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Category: Analytics

Natural Language Processing: A Breakthrough Technology In AI

Posted on by Imarticus Learning

Natural Language Processing: A Breakthrough Technology In AI

Natural language processing (NLP) is a branch of artificial intelligence that deals with computers understanding and analyzing human speech. NLP is used in data science training and analytics for document classification, sentiment analysis, and social media monitoring. NPL is a crucial module that is important for learning data science.

Using NLP algorithms, computers can be trained to process and parse text to extract meaning. This understanding allows computers to interact with humans more naturally by responding to questions and commands like humans do—using natural language.

The importance of NLP in data analytics comes from the fact that most data is not structured or organized in a way that machines can easily read. For example, suppose you wanted to know how many people were born in Seattle between 1980 and 1989. In that case, you could find this information by searching through every record individually or by using an algorithm to organize all those records into individual years and then count them. In both cases, you would need some program or algorithm with instructions on how the machine should conduct it.

Here is where NLP comes into play: instead of humans writing codes for every situation (which would require them to think about every possible scenario), they can use NLP methods. Machine learning algorithms are capable of learning from their own mistakes.

Natural language processing is essential because it allows machines to interact with humans in a way that feels natural. For example, you can ask Siri questions and receive answers in plain English—rather than dealing with complex programming languages or commands.

Natural language processing is one of the most exciting areas of AI research today. NLP is the ability of computers to understand and process human language. It plays a massive role in the development of AI.

NLP is used extensively in voice assistants like Amazon’s Alexa, Apple’s Siri, and Google Assistant. These assistants can understand what you say and respond accordingly, which is incredible. Intense work goes into making machine/AI assistants sound natural when they respond. 

They have to be able to answer questions about schedules or alerts about upcoming events’ reminders; they have to know what kind of information is shareable with whom, and they have to know how to respond when confronted with something inappropriate or off-topic. All this requires extensive training with humans willing and able to provide feedback on how well the assistant understands what was said and what needs improvement before it can go live on the market.

This technology can be used for several things, including:

  • Helping people who don’t speak English understand the meaning behind words spoken—understanding what people are saying so that you can respond appropriately.
  • Understand human speech patterns, allowing us to communicate with machines more naturally.
  • Create more intelligent chatbots and virtual assistants that can respond as humans would.
  • Helping people find information on the internet if they aren’t sure how to phrase their search query.
  • Help machines understand the written text better than ever before, which will help them make better decisions related to translation services or robotic surgery procedures (for example).

The two methods of NLP

Syntactic analysis and semantic analysis are two methods of text analysis. The syntactic analysis breaks down a sentence into its parts and determines how those parts are arranged in relation to each other. The syntactic structure can also determine the type of sentence — whether an imperative, declarative, or interrogative statement, for example. Semantic analysis is the process that determines the meaning of a word or phrase by analyzing its relationship to other words and phrases in context. This might mean looking at the relationship between individual words or groups of words. 

A good example would be:

“The dog ran away”.

Using syntactic analysis, we can see that this phrase has three parts: “the”, “dog”, and “away”. Each word contributes something different to the overall meaning of the sentence—so we can see that each part must be considered when trying to understand what it means. However, with semantic analysis, we would look more closely at each word individually.

Imarticus learning offers a deep-dive post-graduate course that takes you through the basics of NLP and other vital subjects required to learn data science, spread across six months of an integrated course for a successful data scientist career. Book a call with us today or walk into our offline centers to know more about the course and its benefits.

Building a data science career with IIT Roorkee: Top online courses in 2022

Posted on by Imarticus Learning

Building a data science career with IIT Roorkee: Top online courses in 2022

In recent years, data science has become one of the most popular and lucrative career choices. With the increasing importance of big data, companies are looking for employees with the skills to analyze and make sense of large data sets. IIT Roorkee is a great place to start if you’re interested in a career in data science.

This blog will discuss some of the best online courses for aspiring data scientists. We’ll also examine what skills you need to succeed in this field. So if you’re ready to start your journey toward a career in data science, keep reading!

Data Science: An overview

It is the process of extracting knowledge and insights from data. It uses statistics, machine learning, and computer science techniques to analyze data. Data scientists use these tools to solve problems in business, healthcare, and education.

There is a growing demand for data scientists across all industries. This is because businesses are increasingly relying on data to make decisions. Data science can help companies to automate processes, improve customer service, and make better decisions.

