll in the artificial intelligence and machine learning course at IIT, you are to get the following benefits:

Get a chance to learn and earn a degree from the country’s best engineering school
Get a chance to participate in interactive online learning sessions which will be in live mode
Will be able to interact and exchange ideas with the best faculty comprising of the top industry professionals
Engage in productive peer-to-peer networking and learning
Build a strong foundation in concepts such as high-level Python programming, AI, and ML
Participate in the biggest placement on-campus drive

Conclusion:

The importance of artificial intelligence and machine learning courses will continue to be on the rise given the greater involvement of AI in our daily lives. From healthcare, banking, financial institutions, gaming & entertainment to the airline industry, AI is a necessity, and enrolling in the IIT AI/ML course will equip you with industry-specific skills that will help you in every aspect of your professional life.

The two paths from Natural Language Processing to Deep Learning

Posted on June 30, 2022August 29, 2022 by Imarticus Learning

The two paths from Natural Language Processing to Deep Learning

Natural Language Processing is a branch of linguistics, computer science, and artificial intelligence that deals with the interaction between computers and human language, in particular how to design computers to handle and evaluate huge volumes of natural language data. We want a computer that can “understand” the text in documents, including its context and subtleties.

As a result, the papers’ data and insights may be correctly extracted by the technology, which can also classify and arrange the documents themselves.

Massive amounts of unprocessed, text-heavy data need a system like this, which is widely used in machine learning. Professionals with expertise in designing models that analyze voice and language, find contextual correlations, and generate insights from this unprocessed data will be in high demand as AI continues to grow. Natural Language Processing and Deep Learning with Python are one of the most common phrases used in the domain of Artificial Intelligence nowadays.

In machine learning and artificial intelligence, a technique known as “deep learning” mimics human learning processes. Data science, which encompasses the statistical analysis and forecasting models, relies heavily on deep learning techniques to do its work. For data scientists, deep learning is a godsend since it speeds up the process of processing and understanding massive volumes of data.

It is possible to think of deep learning as the automation of predictive analytics. Deep learning algorithms are piled in a hierarchical structure of increasing complexity and abstraction, while typical machine learning algorithms are linear.

Neural Networks and Deep Learning

A Neural Network, also known as an Artificial Neural Network, is made up of layers. Imagine the neurons in a human brain; they are the computing units, and they form a single layer when layered. stacking neurons together creates several layers. It is termed the input layer because it contains the data that we are working with. We run our algorithms and get an output, which is then utilized to do our computations for the following layer, the output layer.

At each successive layer, all of one layer’s neurons are linked to those at each successive layer, which are then linked to the next layer, and so on, until we reach our output layer, where we achieve our desired outcome for the specific data we were working with. Those layers that are between the input and output layers are referred to as Hidden Layers. A Neural Network is the result of this process.

A deep neural network is an artificial neural network with two or more hidden layers, and a model built on a deep neural network is referred to as Deep Learning.

What are the main components of Natural Language Processing?

NLP consists of a number of components, a few of them are mentioned below:

Analysis of morphological and lexical patterns.
Syntactic Analysis: Study of logical meaning from a given part of the information, be it text or audio.
Semantic Analysis: Used to analyze the meaning of words.

Why Certificate Programs In Data Science Are Gaining Popularity

Posted on June 29, 2022August 29, 2022 by Imarticus Learning

Why Certificate Programs In Data Science Are Gaining Popularity

Data science has emerged as one of the most aspiring career options in recent years. Moreover, with the availability of specialised courses and companies understanding what data analysis can do to their business, this is now a profession that is desired by many.

But why has the data science career become so popular in recent years? Well, to understand that, you need to get acquainted with the idea of data science first.

What is Data Science?

Data science is the scrutiny of data through various methods, which include manual as well as the use of different software. The main aim here is to analyse and understand the pattern in a set of data and use it to the company’s advantage. Now, this advantage can be anything, starting from developing a new product to rectifying the gaps in the new one.

A data scientist’s job is to extract the raw data, clean it and present it in a simpler manner. In this regard, a data science course enables a person to examine large amounts of raw and unclean data by processing and extracting information from it.

Why is Data Science Popular?

Here are some reasons why a data science course is so popular nowadays –

It is everywhere

The presence of data science is everywhere. From banking and finance to healthcare, from disaster management to education, and from e-commerce to retail, you will see data science in each field. Today, you will see data science in the entertainment industry also. Information technology is evolving, thanks to data processing and examination. Big data and cloud computing have changed the data science game entirely.

This is the reason why every student today is choosing a data science career.

The field is hot, and the pay is hotter

The salary in the data science field is great. After five years, the pay grade will get even better. Data science will be here for the next two decades at least. So, the salary will keep on rising because its popularity will surge even more. No wonder it has become a lucrative career option. According to Glassdoor and other job websites, data science continues to be one of the highest-paid fields in 2022? The reviews of data science careers are so positive, and the income growth is stupendous. That is another reason why certificate data science courses are becoming increasingly popular.

