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Category: Management

Think You Can’t Master AI? Learn Artificial Intelligence from Scratch

Posted on by Imarticus Learning

Think You Can’t Master AI? Learn Artificial Intelligence from Scratch

There aren’t many fields in today’s world that are as interesting and entertaining as AI or artificial intelligence. Moreover, the segment is booming now and growing at a pace not understood before. Innovation and the introduction of new technologies are helping to fuel this fire, along with its widespread application in almost every walk of life. So, if you are wondering how to become an AI engineer, then you are at the right place; keep reading.

What is Artificial Intelligence?

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Before moving on to the topic of how to become an AI engineer, it is useful to learn more about the field itself. Artificial intelligence has been built to simulate the tasks that can be associated with human intelligence. AI solves real-life problems by using both supervised and unsupervised computer programs. The AI models use large data sets to learn how humans would behave while trying to complete a particular task, and then they would spend time learning, perfecting, and doing it without any human intervention.

The field of AI includes:

Applications of Artificial Intelligence

Most AI applications can be bifurcated as either strong or weak.

  1. Narrow or Weak AI: The automated computer systems recognise patterns in large sets of data, and then after observing and learning them, they accomplish the respective task. Examples of narrow or weak AI include recommender systems in Netflix and YouTube or any other streaming platform, smart speakers or Chess bots. This system can adapt to inputs, but they are unable to perform something that is out of its given parameters. However, they have wide usage in many microservices and several macro services.
  2. Strong AI: It is also called Artificial General Intelligence, and it finds a lot of applications in the field of robotics. This AI is reserved for the longer term and is mostly in the stage of infancy. This part of AI is mostly used to create control and prediction models.

Why Learn Artificial Intelligence?

Why should you learn artificial intelligence? AI is one of the most exciting fields in the Computer Science stream. Moreover, it is also at the fore of discovering solutions to real-world problems that are making our lives hard-pressed. This system is learning and offering solutions in almost every walk of human life.

So, the demand for capable professionals is on the rise and will continue to rise in the coming days. So, being well-versed in this field will help you get employed in some of the leading organisations in the world.

What Does an AI Engineer Do?

An AI engineer does a lot of things as their responsibilities and roles vary based on the industry they are employed in. But speaking generally, AI engineers are capable of developing systems or apps which help to quicken the decision-making process and enhance it by considering all the factors and turning it into an efficient protocol-driven method.

AI engineering is, in its entirety, a complex task which can: 

  • Achieve the objectives it has been assigned 
  • Use logic for solving problems and performing an analysis of the probability of achieving success and incorporate that into the machine learning model
  • Direct and monitor projects that are being developed by analysing systems
  • Comprehension and application of best practices in data mining, processing of data recognition of speech and robotics 

How to Become an AI Engineer?

If you wish to become an AI engineer, then it would be advisable to start by developing a background in Python programming and having a strong grasp of the basics. While you are studying Python, you need to master libraries like Matplotlib, Jupyter, Pandas, Numpy, and Scikit. Make sure you have performed some neural network programming projects of your own.

At the same time, you should also strengthen your mathematical abilities, as AI and ML require mathematical aptitude as well as awareness regarding some mathematical concepts. Therefore, you should choose pre-engineering or non-medical after the 10th class.

Additionally, you need to build your skills in data structure and algorithms and relational database technologies like SQL and NoSQL. There are certain other in-depth applications as well.

After clearing 10th and 12th-grade studies, focus entirely on getting admission in a graduate program that offers Data Science, Artificial Intelligence or Machine Learning as a major. Or you could opt for it after graduation as well as take it up as a PG course. After that, you can spend time building AI and ML projects to gain practical experience in industrial-level projects.

The IIT AI ML course

Imarticus Learning has created a course exclusively for Artificial Intelligence and Machine Learning enthusiasts in partnership with E and ICT (Electronic and Information Communication Technology) Academy at IIT Guwahati. This certification course in artificial intelligence and machine learning is taught by world-class faculties of the IIT, helping you get better exposure.

To sum up, if you wish to learn artificial intelligence from scratch, it is not a challenge anymore. There are courses available online, like the one from Imarticus Learning and ample study material that will help you better understand the concepts and resolve any confusion you have. Also, with ample job opportunities, you can easily find employment to gain relevant work experience. 