Skills You Need To Be A Data Scientist

If you’re interested in becoming a data scientist, there are a few skills you need to have.

  • Technical skills: As a data scientist, you must be proficient in statistical analysis and computer programming. 
  • Data Analysis & Visualization: Data scientists need to be able to clean, organize, and analyze data. They also need to be able to communicate their findings clearly through visualizations such as charts and graphs. 
  • Problem-solving skills: Data scientists solve complex problems. You will need to have strong analytical and problem-solving skills to do this. 
  • ML with AI & DL with NLP: To implement tools and techniques in various logic, decision trees, etc., one needs to have a thorough understanding of machine learning and artificial intelligence. Any data scientist with these skill sets can work on and resolve complex problems specifically created for predictions or for choosing future objectives. These skills will undoubtedly make those who possess them stand out as knowledgeable professionals. 
  • Big Data: Hadoop, MapReduce, HDFS, Spark, and Flink are some technologies used to work with big data. A data scientist should be well-versed in at least one of these technologies to handle big data sets effectively.

Learn Data Science and machine learning with Imarticus Learning.

Students can start their data science careers with this certificate program in data science and machine learning. Students will learn the fundamentals of artificial intelligence, data science, and machine learning through this curriculum and the skills required to apply these concepts in the real world.

 Course Benefits For Learners:

  • This five-month course, developed by IIT faculty members to aid students in understanding data mining and machine learning methodologies, introduces students to Python.
  • India’s best teachers will deliver this data science course live online.
  • Students can lay a solid data science foundation with the aid of our online program.

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

Certification Every Supply Chain And Logistics Management Professional Needs!

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Certification Every Supply Chain And Logistics Management Professional Needs!

Supply Chain Management is an overlooked field but integral to every successful business. Why should you get certified in Supply Chain Management? Because it’ll make your career more valuable and allow you to collaborate with other professionals in the area. 

It will also help you understand how business operations work together on a larger scale so that you can be an effective leader who inspires others and helps them succeed. This post will discuss how to become a successful supply chain analyst.

What is Supply Chain Management?

Supply chain management is a process of planning, implementing, and controlling the flow of goods from the point of origin to the point of consumption. It is also known as supply chain management (SCM).

Supply chain management can be described as a critical component in business strategy because it provides an effective means for companies to manage their businesses effectively while meeting customer needs.

Businesses rely on their suppliers when they need products or services at competitive prices. This relationship between buyer and seller enables both parties to achieve mutual goals such as cost reduction, product quality improvement, and innovation.

Why is SCM important in today’s business environment?

  • SCM helps create and manage the supply chain for any company, large or small.
  • The role of SCM in the supply chain is to ensure that materials are delivered on time, safely, and efficiently from the source through distribution centers to end customer locations. 
  • This process can get broken down into three main components: 
  • Procurement (buying) 
  • Production/Manufacturing (making/producing) 
  • Shipping/Transportation (moving goods).
  • The role of logistics management is responsible for coordinating these activities so they occur at an optimal level with minimal disruptions along the way – meaning there are no bottlenecks in production lines due to insufficient quantities available at one point during processing; no late deliveries causing customers’ orders not being delivered on time.

Why should you be certified in Supply Chain Management?

  • It’s a great way to stand out from the crowd.
  • You’ll show that you are committed to your career.
  • Certification will help you get a job, a promotion, and earn more money!

mBA online courses

With various supply chain management online training available, picking a course based on your current position and future career goals is critical. Verifying your eligibility for the programs you’re interested in is part of the selection process.

After enrolling in the course of study and incorporating on-the-job training, the only thing left is passing the certification exam. You can include a certification on your resume once you’ve obtained it. 

As we’ve discussed, SCM is a crucial element of today’s global supply chain operations, but it’s not just about managing inventory or logistics. It’s also about creating efficient processes that help companies achieve their goals in the most cost-effective way possible.

Explore a Career in supply chain management with Imarticus Learning

Choosing the best certification in Supply Chain And Logistics Management Professional course will help managers make tactical, operational, and strategic decisions.

Course Benefits For Learners:

  • Prepare yourself to contribute to the future creation of more tactical and innovative global supply chains by integrating traditional supply chain online courses with data-driven decision-making. 
  • After completing the IIT supply chain analyst course, students can start preparing for in-demand careers as demand planners or data scientists!
  • Python teaches students to be data-centric, which will help them make better supply chain decisions.

