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Category: Analytics

Transitioning to Data Science: How To Get There?

Posted on by Imarticus Learning

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

Posted on by Imarticus Learning

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

online learning

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

Posted on by Imarticus Learning

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

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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.

Machine Learning A-Z: Hands-on Python and R in Data science

Posted on by Imarticus Learning

R and Python are both equally great programming languages. However, each has its own set of advantages that it offers to the user. For example, when we are talking about development processes or IT operations, Python is always a better option. But when it comes to statistical tasks or analytics, R can prove to be a much more suitable alternative.

This is because R has been created for Statisticians and for statistical projects. Skilled programmers can, however, employ any of the two languages to perform any task. For instance, Python can be used for using statistical techniques like Regression Analysis or Bayesian inference on datasets. Similarly, R can also be used for building new Data Science tools and data models. 

Python is quite easy to learn with simple syntax while R has various language boundaries. One can easily learn Python online with the help of a course. However, R is far superior in graphical and statistical procedures. R is more scientific in nature and will be much easier for statisticians or professionals who have worked with MATLAB, another scientific programming language.

Python is more focused on running algorithms and makes it easy to build programs in general. In Data Science, however, both are equally important and competent languages. R and Python can work with massive databases and are equally good at Machine Learning projects. 

R in Data Science

R is used in Data Science for graphical and statistical purposes. This language can help users create advanced visualizations and high-quality graphics as well as dynamic graphics. R is also great for data mining and statistical computing in general.

R has a set of functions that allows datasets to be loaded into the memory with program statements, but that is only required if you are going to be building R programs that will keep getting used for various functions. Otherwise, you can simply use the data import function in R Studio (IDE for R). R is able to work with data in two different formats in R studio, CSV and TXT. Once you select the dataset you wish to be working with, R will load the dataset and you can then work on it.

Python in Data Science

Python is a high-level programming level that does not require compilation before running code. This makes it very fast to use for all kinds of projects, including Data Science and Data Analytics. Python is extremely flexible and is a multi-paradigm language, thus, allowing Data Scientists to use different approaches and keep improvising the language with extensions and plugins.

Before loading a dataset in Python, you must first import pandas (library) and install them in Python. After that, a custom function must be created that loads the dataset for you. By creating a load_csv function, you can fundamentally provide an argument for your dataset’s file path.

Also, the readlines() are used in order to ensure that the program returns a list containing the lines inside the .csv dataset. You can also additionally present the data in a more visually appealing way by returning the dataset in a data frame format. This makes it easier to view the data as compared to the native list format or NumPy arrays.

Conclusion

Both the languages also are open-source and have huge communities behind them to keep providing new libraries. There are also a good number of updated tools and powerful IDEs (Integrated Development Environments) available for both R and Python.

If you wish to learn Python or R for Data Science, you should definitely opt for a solid Post Graduate Program in Data Science. You can also choose to take up a Machine Learning course with a placement or a Data Analytics course with placement as well. 

The value of an IIT supply chain management certification

Posted on by Imarticus Learning

The value of an IIT supply chain management certification

Supply Chain Analytics Certification facilitates managing the movement of goods and services. It also deals with meeting customers’ needs in a timely and economical way. The demand for Supply Chain Managers is increasing at a high rate and has surpassed other professions. This is because SCM managers are the crucial links for the operations. 

If you are looking to work in a global company that deals with logistics internationally, then the course is the correct train to your destination. This course will equip you with the knowledge of cross-border relations and other aspects of the Supply Chain.

The Supply Chain Analytics Certification at Imarticus will enhance your portfolio to secure a prospective job in the company. With an IIT certificate in Supply Chain Management, you can pursue a top career in roles such as Data scientist, Supply Planner, Supply and operations planner, and Demand Planner. With your basic understanding of operations management and programming, you can further excel in the various course segments. 

What makes IIT certification in Supply Chain Management special?

The course connects Supply Chain Management with Information technology tools such as Machine Learning, Blockchain, and Big Data Analytics. The 6 mega projects offered in the course will give a clear picture of the industry. 