Course | Data Visualisation with R Course (Includes Job Placement)

Posted on by Imarticus Learning

Course | Data Visualisation with R Course (Includes Job Placement)

R programming is one of the in-demand computer languages in the field of data analytics and data science. So, it comes as no surprise that many data analyst aspirant prefers to enrol on an R programming course in place of a Python programming course. That is because it is certainly a better option for data visualisation. The graphs and statistics are more elaborate than Python and are more intuitive.

Moreover, when compared to Python, it is also easy to master this computer language, and the learning curve is not too steep either. Other than that, most of the features in both programming languages are similar to a large extent.

What does the R Programming course consist of? 

If you are taking up a data visualisation course, then make sure you take up a course in R programming as well. What you will get to learn in this course is primarily the Grammar of Graphics. It is an extensive system which is used for building graphs and elaborately describing them. After you learn to make graphs in the R programming course, it progresses to the library and the stuff that comes under this subset of data visualisation.

First of all, you are taught how the package for data visualisation in R and ggplot2 is applied to generate box plots, basic bar charts, line plots, histograms, pie charts and scatter plots. These different types of graphical plotting will also help you master further customisation. The R programming course also teaches other techniques for visualising the data apart from generating charts and plots. You will also be taught about annotations and labelling in these graphs.

Additionally, there is a package called leaflet, which helps you to generate map plots and is one of the most powerful data visualisation packages in R as it can display data at various levels for better visualisation. It also helps plot data based on its geolocation, so it is highly useful for the meteorological department, where various weather-based data are displayed.

Finally, in an R programming course, you will learn how to build creative, intuitive and interactive dashboards using packages like R Shiny that can help to alter the appearance of your data app, which has been built in R.

Where can you enrol for data visualisation with an R course?

Although data visualisation courses are extremely popular and numerous institutes offer them, students should choose one based on their needs. A student should pick up a course that helps them to learn some useful techniques and give them hands-on experience through practical training in the labs and trying out various techniques in R. It will aid them in building various graphical models of data.

Many top technology companies are offering data analysis courses from their stables. But there is no data analytics course with placement. Moreover, the focus in these courses is rarely on R, which can be quite frustrating as a student cannot get an all-round perspective of the data analytics course.

In this regard, a solution can be the data analysis course offered by Imarticus Learning. It focuses on both Python and R and gives both programming languages equal weightage. You will be given both a basic run-in and advanced guidance on plotting various statistics and graphs with the help of R. You will get both classroom training and live online training. This coursework will give you enough exposure and help you succeed as a data scientist.

But before you enrol in this course, please ensure that you have some programming knowledge beforehand because this is an advanced course. Many websites and online academies have free R programming courses. In these courses, you learn about various packages like ggplot2, dplyr, mlr3, knitr and tidyverse. Once you have a good base in programming, especially in R, you can pick up various other requirements for the data visualisation course. You could also take up an internship role to get more practical exposure.

To sum up, finding an R programming course that offers theoretical and practical exposure is crucial. It helps you to get an in-depth understanding of the same and avoid facing troubles while implementing the same in the real world. So, find a course of your preference and secure placement in this popular field of data science. 

Introduction To Data Analytics: Technologies, Jobs and Careers

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Introduction To Data Analytics: Technologies, Jobs and Careers

Nowadays, Data Analytics has become a sort of a buzzword in the data science industry. Just have a look at any of the job websites, and you will see that there are many vacancies in data science. Even Harvard University has labelled it as one of the hottest job fields in the USA, and India is also a part of the same trend.

So, what is the reason behind this craze for data analytics and data science jobs? Let’s have a look.   

What is Data Analytics, and what does a data analyst do?

Data Analytics is a subset of Data science. It is where raw data is cleaned, analysed, interpreted and displayed using several approaches with the help of business intelligence tools. These data analysis tools transform raw data into interpretable information that aids in making successful decisions.

But how is the data presented? Raw data is converted into meaningful information, statistics and explanations with the help of tools and techniques. There are multiple tools that data analysts use for generating all the interpretations of data.

At the same time, there is some programming expertise that a data analyst requires. For example, they could learn either of the two programming languages, R and Python, to process the data. For storing this data, they could use SQL. But the entire tech tools a data analyst needs are mentioned in the next section. So, just continue to read the topic till the end.

Technologies employed by Data Analysts

Several tech tools and programming languages can make the life of a data analyst easier. As already mentioned, data analysts have to process raw data and use it to generate various graphical representations. For that, they need to –

  • Identify the data they require
  • Collect raw data from the specific source they have identified
  • Clean the data and remove the inconsistencies
  • Analyse the data
  • Interpret the results

To perform these functions, data analysts use several tools. First of all, let us delve deeper into the programming languages that come in handy.