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

How I learned computer vision quickly in 2022

Posted on by Imarticus Learning

How I learned computer vision quickly in 2022

In 2022, computer vision comes under one of the most sought skills in the industry. It is a field of AI that deals with how computers can interpret and understand digital images. As a result, many businesses are now turning to computer vision to solve various tasks such as product identification, and image recognition.

Learning computer vision is no easy task. It can take extensive practice to become an expert in the field. However, with the right tools, you can learn it quickly! In this post, I am sharing with you my personal experience of how I learned computer vision quickly in 2022.

How I learned computer vision quickly?

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I started by enrolling in a course on AI and machine learning. This course was crucial in helping me understand the basics of computer vision. It also gave me a strong foundation to help build my further knowledge. In addition to the course, I also used online resources such as tutorials and articles. These were extremely helpful in consolidating my understanding of the concepts. I recommend using these resources if you want to learn computer vision quickly.

And last but not least, I practiced A LOT! I spent hours upon hours trying out different computer vision algorithms and implementations. This allowed me to gain a deep understanding of how computer vision works. It also helped me develop my own intuition for solving problems.

What skills do you need to be successful in computer vision?

To be successful in computer vision, you will need certain skills. Here are some of the skills you need to learn:

  • Image processing: This involves understanding how to process digital images. You must know how to convert images into digital formats and how to manipulate them. 
  • Feature extraction: This is a process of identifying important characteristics in an image. These characteristics can be used to identify objects or people in the image. 
  • Pattern recognition: This is the ability to identify patterns in images. This skill is important for tasks such as object recognition and facial recognition. 
  • Deep learning: This is a type of machine learning that is becoming increasingly popular in computer vision. Deep learning allows computers to learn by example. This means that you can train a computer to recognize objects by showing it examples of images with those objects. 
  • Programming: You will need to be able to write code in order to implement computer vision algorithms. Python is a popular language for computer vision, but other languages, such as C++ and Java, are also commonly used.

That’s set. These are some of the skills you need to learn in order to become proficient in computer vision. If you want to learn computer vision quickly, I suggest that you focus on mastering these skills.

Discover the Deep Learning certification course with Imarticus Learning.

Imarticus Learning’s course on AI and machine learning is the perfect course to start your journey. The course covers all the important concepts and skills you need to know. It also provides hands-on projects to help you apply your knowledge.

 Course Benefits For Learners:

  • Students tackle 25 real-world projects—preparing them for rewarding careers in the data science field.
  • By earning a certificate from the E & ICT Academy, based at IIT Guwahati, and supported by Imarticus Learning, students can demonstrate their skills to employers.
  • Students who complete this IIT AIML course are well-qualified for jobs in the machine learning and artificial intelligence sectors.

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

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INTRODUCING CERTIFICATION IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN COLLABORATION WITH E & ICT ACADEMY, IIT GUHAWATI AND IMARTICUS LEARNING

Even a beginner can learn python online: Here’s how

Posted on by Imarticus Learning

Even a beginner can learn python online: Here’s how

When you’re just starting out in the world of coding, the syntax of other languages might be incredibly intimidating. Python, on the other hand, with its simple setup and readability, encourages you to think like a programmer and saves you time in constructing a large syntactic format. Amazing as it is, typing and compiling code in this language is like a breeze because of its straightforward syntax. If you want to learn python online, you must know that it has never been easier than now.

How should you start to learn Python?

Learn the Syntax

Identifiers and Keywords in Python

  • Identifiers: Classes, functions, variables and other programmatic constructs are all given unique names, known as identifiers. It is useful for setting apart distinct things in the world. The names of Python objects such as variables, functions, classes and modules are called identifiers. Any character from a to z, or the underscore (_), may serve as the first character of an identifier, which may then be followed by a combination of letters, numerals, and/or additional underscores (0 to 9). Names in Python cannot include any punctuation, including @, $, or %.
  • Keywords: Python’s equivalent of words that are reserved are called ‘keywords’. In other words, we can’t use a keyword in any way that would make it an identifier (such as a variable or function name). They serve as the foundation for the Python language’s grammar and organisation. Python is case-sensitive when it comes to using keywords. In Python 3.7, you’ll find a total of 33 different keywords. This figure is subject to minor changes over time.