We, at Imarticus, offer one-to-one mentorship with Industry experts who hail from top companies around the world. Our course will also allow you to connect with the multi-national network of professionals who work in the industry and own Logistics companies. This will offer you an opportunity to increase your network of connectivity and simultaneously gain skills from the experts. 

Why do you need Certification In Supply Chain Management?

Suppose you are a business professional who wants to upgrade your knowledge in Supply Chain Management and explore analytics. In that case, it is right to seek more as this course offers case studies that you can perhaps relate to your job. 

On the other hand, if you are a student who has a keen eye for creating sustainable supply chain solutions through data analytics, then this course would sharpen your skills. The course would enhance your potential and give you both theoretical and practical knowledge. 

Supply Chain Analytics Course Training will help you learn and experience the analytics role and the dynamics of SCM analytics. You will learn to work with SCM data and get practical exposure to analytics techniques and tools. On completion, you’ll have theoretical and practical skills to efficiently conduct analytics and optimisation to meet your organization’s SCM needs.

What kind of concepts would be covered in the course?

The course will help you understand the key role of analytics in Supply Chain Management and the current dynamics related to the industry. The course would give you a brief insight into Cognitive analytics, prescriptive analytics, predictive analytics, and Descriptive analytics.  

  • The Bullwhip-effect
  • Risk-pooling
  • Supply Chain Design 
  • Just-in-time Planning and Control
  • Supply Chain coordination 
  • Project management techniques
  • Real-time route optimization

If you have the right set of tools in the SCM and think that there is a lot to explore, then you simply have to visit here.

If you want to learn data science and machine learning, look no further

Posted on by Imarticus Learning

If you want to learn data science and machine learning, look no further

We all must be familiar with the terms data science and machine learning. These are the emerging technologies that are in high demand these days. They are the present and the future in a technologically-driven world, which is why most people opt for a career in these fields. If you’re a fresh graduate or someone who wants to elevate his career or is interested in starting a career in analytics, you have reached the right place. This article will discuss the reasons to go for a career in data science, different job roles, and the best data science course available.

Simply put, machine learning is the science of getting computers to learn and act like humans by feeding them information from the real world. Coming data science is the science that is used to process a huge volume of data using different tools, algorithms, and methods to discover hidden patterns in the raw data. These advanced technologies are not restricted to a specific area but are applicable in various fields, such as transportation, healthcare, finance, sales, and many more.

Why go for a data science and machine learning course?

  • High demand

The data science sector is highly employable and the fastest growing job market globally. It is predicted that data science will create 11.5 million jobs by 2026. The demand for data scientists is high in various industries, making it a versatile career option.

  • Eliminates boring tasks

The primary benefit of data science is the ease it has brought to operations by automating manual, cumbersome, and redundant tasks. Many industries benefit from these advanced technologies as they use historical data to train machines to perform repetitive functions in much less time.

  • Highly remunerative career

A certified data science and machine learning course paves the way for one of the most highly paid jobs. Glassdoor revealed that data scientists earn an average of $116,100 annually. Moreover, the abundance of opportunities available for people in various sectors makes it an appealing prospect.

  • Highly prestigious job

Businesses highly value data scientists as they help make smarter, data-driven decisions. They hold an essential say in companies as even the higher management relies on their expertise on some issues. They are highly reputed since they make more intelligent products, improving overall user experience.

  • Career growth

If you’re feeling stagnant in your job, a professional certification from a data science course can help grow your career exponentially. It will make you stand out among your competition and strengthen your profile. A study by Business Wire stated that a certified data science course led to a salary increase of 20% to 40%.

Job roles in data science and machine learning

A certified course in data science and machine learning is well-regarded and opens up plenty of opportunities for you in the form of the following job roles:

  • Data scientist
  • Data Analyst
  • Business Intelligence Analyst
  • Data Engineer
  • Data Architect
  • Machine learning Engineer
  • Project Manager
  • Data Statistician

Anyone interested in data science and machine learning can enter the job market as a data scientist at any career stage. A background in Mathematics and statistics would be of great help. However, you can aspire to become a data scientist irrespective of your academic background and even if you’ve never written a code, with the help of your sheer commitment and proper guidance.