  • Python
  • R
  • SQL
  • Hadoop for big data

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The best thing about these programming languages is that there are multiple online resources to master these programming languages. You will find millions of tutorials to learn Python online.

Apart from the programming languages, you need to master some of the tools that are mentioned below:

  • Google Sheets
  • Microsoft Excel
  • Tableau
  • SAS(Statistical Analytical System)
  • Microsoft Power BI
  • Jupyter Notebooks

Mastering these tools and programming languages is quite important because they help you by making your job easier. You get to learn all these in a good data analytics certification course, and you can get in touch with us at Imarticus Learning.

Jobs for Data Scientists

Data science jobs stretch across various sectors. It has always been used for business, in both sales and marketing. Not only that, it is also handy for retail so that the inventory can be managed. Apart from business, it is used in medical infrastructure, operation research, finance and allied sectors. It is also being used in the entertainment field for various data-based jobs, especially for calculating the TRP of various shows.

Now it is also being used in education, law, security, automobile industry, energy sector supply chain, social media and in various fields of research. Data analysis has crept into almost every industry as it is finding a lot of applications in various fields.

But which are the most popular roles that are also enjoying a huge career and salary growth? Some of these roles are mentioned below:

  • Medical and health care analyst
  • Market research analyst
  • Business analyst
  • Business intelligence analyst
  • Operations research analyst
  • Intelligence analyst

These jobs are the top roles across various industries and job sectors. You will find multiple listings of these roles in all the leading job portals. Some of the beginner roles start above the ₹5,00,000 pay bracket. However, if you have completed a good data analytics certification course, then you will be able to command a good salary from your employing organisation.

The overall career of a Data Analyst

Choosing data analysis as a career path is a great decision, especially in the current market. After bagging a beginner role, try to gain more technical skills. Then you move to the position of a data scientist.

But there is a clear bifurcation of the career paths. For example, if your interest largely lies in statistics and data analysis, then try out business intelligence and analysis. But if you love the tech side, pick data science and data engineering as your career.

To conclude, the opportunities for data science jobs in the current scenario are increasing every year and are slated to grow even further in the coming years. So, being prepared with the necessary knowledge and technical know-how will greatly boost your career. In this regard, you can always look at the Post Graduate Program in Data Analytics and Machine Learning from Imarticus Learning to enhance your skill set. 

Learn Hadoop Online: A Brief Summary of Apache Hadoop

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Learn Hadoop Online: A Brief Summary of Apache Hadoop 

Introduction To Apache Hadoop

A type of open-source software based on a Java programming framework, a Hadoop system is programmed to address any hurdle it faces. Using a skilled framework distributes unclear and large amounts of data in multiple programming systems.

Apache Hadoop provides increased effectiveness and efficiency with high productivity. Though it is a single server, it extends to various networks further connected to machines.

Components

Apache Hadoop has several components which play a critical role in bringing out the responsibilities of Hadoop. They are as follows:

  • Library deals with all the complications and discrepancies at the top layer of an application.
  • The Hadoop Distributed File System is the Storage unit that helps process stored data in various chunks and is efficiently transmitted with the help of cluster nodes. 
  • MapReduce is the processing unit. 
  • Yet Another Resource Navigator (YARN) is the resource management unit. 

Role of Apache Hadoop In Big Data

In the era of digitization, all information has to be stored digitally, and it is a huge challenge to control and manage all the data. It thereby creates a need to develop a system that can control, manage and handle an overabundance of such data. Thanks to Apache Hadoop, one can store and manage big data. Various roles played by it are:

  • It stores data at a lower cost: 

Apache Hadoop is designed in such a way that it can store data at much lower costs as compared to other systems available.

  • Velocity and variety: 

Apache Hadoop processes data and gives information to enterprises on time. It uses different techniques and tools to structure the data into valuable outcomes.

  • Provides security to big data: 

Apache Hadoop is also used to detect cyber attacks on the system as it uses different tools and techniques. It is also helpful in recognizing the attackers that try to attack and want to gain access.

Advantages of Apache Hadoop

Some of the advantages of Apache Hadoop are mentioned below.