Indentations in Python

The spaces at the start of a line of code are called indentation. Python places an emphasis on proper indentation, which is mostly superficial in other languages. Python code blocks are denoted by indentation. Hence there is no need to use ‘{’ and ‘}’ to define blocks of code.

Python Data Types

  • Numerical data types: Python can handle simple numbers, complex numbers and floating-point numbers. int, float and complex are the Python classes that define them.
  • Sequence data types: With Python, lists are one of the most flexible ways to interact with several data items simultaneously.

Python’s tuple data structure may be thought of as a list. While we may modify list items after they have been assigned, tuple elements cannot be modified after the assignment.

  • String data type: In computing, a string refers to a sequence of characters. A Python string is a set of Unicode characters. Unicode was created so that every character from every language may be encoded consistently and reliably.
  • Mapping data type: In Python 3.7 and beyond, a dictionary is an organised list of elements. A dictionary stores information as a key/value pair for each entry. This is because dictionaries are designed to provide results after the key has been determined.

Flow Control in Python

In programming languages, decision-making statements determine the course of programme execution. The ‘if’, ‘elif’ and ‘else’ statements are used to make decisions in Python.

Loops in Python

In certain cases, you may want to run the same piece of code several times. Languages’ varied control structures enable more complex execution routes. Python ‘while’ and ‘for’ loops make it easy to manage looping situations.

Functions in Python

A function is a collection of connected instructions that may be used again and again to accomplish a certain task. Your programme will benefit from the increased modularity and increased code reuse made possible by functions. It is common knowledge that in addition to Python’s numerous predefined functions like print(), you may also write your own. User-defined functions are the common term for such functions.

Create Projects

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Python is not always easy to learn. Reading a book might help you understand the material, but putting it into practice can be difficult. Worse, you might spend a lot of time studying syntax just to get bored or lose interest. Making Python projects improves your odds of success. That way, you are able to put your skills to the test in a realistic setting.

Conclusion

Getting started with Python is simple, and after you’ve mastered the language, you’ll be well-positioned to pursue a rewarding career in the expanding field of data science and analytics. Better still, you’ll be in high demand as a professional since new uses for AI mean a higher need for Python programmers. 

If you are a person who is intrigued by the domain of data science and data analytics, you should definitely consider the best data analytics certification course brought to you by Imarticus. The Post Graduate Program in Data Analytics & Machine Learning is an extremely comprehensive course to learn data analytics. So enrol right now and do not miss this opportunity to be an asset to the corporate.

IIT Roorkee’s machine learning certification is a top data science course

Posted on by Imarticus Learning

IIT Roorkee’s machine learning certification is a top data science course

While selecting a career for your future, it is a must to enquire about it before proceeding any further. The research will show you the statistics related to it. From there you can understand the present scenario of that particular field and its growth projections. 

To make your research work easy, we have already found one of the best career options for you. It will be an ideal choice for an individual to pursue a career in data science, especially looking at its future growth. According to the Bureau of Labor Statistics, a career in data science is projected to grow 22% between 2020 and 2030. Thus, data science becomes a good career option for you to accomplish your life goals. 

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After you get clarity about moving forward in data science or acquiring some essential industry expertise in machine learning, then the next step is to choose an appropriate course. For that too, we have your back, as we have already found an IIT data science certification course, a perfectly designed course to transform you into a desired professional. 

This 5-month data science online training program has the ability to build a robust foundation for you in the field of data science and machine learning. Now, let us know what all you will get to learn through this IIT data science certification course;

Languages and Tools Covered

In the course of this program, you will be taught everything related to data science and machine learning. Most importantly, proper knowledge of some programming languages and tools is essential in this field. So, here are some of those languages and tools, which will be covered during your data science online training.

  • Python
  • SQL
  • NLTK
  • Pandas
  • NumPy
  • Tableau
  • Matplotlib
  • Scikit-Learn

Career Benefits

One must look for the benefits of a course they are going to pursue in order to compare it with others and to understand what they are getting in return. So, here are some add-ons on the IIT data science certification course that you must be aware of.