Imarticus Learning offers an excellent Certificate Program in Data Science and Machine learning for working professionals and anyone looking to kickstart his career. This certified course is built in collaboration with iHUB DivyaSampark, a technology innovation hub at IIT Roorkee.

This comprehensive program is easy to understand and prepared by the acclaimed IIT faculty and industry experts for early and mid-level professionals. Thus, it focuses on building a strong data science foundation and specializes in machine learning with Python for data-driven decision-making.

Some of the important features of this data science program are as follows:

  • Live online training will be imparted by renowned faculty of India from IIT Roorkee, IIT Guwahati, IIT Ropar, and industry experts.
  • A 5-month program designed to equip you with the proper knowledge to implement and apply data science concepts to real-world problems.
  • Opportunity to participate in 2-day campus immersion at iHUB DivyaSampark at IIT Roorkee.
  • Startup mentorship and funding support under the program.
  • Program coordinated by Dr. Balasubramanian Raman, the top data science and ML academician.
  • Certified collectively by IIT Roorkee and Imarticus Learning under the National Mission on Interdisciplinary Cyber-Physical Systems.

Check out the program in detail on our website. You can even connect to us through chat support or meet us in person at any of our nearby training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

How To Use Tableau To Improve Your Data Analysis Skills

Posted on by Imarticus Learning

How To Use Tableau To Improve Your Data Analysis Skills

Tableau is a data analysis tool that lets you create, analyze and share interactive dashboards. Thousands of organizations worldwide use it to visualize their data in a way that helps them make intelligent decisions. Tableau professionals use Tableau Desktop to build and manipulate charts and tables with point-and-click ease. 

An overview of Tableau

Tableau is an interactive, self-service reporting and analytics tool. Faculty and staff can access Tableau in a single Creator environment using Tableau Creator or through a shared dashboard.  It’s easy to use, but it’s also powerful enough for more advanced users.

Tableau helps you analyze your data by allowing you to connect all the elements of your business in one place so that everything from customer interactions to sales processes gets organized in one place.

 You can then use this information as part of reporting or decision-making processes at any level, from local to global organizations. You can use Tableau to create dashboards and visual representations of your data that help you understand its essential elements. 

How to create visualizations in Tableau?

A tableau is visualization software that allows you to create interactive and beautiful data visualizations. Tableau is an industry-leading cloud-based data analysis tool. It allows users to create complex charts, maps, and dashboards in minutes using their desktop or web browser. Users can also collaborate with other teams via webhooks so that everyone can view the same file simultaneously. 

Making Visuals in Tableau

Let’s start with actual Tableau data visualization.

  • Boolean: This type of data stores true and false.
  • Date/Datetime: This data type can facilitate Tableau’s built-in date hierarchy when used with legitimate date or DateTime fields.
  • Numbers: These values are numerical in nature. Values may be either floating-point numbers or integers (numbers with decimals).
  • String: A string is a group of letters or numbers enclosed in single or double quotation marks.
  • Geolocation: To plot maps, we need these values.

Tableau: A Better Way To Manage Business Data

Tableau is one of the best business intelligence (BI) tools for visualizing and analyzing data. It helps you make better decisions faster.

Tableau is great for:

  • Analyzing your data in Excel or another reporting tool
  • Reporting on websites and dashboards
  • Creating high-quality presentations and reports
  • Using Tableau to improve your data analysis skills will help you become a more valuable employee.

A tableau is a powerful tool; many features can help you become more efficient. 

Explore a career in data science with Imarticus Learning

 

online learning

With this Tableau online training, you can learn Tableau and receive a job offer. Create complex models and learn data analytics skills that produce vital business forecasts and insights by putting 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 chat support, or drive to one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.