  • Flexibility: In Apache Hadoop, data can be stored in semi-structured and unstructured formats. It also enables enterprises to access new data sources easily.
  • Scalable: Traditional systems have limited data storage capacity. On the other hand, Hadoop is highly scalable as it is distributed and stored across several servers.
  • Resilient: This system is fault resilient as it stores data in several nodes, and there is another copy to use in the event of a contingency.
  • Fast: The storage method used by Hadoop is rooted in a distributed file system that manages clustered data. The tools used for processing data are often located on the server where data is placed, resulting in faster data processing. 

Discover Data Analytics and Machine Learning Certification With Imarticus Learning 

Our Data Analytics Courses will help students:

  •  Learn job-relevant skills with the most in-demand data science tools and techniques. 
  • Master data science skills through 25 in-class, real-world projects and case studies from industry partners.
  • Learn with a curriculum that focuses on outcomes and a pragmatic learning style, including SQL programming, big data, Hadoop, data visualization with Tableau, etc. 
  • Obtain guaranteed interview opportunities and get hired.

Conclusion 

Ideal for recent graduates and early career professionals, this elite Data Analytics and Machine Learning Course will help you take your data analytics and science career to heights you have never imagined! 

For any queries, please do not hesitate to Contact Us or drive to one of our training centers in Mumbai, Pune, Thane, Chennai, Bangalore, Delhi, and Gurgaon. 

Transitioning to Data Science: How To Get There?

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Transitioning to Data Science: How To Get There?

The emergence of big data has prompted businesses to rely on data to make informed decisions. But how do you make sense of all that data?  That’s where the data scientist enters the scene.

A data scientist collects, analyses, and interprets data to make business recommendations. They do this by using AI, Statistics, and Computer science. They can apply these skills to a wide range of industries such as healthcare, finance, and retail.

The Data science career is an excellent choice for those interested in working with data. And it’s pretty rewarding with the right skills. Whether you want to advance in your career in data science or start, many options are available. One of the most effective ways is through data science courses.

These courses enable students with the right skills and knowledge to succeed. Let’s explore how you can transition with the help of proper data science online training.

Transitioning to Data Science via Applied Learning Courses 

The easiest way to transition to the data science space is to learn the fundamentals of the subject. Consider enrolling in a data science online training program that incorporates applied learning.

This learning method is convenient since students are not restricted to physical classrooms. Also, it offers students the flexibility to learn at their own pace, anywhere, and at any time. 

The learning model in an online environment is flexible and includes various resources. These include videos, lectures, articles, books, and one-on-one interactions with the instructor. Next, let’s talk about what you’ll need to learn in your data science course.

Data Science Online Training Curriculum

To transition into data science, you’ll need to learn the fundamental concepts, including:

  • Statistics
  • Probability Theory
  • Probability Distributions
  • Hypothesis Testing
  • Statistical Tests

These topics form the core of any data science course. Moreover, an understanding of Machine learning and Predictive Modelling is also required. Apart from these topics, you’ll also learn about some essential tools and languages. These include:

  • Python
  • Tableau
  • SQL
  • NumPy
  • Pandas

Combining these tools with fundamental concepts will help you in your data role.

What Makes a Good Data Science Online Training?

So, we’ve considered the curriculum requisites for transitioning into a data science career. Now, let’s examine what makes a great data science course based on applied learning: Faculty from top institutes such as IIT/IIM and other industry experts.

  • Live instructor-led online sessions with access to the session recordings and notes.
  • Online discussion with course faculty and peers to clear doubts and brainstorm.
  • Real-world case studies and live projects to provide insight. These concepts can predict property value, heart disease, taxi fare, etc.
  • Regular assignment assessments to track progress.
  • A Capstone project to collate and present the course learnings.
  • Career support activities, including resume-building workshops and mock interviews for job placements.
  • Startup mentorship and funding for those looking to start their ventures.
  • Certification of completion.
  • Access to an alumni network and a chance for an on-campus immersion program.

A course providing these things will ensure that you learn data science skills and make data-driven decisions. One such data science online training based on the concept of applied learning is offered by Imaticus Learning.

About Imaticus Learning

Imarticus Learning, in collaboration with iHUB DivyaSampark @ IIT Roorkee and the Department of Science & Technology (DST), offers one of the best certification programs in Data Science and Machine Learning. 

Since the program is made especially for the early and mid-level professionals, you’ll understand the various aspects of data science and learn how to implement and apply these concepts to real-world problems. 

Imaticus Learning covers all the points that make for excellent data science online training program, as mentioned earlier. Check out the success stories of those who transitioned into the data science field. Some alumni work with big brands such as Accenture, Capgemini, KPMG, etc.