  • Resume Building- After completing this data science online training, you will be rewarded with a certificate. It will be issued by y iHUB DivyaSampark @ IIT Roorkee, Department of Science & Technology (DST) and Imarticus Learning. Therefore, you can add this certification by nationally recognised bodies to your resume to enhance it and stand out from the rest. 
  • Career Monitoring- During the program, you will get mentorship from industry experts and members of the IIT faculty. They will also help you in shaping your career in the right direction. 
  • Mock Interviews- This course is not just about understanding the working system of data science, but it is a lot more than that. Here you will also be mentored for mock interviews that come next in your journey. You will be shaped into a professional, no one can reject. 
  • Peer Meet- This data science online training does not take your chance of meeting your peers from it. On the contrary, it offers a 2-day campus immersion where you get the chance to communicate with the faculty from IIT and other learners. 
  • Startup Funding Programs- The list of benefits does not end here. This IIT data science certification course also helps learners pitch their startup ideas and get investments or support. This course supports your dreams and empowers you in pursuing them. 

Hands-on Real-World Projects 

Practical knowledge is as necessary as having a theoretical understanding. That’s why this course is a perfect fit for you. Here you get an opportunity to work on real-world projects, and case studies that will teach you technical skills in data science and machine learning fields. 

  • Property Price Prediction
  • Forecasting Sales of Furniture Products
  • Heart Disease Prediction
  • Vaccine Usage Prediction
  • Taxi Fare Prediction
  • E-commerce Customer Segmentation

Conclusion

According to the U.S Bureau of Labor Statistics, there are about 13,500 job openings for data scientists each year. That means, there are quite a good number of opportunities available, and one just needs the correct set of skills to get those job positions. Therefore, choosing an appropriate course is not only an essential part but also the first stage of your career foundation. A lot of your future depends on the study program you choose. So, always be aware of the course you are getting into. 

Here, in this IIT data science certification course, the experts aim to develop you into a professional that has data mining insights and the ability to help businesses make the right decisions for growth. At the end of this course, you will have solid skills in machine learning with Python and data science.

For more information about this data science online training, you can contact us right away. Your future awaits you to make the correct decision. 

What you’ve not considered before: Learn python online

Posted on by Imarticus Learning

What you’ve not considered before: Learn python online

The world is evolving every day and we are moving towards a tech-savvy world, where almost everything is digital. Even nowadays, numerous software and programming languages are used to conduct various tasks. Among them, one of the popular choices of programming language is python. This language is widely accepted and practiced to carry out important works like data analysis.

Data analytics and the python language share a relationship that is interesting to know. Below is some information that will expand your knowledge of python and its relation to data analytics. 

What is Python?

To briefly explain, python is a programming language used for various purposes like web development, system scripting, software development, and even in mathematics. There are multiple applications of this programming language as well. Starting from rapid prototyping for software development to connect database systems, it is also used on servers to create web applications. Python can be used just as a scripting language or can be compiled to byte code for building gigantic applications. 

One of its interesting uses lies in mathematics where the python language can handle big data and solve complex mathematical problems. 

When it comes to applying python, the different platforms available are Windows, Linux, Mac, Pi, Raspberry, and many more. 

With every passing day, the use and popularity of python are increasing and becoming a huge part of our future. Thus, it will be a good call to learn python online and gain the skill that is in demand.

Facts about Python

Here are some other facts that make python distinct from others and an easy language to learn and apply; 

  • Python has a similar structure to that of the English language which makes it easier for an individual to learn it. 
  • This structure also helps programmers to write programs in fewer lines compared to any other programming languages. 
  • Interestingly, python runs on an interpreter system that allows the coder to run all his/her codes as soon as written. This signifies that prototyping can be really quick using python language. 
  • We can easily integrate the python language with C, C++, CORBA, JAVA, and ActiveX. 
  • To understand in simplest terms, a sizable collection of libraries in python is completely dedicated and appropriately used for valuable analytics and to solve complex calculations. 

Why should you learn Python Online?

We already know about the popularity of python and its universal appeal. This is one reason to learn python online from the best platform to gain good command over a language that applies from data science to app development. 

Even if you compare python with any other programming language, it is one of the most versatile, making it the popular choice of people.

Among the various reasons behind learning python, one evident reason is its simpler approach. Comparatively, it has a simpler syntax and high-readability factor, making it beginner friendly. Another quality of this language is its flexibility across other programming languages. For example, you can integrate it with JAVA and .Net, and perform cross-language operations as well. 

