Contact Us
×

Category: Management

Supervised Learning: Definitions and concepts you need to know

Posted on by Imarticus Learning

In recent years, artificial intelligence (AI) and machine learning (ML) have gained immense popularity and are expanding their horizons rapidly. It is said that technologies driven by ML and AI are yet to show their true potential. Hence, companies from every sector are adopting AI and ML and trying to integrate various powerful technologies. This is why, the future of artificial intelligence and machine learning is quite promising.

One of the subfields of artificial intelligence and machine learning is supervised learning. To learn and understand more about this sub-area, one can get enrolled in online artificial intelligence and machine learning course. This will help to create a vivid understanding of supervised learning. Subsequently, an individual can commence a successful and lucrative career in supervised learning.

What do you mean by supervised learning?

Supervised learning is one of the promptly growing sub-arenas of artificial intelligence and machine learning. This branch deals with issues faced in the real world. It also has the potential to solve these problems. Notably, problems like the segregation of spam mail and messages can be easily done with the help of this amusing technology. Supervised learning consists of various datasets and algorithms that can predict the results automatically.

If an individual is willing to commence a career in supervised learning, then he/she must have detailed knowledge about it. For this, one can opt for online supervised learning training. This will help you to bag lucrative job offers.

How does supervised learning function?

Supervised learning acts on the training set. This dataset trains a model for the desired output which is later yielded by the model. A training dataset mainly consists of various inputs and correct outputs. This procedure assists the machine or model to comprehend real-life problems over sufficient time. The training dataset adjusts all the errors until it is minimised and accurate. 

Supervised learning segregates problem detection into two distinct categories. And, they are:

Classification

Classification can assign tested data to accurate categories with the assistance of an algorithm. It traces, defines, and labels different data entries within the dataset of the model. The few most commonly used classification algorithms are k-nearest neighbour, linear classifiers, decision trees, random forests, and support vector machines (SVM). These algorithms are user-friendly and easy to use. 

Regression

Regression is used to comprehend the link between dependent and independent variables. It is usually used to create projections or statistics. Some of the most used regression algorithms are logistical regression, linear regression, and polynomial regression.

What are the various algorithms of supervised learning?

Supervised learning has various types of algorithms. And, these have been precisely discussed below:

K-nearest Neighbour

KKN is also known as k-nearest neighbour. This segregates data points with the help of proximity to other data. This algorithm tends to assume that the same data points can be located exactly near each other. So, it calculates the distance between two data points with the assistance of Euclidean distance.

Random Forest

One of the most famous and flexible supervised learning algorithms is Random Forest. It can be used for classification as well as regression. Initially, it obtains all the unrelated decision trees and unifies them together to obtain more precise data projections  

Support Vector Machine (SVM)

One of the most popular supervised learning models is Support Vector Machine (SVM). This was created by Vladimir Vapnik and can be used for regression as well as classification. This model creates a hyperplane, where distance is maximised between two classes of data points. This hyperplane is also known as the decision boundary.

Logistic Regression

Logistic regression is generally used when there is a binary or dual output like ‘yes’ and ‘no’. This regression model is built to comprehend the bond between the inputs. However, the main task of Logistic Regression is to resolve problems like spam identification.

Linear Regression

The main task of Linear Regression is to find the link between a dependent variable and independent variables. It is also responsible for foreseeing future results. There are two kinds of Linear Regression, namely Multiple Linear Regression and Simple Linear Regression. For an instance, when there is only one dependent variable and one independent variable, it is known as Simple Linear Regression. However, when there is more than one independent variable, it is referred to as Multiple Linear Regression. The method of least squares is used to plot the line of best fit for different linear regressions. 

Conclusion 

Imarticus Learning is offering an IIT artificial intelligence course that covers the entire portion of supervised learning. This is an online course that is led by experienced instructors. The course will open many lucrative job opportunities for those who want to commence a career in this domain. Thus, without any delay, get yourself enrolled in this online course. 

A quick guide to understanding neural networks and their applications

Posted on by Imarticus Learning

Introduction

We have been hearing about AI everywhere and how it will replace humans in many sectors.

But do we really know what it is? And, how is it going to affect the human race?

Nowadays, AI is a commonly used terminology in analytics. It is often used in neural networks or artificial neural networks. Especially, if you are looking to build a career in data analytics.

An algorithm called a neural network allows a computer to learn from observational data. Computing neural networks are modelled on how the biological nervous system processes information.

Interconnected neurons with input-receiving dendrites make up biological neural networks. They generate an output based on these inputs and send it to another neuron through an axon.