You can visit the Imarticus Learning website for live chat support. You can also drive to one of their training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Conclusion

As data becomes central to decision-making in organizations, those with the skills to analyze and interpret it will be in high demand. Starting or transitioning to a data science career requires a strong foundation. And to help you with that, you can look for result-oriented data science courses.

Attending these courses helps you develop the skills needed to become a top Data scientist, Data Analyst, Business analyst, Data manager, Business Intelligence expert, etc.

This blog discussed what constitutes a top data science online training program and explored one such institute in Imaticus Learning. Feel free to check it out. Also, let us know your opinion on the necessary things for transitioning into the data science career.

Top 10 Popular Data Analytics Tools For A Better Career

Posted on by Imarticus Learning

Top 10 Popular Data Analytics Tools For A Better Career

Data is definitely today’s one of the most valuable assets. We all know the limitless power of data and how it dictates business operations. Whatever the scale of a business, data makes the core of it. Not only businesses or IT hubs are using data analytics, but various other fields are also taking the advantage of it. Let us take a very simple instance to understand how data analysis works.

Let us take sports as a case study. This will help you understand that a field that is remotely connected to science and technology is extracting its benefits. Assume X is a tennis player who has been on the circuit since 2005. He has been touring all over the world, participating in various tournaments, and has recently put his shoes off. Now, you get to see his performance graphs, how consistent he was, which were his favorite shots, etcetera on television channels. This is the most common scenario when the stats are analyzed post-retirement. Have you ever thought about how that is possible? 

 For instance, all the records and stats right from his first match to the final match with a comparative analysis require rigorous data analytics. It is humanly impossible to gather all the data and then filter out necessary ones manually. 

Here comes data analytics tools that help you perform the task effectively. Go through the upcoming sections to get familiar with the new-age data analytics tools.  

An Introduction to Data Analytics

We are currently living in the world of data and therefore you will often be advised to learn data analytics. 

Data analytics tools are particular applications and/ or software that enable data analysts to work with a large volume of data. Data, in its crudest form, is unstructured and haphazard. A data analyst filters out unnecessary data and then collates the required information in the database. This is structured data that can be used effectively for future references. 

Data analytics tools help manage and work with data. In other words, useful data is actually the derivation of structured data via data analytics tools. Find below a list of the latest tools that are used by the giants of the industry like Google, Facebook, Apple, Dominos, and others.  

Top 10 Data Analytics Tools

Python

One of the most widely used programming languages among AI developers today is Python. It can be used effectively to run programs because it does not need to be pre-compiled into machine code. Additionally, it has an automatic memory management system and a dynamic type system that support a wide range of programming paradigms.

Microsoft Excel

It may sound trivial but in reality, Microsoft Excel works as a strong data analytics tool. Numerous filters, formulae, and other features enable users to analyze data effectively with Microsoft Excel. Asa matter of fact, this is the very tool we all perhaps get to learn in our schooldays. 

RapidMiner

As the name suggests, RapidMiner is an excellent data analytics tool used for data mining. Data mining includes scopes such as visualizing, filtering, structuring, storing, and managing big data. 

QlikView

QlikView is a self-service business analysis tool that you should learn to be at par with the most recent trends in data analytics. Samsung and CISCO are among the tycoons that use QlikView for data analytics.

Apache Spark

Apache Software Foundation came up with one of the most useful data analytics tools that empower users with multiple features. Above all, this is an open-source application used by Visa, Oracle, and other big names. 

Talend

If you are eyeing a data integration tool, then Talend is the suitable solution for you. Talend incorporates an ELT backbone which ensures the safety and simplicity of the interface. 

Splunk

Splunk is among the widely used data analytics tools to visualize, filter, and analyze raw data. It is favored and trusted by 92 of the top Fortune 100 companies.  

Tableau

Tableau offers you a simple, user-friendly interface to work with a cluster of structured and unstructured data. It is one of the rare tools that allows you to work on live data sets. 

Datapine

If you want to get a grasp of data analytics, you should start with a simple yet effective analytics tool. Datapine is one of those tools that allows beginners to work with a large scale of data without complicating things.  

SAS Forecasting

Data forecasting or data prediction is an important part of data analytics. For example, you may need to predict a stat for the future based on available current data. SAS Forecasting is the ideal tool to do such things easily.  