Low entry barrier

Full-time data science courses have age and academic eligibility. You also need to have a STEM background for most of the programs in top colleges and universities. Certificate data science courses don’t discriminate much and give everybody who’s interested a fair chance to become a data scientist. This can also be a reason for the growing popularity.

Better PCs, cloud computing and open-source frameworks are changing the game

Although data science does not require a heavy computer these days, still a computer with good RAM and GPU is a must for data science. In earlier days, such heavy-duty PCs cost a bomb. On top of that, the PCs then were a far cry from what they are today. The PCs also cost a lot less these days. This is indirectly promoting data science.

Another reason is the increase in cloud computing. You don’t need a more powerful local server and a large storage capacity. The cloud is almost infinite for this matter. Also, open frameworks like Tensorflow and PyTorch have made the cumbersome job easier and more enjoyable. Everything is breaking the convention these days.

Certificate programs are shorter and cheaper than regular data science courses

Although full-length data science programs are the best choice, not everybody can complete a full-length course. The reason behind this is the lack of time. A regular college student has time on his/her hands, but a working professional doesn’t. That is the reason why certificate programs in data science are becoming immensely popular.

Final Words

Considering the popularity of data science and what it can be in the coming years, it is fair to assume that the demand for a well-trained and skilled data scientist will be significant. So, if you plan to make the most of this opportunity, then enrol for a data science online training course by leading education institutions like Imarticus.

Hiring Managers: Become a supply chain analyst with 5 characteristics

Posted on June 29, 2022August 29, 2022 by Imarticus Learning

Hiring Managers: Become a supply chain analyst with 5 characteristics

Supply chain specialists or analysts ensure that a company’s supply meets consumers’ demands. Their responsibilities include keeping a business on a budget, guaranteeing timely delivery, and overseeing the total supply chain operations of a business. They enhance the productivity of a company’s supply chain operations using data collection and analysis.

To become a supply chain analyst, one needs to have specific knowledge. That means the regular stream of study will not cut it. Following their graduation, one needs to complete a professional IIT Supply Chain Management Course. However, completing that course is not enough; a professional in this field must possess a few essential skills. Read on to learn about them.

5 Key Qualities of a Supply Chain Analyst

Supply chain management involves integrating and overseeing processes where software, machines, and people all play a crucial role. Here is a list of the top essential characteristics required to become a supply chain analyst:

Strong communication skills

Communication skills and supply chain processes go hand-in-hand. That’s because supply chain managers communicate requirements to all channels, train staff, and lead others within a company’s supply chain.

They need to interact through telephones, chat apps, texts, email, and in person. Thus, honing technical, verbal, and written communication skills will effectively serve their purpose.

Data analysis

They need to use and analyze data accurately for tracking demand, sales trends, shipments, and orders. They must be able to figure out the inefficiencies and weaknesses of the supply chain. Additionally, they should have excellent math skills to estimate savings and costs.

Project management potential

Whether they are trying to upgrade down-chain processes, maintain a smooth flow of operations, implement something new, or enhance a pre-existing supply chain, project management skills are a necessity.

PMP education, understanding of Lean process management, and statistical process control will help them to reduce errors, increase efficiencies, cut costs, and improve the supply chain. Most project management procedures teach them to avoid impacting consumers negatively, causing morale problems, or burning out staff.

Flexibility

There are rules for successful supply chains, but solving problems does not always correspond to bookish knowledge. In simple words, they need to think out of the box, embrace change, and support those who bring innovations. This will positively impact productivity as well as other KPIs.

Exceptional computer and software skills

Nowadays, it is irrelevant to manage supply chains with primary spreadsheets & heads for figures. To keep the processes, products, and people in line, they require using competent software.

New-age technologies such as the Internet of Things, machine learning & artificial intelligence are in demand. The potential to instantly understand the latest computer programs and learn how they blend with up-chain or down-chain systems is vital.

Eligibility Criteria to Become a Supply Chain Analyst

Wondering how to kick start your career in supply chain management? Following are the minimum eligibility terms for your reference:

Bachelor’s degree in logistics, supply chain management, or a related subject
Strong analytics and data collection skills to upgrade product delivery, mitigate risks and identify trends
Proficiency in mathematical analysis, SQL analysis tools, and spreadsheet applications
Knowledge of relational databases, ERP systems, and MS Office
Work experience of 1 to 2 years (preferable)

Note that recruiters may give training to beginners on logistics management systems and in-house inventory to improve their skills.

Summing it Up

The supply chain forms the centre of a business’s operations. Supply chain analysts are in charge of a product’s journey, starting from sourcing raw materials to making sure it satisfies consumers. They are the backbone of a company that engages in contract and financial management.

They are responsible for planning projects and building relationships with a solid knowledge of warehousing, transportation, and manufacturing. As such, recruiters prefer candidates having professional certifications in supply chain management, logistics, or related disciplines. So, increase your job opportunities with a noteworthy supply chain certification online from leading educational institutes like Imarticus.