History of AI

Let’s dive deeper into the history of AI and how it evolved to have a better understanding of it.

Since the 1950s, researchers have been working to create smarter and better robots. To do this, they mimic how neurons function.

Humans ultimately succeeded in building such a computer. A computer that could identify human speech, after much trial and error. Only after the year 2000 were people able to achieve deep learning. It is a branch of AI that can recognize and differentiate between different images and movies.

Deep Learning: Do we know what it is?

Deep learning is a subset of machine learning. It enables computers to learn from examples as people do.

Instead of hardwiring a computer programme to detect and learn, machines are educated using images as examples. You have control over the factors that feed into it, not how it knows. The computer recognizes the object based on the previous input photographs.

Any system using deep learning is powered by a synthetic version of a biological neuron.

Origin of the term “Neural Network”

After learning the history of AI, let’s dive into the origin of the term ‘Neural Network’.

The earliest prototype of an artificial neural network was created by logician Walter Pitts and neuroscientist Warren S. McCulloch. Their work is where the word ‘neural network’ originated. They discussed the idea of a neuron in their work. A neural network is a single cell that is part of a network of cells and takes inputs, evaluates them, and produces an output.

Functions of Neural Networks 

Neural networks can carry out the following tasks.

Text translation.

Recognize faces.

Identify speech.

Identify text written by hand.

Command robots.

These are just a few examples, but neural networks can perform many more functions.

Types of Neural Networks

We have talked a lot about the history and origin. Now, let’s see the types of Neural Networks.

Multi-layer perceptron

The neural network employs a nonlinear activation function and a multi-dimensional perceptron. The multi-dimensional perceptron might have three or more layers.

Convolutional Neural Network

This neural network employs a variant of complex perceptrons and the convolutional neural network.

Recursive Neural Network

It uses weights to produce structured predictions.

Recurrent Neural Network

A recurrent neural network is the fourth one. It links neurons in a specifically directed cycle.

LSTM neural network

LSTM neural network utilizes the recurrent neural network design. This long short-term memory neural network lacks an activation function.

Sequence-To-Sequence Models

The last two modules create a vector space from a large amount of text. It uses two recurrent networks and shallow neural networks.

How do the neural networks work and are put to use?

As discussed earlier, the purpose of neural networks is to find patterns in data. Clustering, classification, and prediction are used to separate these patterns. These all address specific issues that apply to various fields. The fields include marketing, sales, security, and finance.

Neural networks are used for a variety of tasks. It includes facial recognition software to apprehend criminals and daily stock market forecasting.

These networks can be leveraged for marketing objectives. They can be used for chatbots, target marketing, and market segmentation.

Neural networks will be used in biomedical systems in the upcoming years. They will be used to track down diseases. Or even to determine the probability of a person having a particular genetic characteristic or anomaly.

Conclusion 

Artificial neural networks come in a variety of forms and functions to yield astounding outcomes. The neural networks are constructed similar to how brain neurons function. It is their most crucial feature.

Consequently, they are built to acquire more knowledge and make decisions in a human-like manner. Thus, neural networks can actually deliver better results. It contrasts typical machine learning algorithms which seem to stop after a certain point.

Data science is used in the real world and creates prediction models to improve business outcomes. This ensured placement program is appropriate for professionals and recent graduates. Anyone who wants to pursue a career in data analytics and science can pursue this degree.

Get in touch with us via chat support for building a data science career. You can also visit our training facilities in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Machine learning tools that data scientists must learn in 2023

Posted on by Imarticus Learning

Machine Learning is an inseparable part of Data science these days. With the advancement in software development in AI and ML, several advanced and cutting-edge Machine Learning tools have been introduced in the market. 

corporate leadership

Due to popular demand, these tools have become easier to access, and every data scientist should avail of this wonderful opportunity. If you are a data scientist pursuing a PG in data analytics, it is even more important that you learn how to use these tools. Learning these tools will also be advantageous for your curricular studies, and you can upgrade your skills. 

Top 8 Machine Learning Tools Every Data Scientist Must Learn

And now, let me share about each of them in greater detail!

  1. Python

Python is a widely used programming language and a useful tool in data science to analyse data. It can also be repurposed for machine learning and deep learning. The syntax is also quite easy, and the programming language has rich libraries. 

The community is also very active and responds quickly in case you have an issue. There are also regular boot camps for Python in India. There are many resources where you can learn Python. You can take an online course or read a book to learn the tricks. 

  1. NumPy

It is an acronym for Numerical Python. It gives support for multi-dimensional arrays and matrices. This Python library uses C/C++ for its development. The biggest advantage of using NumPy is that it provides all the necessary mathematical support for ML. 