Best Data Analytics Certification Course

Data analytics is a topic that has earned a reputation in and outside India as one of the vital operational wings of the business. Competent data analysts are placed in big national and international agencies with handsome salaries. Thus, students often look for the best data analytics certification course. Imarticus has an integrated post-graduation course on data analytics that prepares trainees for a bright future. 

Data Analytics Course with Placement

You should learn data analytics from a reputed institution that offers you a data analytics course with placement opportunities. 

Placement immediately after the course will boost your morale and also introduce you to the real world of data analytics. You will get to know how the giants of industries run their businesses with the power of effective data analytics.  

How supply chain analytics are enabling organisations to become more efficient

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How supply chain analytics are enabling organisations to become more efficient

With the growing competition in the market every organisation tries to enhance their company’s effectiveness to its maximum potential. Supply chain analytics enables organisations to strategise their business and carry out predictive planning that could benefit their sales and bring in maximum profit. In this article, we will explore how supply chain analytics benefits companies and why you should choose a career as a supply chain analyst.

What is Supply Chain Analytics?

The work of supply chain analytics is to produce insights, recognise patterns, and assess the information provided by the supply chains. This information or data is extracted from the supply chain execution systems and the management of inventory, order, warehouse and transport. 

Here’s a brief account of the four basic supply chain analytics that enables organisations to build more profitable operations to increase their efficiency:

  • Descriptive analytics 

This assists in providing visibility to the suppliers and analyses the past sales data extracted from both the internal and external supply chain execution systems. This enables the suppliers and all the other sales channels to draw comparisons through the historical data and recognise the changes in the present status of the sale and understand the reasons causing them.

  • Predictive analytics 

Predictive Analytics enables companies to analyse future events and their possible impact on the business. This helps the companies to eliminate risks and prepare effective plans and strategies to deal with any disruptions in the future and act accordingly.

  • Prescriptive analytics 

This takes into account the outcomes of both Descriptive and Predictive Analytics and puts forward suggestions that help the company mitigate any kind of disruptions. It provides better ways to tackle problems by interpreting the data of their own business activities along with their partners. 

Why choose a career as a Supply Chain Analyst?

best supply chain management and analytics courses

A career in supply chain management is very steady and lucrative. It has a lot of opportunities and provides growth and employee satisfaction. The SCM Imarticus is a professional supply chain management online training platform 

Which provides various supply chain management certification course options that will help you learn all the know-how and open doors for you in the field of supply chain management.

Following are the ways in which Supply Chain Analytics benefits organisations and increases their efficiency:

Data transparency in the supply chain management

The supply chain analytics helps in improving data visibility for the organisations helping them in making informed decisions to enhance their supply efficiency and also analysing what went wrong in the business and how to improve their supply chain management system.

Mitigation of risks and other liabilities 

Supply Chain analytics analyses the potential risks in the future and also suggests ways to avoid those disruptions which help the companies to prepare themselves to tackle any challenges and liabilities associated with supply chain management. 

Cost-effective management

Supply chain analytics eliminates the manual tasks like accounting, data entry, or calculative works which were done by the human workforce. This helps in cutting down costs and also produces more accurate data and billing practices at the same time. 

Selection of better partners

Supply chain analytics provides information about the vendors, their way of handling the business and how relevant they are in the business. This helps the supply chain managers to select partners who are a good fit for the company and can increase its efficiency.

Demand prediction

Supply chain analytics predicts the growing trends in the market to ensure the meeting of the demands of the consumers. It helps the companies to determine what products should be stored as they can bring in more profits and what can be minimised.

Efficient flow Of products

Supply chain analytics ensures an effective flow of goods as it regulates every facet of the supply chain by using its tools and features. It also enables better communication in the supply chain which mitigates the issues of cost and improves the relationship between suppliers and customers.

Conclusion

Supply chain analytics has become one of the most essential elements in supply chain management and uses its technological infrastructure to increase efficiency in the supply chain. It helps in the profitable and accurate planning of sales, improvement in the risk and order management system, and brings in profits and consumer conversions at the same time. There are many supply chain management certification courses and supply chain management online training available that can help you build a profitable career in this field.

Machine Learning For The Curious: Placements made easy

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Machine Learning For The Curious: Placements made easy

You can use curiosity as a strong motivator to your advantage. We all share a fundamental human quality to varying degrees: a desire to learn more. In this course, we will explore machine learning, an exciting field that has been fundamental to the development of AI. We will introduce some key concepts such as neural networks, deep learning, and more to understand how these technologies work.