There is no other language that can compete with python when it comes to the numerous useful libraries. The python language comes with an assortment of libraries like NumPy, Matplotlib, StatsModels, Pandas, and many more. Because of the availability of this vast collection of libraries, python has more uses and its functions have multiplied significantly over the years. 

Adding to the extensive list of qualities of python, its application in the field of data science is commendable. There is a huge role of the python language in data analytics as it is easy to learn and understand. 

Python and Data Analytics

Till now, we know little about the application of python in complex mathematics. This function of python language enables it to be a useful resource in data analytics. All the above-mentioned qualities of python make it the best choice for data analytics. Apart from those features, it is also well-known for its graphics and visualisation. As it is quite easy to comprehend visual information, python becomes the preferred language because of its plethora of different visualisation options. 

Besides this, there are multiple built-in analytics tools in python to process complex data. These tools can penetrate patterns, provide insightful information, as well as correlate those in extensive sets. 

To summarize this relationship, we can say that the language’s ability to analyse huge data sets in no time and carry out repetitive tasks makes it the right choice for data analytics. Thus, it is worth it to learn from a data analytics course with placement that can provide you with knowledge and experience, all at the same time.

Conclusion

It is widely known that data analytics is a huge field of operation that deals with complex data to derive valuable information from it. And to work out these enormous tasks, python is internationally recognized. It assists in managing data with its versatile nature, and multi-features.

So, to be an asset for a company in the future, it is an excellent choice to learn data analytics which includes python as well. When you learn data analytics, you will understand how valuable it is in this field. 

Lastly, to learn data analytics it is advisable to opt for a postgraduate program in data analytics & machine learning to gain the appropriate knowledge of analysis combined with the skills of python. 

Can you learn analytics and supply chain management together?

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Can you learn analytics and supply chain management together?

Customer demand is fulfilled by a series of interlinked and interdependent processes, which is cumulatively known as the supply chain. These activities are associated with the flow of information, fund and product or services, as the case may be. The stakeholders who are instrumental in the path of the supply chain are vendors, manufacturers, distributors, retailers and customers. The sole process of supply chain management aims towards customer satisfaction and retention, besides maximising the bottom line of all the stakeholders of the chain. Various Supply Chain Management Online Training Programs are also available in various institutes.

Subjects to be learnt 

There are several premier institutes in India that teach the subject of supply chain management as a PG course. However, a prospective candidate may also complete a Supply Chain Management Certification course after graduation to pursue a professional career. The basic subjects to be learnt in order to handle these activities are marketing management, finance, organisational behaviour, economics, mathematics, statistics, brand promotion, corporate communication, etc. whereas the elective subjects may include warehousing management, logistics, international trade, export import business activities, etc. Technically there is no bar to which type of graduates may attempt their career in the PG courses in Supply Chain Management courses. However, it may be noted that a commerce background will certainly be advantageous.

Overview of Data Analytics 

Today the usage of the internet has increased multifold times. With the easy accessibility of smartphones across the country, India alone has an active internet user base of 70 crores. Online social platforms like Facebook, communicators like Messenger, Instagram, Twitter and WhatsApp or professional platforms like LinkedIn generate huge databases on a daily basis. These data capture user behaviour and areas of interest. Similarly, a large amount of data can be also retrieved from client organisations, too. These are the fields that are captured to understand the needs of customers. Similarly, organisations also have records of their own data for predictive or prescriptive analysis in the future. Thus the work of data analytics starts with the process of identifying and then follows the sequence of collecting, cleaning, analysing, interpreting and visualising data. The sole purpose of data analytics is to make a meaningful prediction for a Business House in different functional fields to achieve and surpass the targeted bottom line of the organisation. To achieve this goal, an analysis of risks in business and operations is performed with due diligence.   

Topics to be learnt 

There are a good number of reputed institutes that teach the subject as a PG course. However, a prospective candidate may also learn the subject as a certificate course for three or six months. Data analytics online courses are also available in India. Like the supply chain management course, there is no bar for students of any field. However, it may be noted that mathematics and statistics are the first subjects, which a candidate will be expected to know.