Machine Learning for The Curious

The Machine Learning course will teach you how to build a machine learning system from scratch. In this course, you’ll learn the theory behind machine learning, how it works, and practical applications of the technology in real life. You’ll also get hands-on experience with several different ML algorithms: linear regression, Naive Bayes classification, and matrix factorization (also known as PCA). 

Techniques from other disciplines cannot duplicate the capabilities and outcomes produced by machine learning methods, and if they could, they would refer as machine learning. Machine learning techniques differ from other techniques in two ways:

  • They are applications that use data to learn.
  • They are programs that produce programs to solve issues.

What Is The Difference Between AI, Deep Learning, and Machine Learning?

  • AI is a general term used to describe machines capable of exhibiting intelligent behavior.
  • Machine learning is the application of AI to create machines that can learn from data and make predictions. It is the most widely used technique in machine learning, especially in deep learning (DL) systems.
  • Deep learning is a form of machine learning and artificial intelligence (AI) that resembles how people learn specific subjects. Data science, which also includes statistics and predictive modeling, includes deep learning as a key component. 

Machine learning: A fascinating field

It is a branch of AI (artificial intelligence) that enables computers to learn from data. It’s also called statistical modeling because it uses algorithms to predict future events based on past ones. Machine learning gets used in many applications, including computer vision, natural language processing, and speech recognition.

Programs that use machine learning learn from examples, which makes it fascinating. A machine learning method can automatically analyze and understand the structure of the data you have collected to solve the problem you are trying to solve.

Discover a career in data analytics with Imarticus Learning

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With this machine learning course, students can become data analysts and receive job offers. Learn machine learning using data science that produces vital business forecasts and insights by applying your new knowledge to practical use.

Course Benefits for Students:

  • The most widely used data science tools and methodologies, as well as data analytics and the fundamentals of machine learning, will be familiar to students.
  • To receive a data analytics certification course, students must complete 25 real-world projects and case studies directed by business partners.
  • Using a data analytics tool to display data is one of the most in-demand skills in the market. Therefore, recent graduates and those starting their careers might want to think about enrolling.

 Contact us through the chat support system, or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Understand Amazon’s Supply Chain

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Understand Amazon’s Supply Chain

If you are thinking of a supply chain management career, then you must learn how experts from different industries plan and execute their supply chains. One example of supply chain management that you can refer to is the American multinational e-commerce giant Amazon which has become a household name by winning the trust of millions of its customers.

Amazon made its debut in 1994 as a book-selling website. Today, it features one of the largest and most efficient supply chain models ever seen around the globe. How did Amazon achieve this? What are the fundamentals it focused on for the management of its supply chain? Let’s find out!

Before we get into the details of Amazon’s supply chain, an aspiring supply chain professional like you needs to get the conceptual basics correct so that you can understand these real-life examples well and in their entirety. 

For this, you may wish to enrol in our IIT Supply chain management certification course which equips you with the fundamental concepts of the field that are necessary for making data-driven strategic business decisions!

All About Amazon’s Supply Chain

Amazon’s Supply Chain refers to the entire process under which a product on offer by Amazon undergoes in its life journey. This is the process that starts right from the moment a product reaches Amazon’s warehouse, enters its inventory records, and goes on till the time it gets delivered to the customer.

To offer a robust platform to its suppliers, Amazon provides them with two types of fulfillment options – 

 

  • Fulfillment By Amazon (FBA) – Under this option, Amazon is responsible for storing, packaging, as well as shipping the product to the customer.
  • Fulfillment By Merchant (FBM) – Under this fulfillment option, the responsibility of storing the products in the warehouse, packing, and shipping them to the customers rests with the Merchant.

 

How Does Amazon Supply Chain Work?

Over the last 2 decades, Amazon has made several changes to the working of its supply chain, in a bid to crack an efficient system with which it can offer the fastest delivery options like same-delivery to its customers. 

As soon as Amazon receives an order, products get arranged into pallets either manually or with forklifts into the warehouses, where they get packed and screened for quality checks. After receiving a go-ahead from clearances, Amazon’s logistics team enters the supply chain and completes the delivery of the orders.

To achieve this efficiently, the e-commerce conglomerate puts its primary focus on two elements of the chain – Storage and Delivery. Let’s uncover how Amazon takes care of these two areas.

  • Storage 

Amazon has more than 20 Crore customers globally who have subscribed to its Prime membership, which means, it needs to deliver a huge number of its orders in just 1 day or a maximum time of 2 days.