In order to pursue a career as a data analyst (at the beginning stage) or a data scientist / consultant (at a mature or experienced stage), the institutes teach the following topics/skill sets –

  • Advanced Excel Topics (such as Functions, VLOOKUP, Macros & VBA, Charts and Pivot Table)
  • SQL or Structured Query Language (Aggregate Function, Joins, Views, Query Optimisations, Triggers and Transactions)
  • Programming Language – 1) Python, 2) R and 3) SAS or Statistical Analytical System
  •  Artificial Intelligence
  •  Machine Learning
  •  Visualisation Tools – 1) Tableau and 2) Power BI
  •  Soft Skills like communication, time management, problem-solving and analytics skills

A common pertinent question that hovers around the minds of prospective candidates is whether they can learn Analytics and Supply Chain Management together. The simple answer in one word is “yes”. However, one needs to be focused on his / her professional field. If the candidate is interested in working in the Supply Chain Management domain of an organisation, learning Data Analytics will certainly be an added advantage for him/her in understanding the solutions provided by predictive or prescriptive analysis. On the other hand, if a candidate is focused on becoming a Data Scientist, then he/she must concentrate on the core subject first. Nevertheless, he/she may also study supply chain management to understand the functional elements in a better way to equip him/her with more practical/real-time field-based knowledge.

Conclusion

In this context, it may be noted that both the courses are available offline, as a PG course and also online, as a certificate course. Depending on the individual focus, the candidate may choose a combination of online and offline courses for the two courses simultaneously or even may opt for online certification courses for both topics, depending on priorities.  The IIT Supply Chain Management Course at Imarticus which provides live online training will help you to reach your goal. Both fields have excellent career growth potentials, particularly for candidates having innovation in thoughts, analytic skills and excellence in communication. There is no second thought that candidates with a combined knowledge of both subjects shall definitely excel in their career growth and would be rated as the most valuable employees by their organisations.  

The anatomy of a data analytics course with placement

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Data Analytics deals with the analysis of raw data for coming to conclusions about data that an organisation has acquired or for identifying various trends and patterns. A data analytics course with placement will help you to learn and understand the anatomy of Data Analytics and how it can benefit your career so that you can get good placements. The Data Analytics techniques and methods work on certain algorithms that deal with raw data with Artificial Intelligence. The involvement of machine learning is also of prime importance.

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Read along to get a brief idea of why you should take the Data Analyst certification course and how it can benefit you to boost your career.

What is Data Analytics?

Data Analytics is the process of collective transformation and organisation of raw data so that a data analyst can conclude out of it to get the desired results. It also helps the organisation to have a better decision-making process and make predictions for future operations. In today’s time, a career in data science is a flourishing one and if you want to become a data scientist or data analyst, then you need to understand what are the benefits of learning Data Analytics.

A Data Analytics course with placement can help you gain the following advantages:

  • Data Analytics helps to deliver business needs in a proactive and anticipating manner.
  • Data analysts help to mitigate the risk factor in an organisation.
  • As the data is properly understood and analysed, the results that are derived from it are always more accurate.
  • All the financial, physical and intellectual assets of the company with the help of good security measures.
  • Data analysts help an organisation make good investments and have productive results.
  • With the help of data analysis, a company is more responsive and personalised in its services.
  • Data Analytics improves and optimises the customer experience so that companions do not lose any customers.

Anatomy of Data Analytics

The factual information that you collect from multiple sources in the form of a physical or digital format is known as data. The anatomy of Data Analytics can be understood when you know about the division and classification of data. Data can be classified as follows:

Qualitative data

The non-numeric data which is all about properties and characteristics is known as qualitative data. It is generally collected by labelling, observing, listening or watching an object. Project management uses a lot of qualitative data. Qualitative data can be generated as follows:

  • By conducting interviews.
  • By translation of symbols.
  • By image processing.
  • By making observational notes.
  • By listening to multiple audios.
  • By watching video recordings.
  • By looking at documents and notes.

Quantitative data 

The numeric data that is statistical, conclusive, countable and measurable in nature is called qualitative data. it provides a clear picture of the aspects of numerics. Quantitative data can be in the following forms:

  • Metrics
  • Market research
  • Tests and experiments
  • Surveys

Structured data

Structured data is the type of data that is present in an organised and standardised format that is easily readable and searchable. Structured data is much easier to work with and this type of data is more concise and accurate. Some examples of structured data are as follows:

  • Dates and names
  • Data related to product user
  • ERP system data
  • Bank account numbers and statements
  • Identification numbers

Unstructured data

Unstructured data is not available in an organised and standardised format. It cannot be easily searchable or readable and it is difficult to understand. This type of data is generally present in long formats. Some examples of unstructured data are as follows:

  • SMS
  • Emails
  • Audio and video files
  • Social media posts
  • Text exchange on social media

Responsibilities of a Data Analyst

to understand the anatomy and working model of Data Analytics and to have a career in data science, you must know what are the rules and responsibilities that a data analyst has to perform. A data analyst certification course may help you learn these. the roles and responsibilities of a data analyst are enumerated as follows:

  • Ascertain organisational objectives by working closely with the data scientists and IT management teams.
  • Use standardised statistical tools and techniques to analyse the result.
  • Extract data from multiple sources, mainly primary and secondary ones.
  • Constantly thrive for process improvement and identify different means to do it.
  • Identify designs, patterns, trends and correlations in different data sets.
  • Create and design RDBMS and data systems.
  • prepare data reports and visual representations so that they can be presented to higher management.
  • Solve data-related issues and code problems.

Conclusion

Data Analytics Course With Placement

To become a Data Analyst, enrol yourself on a Data Analytics course with placement so that you can kickstart your career in the said field. Learn the Data Analytics course by Imarticus so that you will be able to make data-driven decisions. Proficiency in Data Analytics will help you to reach milestones in your career. 

Artificial intelligence and machine learning: Top courses, skills, salaries and careers

Posted on by Imarticus Learning

In 2022, the scope of Artificial intelligence (AI) and machine learning will continue to grow as more businesses adopt these technologies.

AI/ML is already used in many industries, such as healthcare, finance, manufacturing, and retail. As these technologies become more advanced, they will likely be used in more industries.

For example, AI could help plan city infrastructure or optimize traffic patterns. The demand for AI/ML skills will continue to grow in 2022. As businesses adopt these technologies, they will need employees who know how to use them. There are many ways to learn AI and machine learning, such as taking online courses or attending conferences.

The salaries for AI/ML jobs will continue to rise in 2022. With the demand for these skills increasing, employers will be willing to pay more for employees who have them. In addition, as AI and machine learning technologies become more commonplace, workers with these skills will be in high demand globally.

Significance of AIML courses in today’s era

In today’s era, Artificial intelligence (AI) and machine learning are two of the hottest topics in the tech industry. There is a lot of hype around AI and machine learning and for a good reason. These technologies have the potential to revolutionize many industries and change the way we live.

AI and machine learning are already being used in several ways, such as improving search results on Google, identifying plagiarism, and helping doctors diagnose diseases. As these technologies continue to develop, they will become even more integrated into our lives.

e-learning training programs

That’s why it’s essential to learn machine learning now. If you want to stay ahead of the curve and be prepared for the future, then you need to understand these technologies. Luckily, several excellent courses can teach you everything you need to know about AI and machine learning.

Some skills you learn during an AI, or machine learning course include:

  • Statistical methods: You will learn about different statistical methods used for data analysis. This is important for understanding how machine learning algorithms work.
  • Programming: Most courses will teach you how to code in one or more programming languages. This is necessary for implementing machine learning algorithms.
  • Linear algebra: This branch of mathematics is essential for understanding how matrix operations work in machine learning.
  • Calculus: Differential equations are used extensively in machine learning!

Career scope after Artificial intelligence course?

Numerous career opportunities are available for those who complete a course in artificial intelligence (AI) and machine learning. With the right skillset, you could pursue a role as a data scientist, software engineer, research scientist, or business intelligence analyst, to name just a few potential positions.

Data scientists are in high demand across almost all industries, as they play a vital role in extracting insights from large data sets. AI and machine learning are essential tools for data scientists, so if you have these skillsets, you will be well-placed to pursue this career path.

Software engineering, research scientists and business intelligence are other popular career choices for those with AI and machine learning skills. These roles suit those with strong analytical & mathematical skills.

Learn and Grow with Imarticus Learning:

Imarticus Learning offers a PG program in Data Analytics & Machine Learning, an assured placement postgraduate program built for future data science experts. Students learn real-world applications of data science & build predictive models.

Why this Course:

Artificial Intelligence Training: Grasp foundations of AIML and learn the data science tools and be job-ready. 

Placement: The course comes with an excellent job assurance.

Best learning input: Live instructor-led sessions to provide the best student outcomes.

Practical Approach: Master skills through real-world projects, hackathons, capstone projects and mock interviews.

Contact the Live Chat Support system or visit our Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad training centres.