To fulfill this promise of fast delivery, Amazon maintains a huge network of fulfillment centers for storing its products. Amazon currently has 185 fulfillment centers spread across different cities of the world with a carpet area of up to 10,00,000 square feet!

This huge storage capacity helps Amazon maintain a cutting edge over its competitors and maintain a smooth fulfillment of its orders. 

Another important aspect that Amazon has taken into consideration for its warehousing is its location. Most of its fulfillment centers are located near metropolitan cities from where it received huge and regular demand.

Moreover, to speed up warehouse operations, Amazon has deployed over 10 Lakh employees in its fulfillment centers globally. It also uses robots, drones, and other high-end technologies to run its warehouse ecosystem with greater efficiency. 

  • Delivery

The second most crucial segment of Amazon’s Supply Chain is its logistics and delivery teams. Amazon ships products mainly via two channels – road and air.  Amazon maintains a huge fleet of trucks, bikes, and vans for transporting products via roads. It has also partnered with various delivery services including FedEx and UPS.

Amazon also has a cargo airline of its own called Amazon Air which is used for transporting products. Amazon Air makes more than 160 flights every day with more than 85 planes, which include 11 Boeing Jets.

This is how Amazon can meet and many times exceed its customer’s expectations in terms of fulfillment and timely delivery of their orders!

Take Away

A Supply Chain Management System is an area that can either make or break a business. If you are interested in making an impact on a business by becoming a part of its supply chain decision-making, you must get a supply chain analytics certification today!

Want to know more about the supply chain management career options? Contact us through chat support or visit our nearest training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, 

Learning Hadoop Online – Your Guide To Building A Career In Big Data

Posted on by Imarticus Learning

Learning Hadoop Online – Your Guide To Building A Career In Big Data

Big data is in demand because it has the potential to change the way we live and work. It can also help businesses solve problems faster, make better decisions, and deliver better customer experiences. 

At a projected CAGR of 13.4% over the forecast period, the global big data analytics market can increase from $271.83 billion in 2022 to $655.53 billion in 2029. With this growth also comes an increased need for professionals who understand how big data works and how organizations across all industries can use it.

What is big data?

Big data is a term used to describe the collection, storage, and analysis of large amounts of data. Data collection volume is increasing exponentially. The size of the data gets measured in terabytes. Big Data technologies have been around for years, but recently they have become viable tools for decision-making in business and government. 

Why is it in demand?

Hadoop and Bigdata are a buzzword. The term “big data” has been around for a while, but it’s only recently that businesses have used this phrase in their marketing materials and press releases. As more companies begin using big data analytics, it’s essential to understand what exactly you’re getting yourself into when you decide to go down this path of working with Hadoop—and what career opportunities exist there!

Hadoop allows users access to large datasets by processing them through various methods (e.g., MapReduce). There are many benefits associated with using Hadoop: they can get used across multiple industries, including finance, retailing, and healthcare; they allow organizations access to real-time insights into their customers’ buying habits; they provide improved operational efficiency through reduced costs on hardware infrastructure maintenance over time.

Role of the Hadoop developer.

A Hadoop developer is a person who has a strong knowledge of the Hadoop platform and can design and develop applications on it. They can be an analyst, software engineer, or data scientist.

The primary role of a Hadoop developer is to work with different tools and technologies to develop big data solutions using MapReduce functions, Pig scripts, and Hive queries. They also help manage storage requirements by using HDFS, which stores large amounts of data locally within clusters without downtime due to network issues.

Why do you need Hadoop online training and certification?

It is an open-source software framework for storing and processing big data. It has become a core technology for many companies, including Facebook, Yahoo, and Amazon. The tool has emerged as one of the most popular technologies in big data analytics over the years because it can efficiently process vast amounts of data. 

Discover a career in data analytics with Imarticus Learning

With this machine learning course, the student can learn data analytics and receive job offers. Learn machine learning using data science that produces vital business forecasts and insights by applying your new knowledge to practical use.

Course Benefits for Students:

  • The most widely used data science tools and methodologies, as well as data analytics and the fundamentals of machine learning, will be familiar to students.
  • To receive a data analytics certification course, students must complete 25 real-world projects and case studies directed by business partners. 
  • Using a data analytics tool to display data is one of the most in-demand skills in the market. Therefore, recent graduates and those starting their careers might want to think about enrolling.

 Contact us through the chat support system, or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

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