It also uses less memory and has a faster performance when compared to other libraries. It is truly an asset for Data Scientists who use machine learning for projects like random password generators, statistical analysis, calculators or video games.

  1. Pandas

It is a data analysis and manipulation library built over the NumPy package’s architecture. It helps to handle tabular data. Pandas are quite flexible, as they can be used with other tools as well. You can effectively use it to build a recommendation system like Netflix or Python. You can also make prediction systems for stocks and neuroscience from this package.

  1. Scikit 

It is an open-source ML library for Python. It is built over the architecture of NumPy, SciPy and Matplotlib. Since it is accessible and reusable, it has great flexibility. It can be used for training and testing models using classification, clustering and regression algorithms. 

Apart from making prediction analysis, recommendations systems and automation, it can also be used to develop evaluation and matchmaking systems.

  1. Matplotlib

It helps in data visualisation and graphical plotting and is a wonderful OOPs tool that helps make embeddable plotting APIs. Since it can be used cross-platform, it can be integrated with third-party apps. It includes LaTex to develop neuroscience apps, stock price evaluation systems and also for game development.

  1. R Programming

R is another famous tool for Data Scientists who are also into machine learning. It is also a good choice of popular programming language highly regarded by statisticians or data scientists. It is also useful for a visual representation of data (with the help of ggplot2). 

R has many packages, making it a perfect scientific research tool. It finds many applications in the healthcare data sector and other fields that heavily use statistics. It is also best suited for data mining.

  1. TensorFlow

TensorFlow is quite a robust machine-learning tool developed by Google. As a data scientist, you can use it to build and train machine learning models in a short time. It provides a data automation platform. You can also train and monitor your models using TensorFlow. This tool is extremely useful but only when the hardware is decent enough.

  1. Hadoop 

Apache Hadoop is a collection of open-source software platforms that allows data scientists to use a whole computer network to solve Big Data and Computation problems. Hadoop provides a software framework that helps distribute the storage and improves big data processing using the MapReduce programming model. 

Now Hadoop is used to power many cloud storage apps and also powers search engines and social networks. Its community is so widespread that you have multiple resources to learn Hadoop online.

As an aspiring data scientist, it might be challenging to learn these separately. However, there is an option to learn all these tools at once. Imarticus Learning has a good data science course with placement, which covers all these important tools as a part of its curriculum. You will be taught by the best faculty and even be given a job placement after ending this course. What else could you ask for? 

The Importance of PG Data Analytics in A Data Analyst’s Life

Posted on by Imarticus Learning

As a data analyst, you know that having accurate, reliable data is essential to your job. But what if the data you’re working with could be cleaner? That’s where PG in Data Analytics comes in. Data Analytics is a powerful tool that can help you clean and organize your data to get the most out of it. This blog will show you how to use Data Analytics to make your life as a data analyst easier.

Importance of Data

As a data analyst, one of your most important responsibilities is to ensure that the data you’re working with is clean and accurate. This can be challenging, especially when working with large data sets. 

Data analytics’s features make it the perfect tool for data analysts. Additionally, it allows users to filter and sort data to find the information they need quickly and easily. Finally, Data Analytics offers several advanced features that enable users to customize their experience. 

How to Use Data Analytics?

Now that we’ve discussed some of the features that make Data Analytics a valuable tool for data analysts, let’s talk about how to use it. When you first open Data Analytics, you’ll see a dashboard with various options. The first thing you’ll want to do is select the “Data” tab. This will take you to the “Data Explorer” page, where you can begin cleaning and organizing your data. 

Select the “Filter” option from the left-hand menu to clean your data. This will allow you to specify which columns you want to include in your analysis. Next, select the “Sort” option from the left-hand menu. Finally, select the “Visualize” option from the left-hand menu. This will enable you to create charts and graphs that will help you better understand your data. 

The Benefits of Getting Started with Data Analytics

Many learners are intimidated by the thought of data analytics. They see it as a complex, confusing subject that needs to get explained. However, data analytics can be advantageous and exciting once you start. 

Here are some benefits of getting started with data analytics: 

You can use data analytics to answer all sorts of questions about our world. For example, you can use data analytics to determine why crime rates are higher in certain areas or what factors contribute to successful relationships. By understanding the data, you will better understand the world around you.

Data Analytics is a powerful tool every data analyst should have in their arsenal. It offers an intuitive interface, the ability to filter and sort data, and several advanced features that make it an invaluable tool for anyone who works with data daily. So what are you waiting for? 

Discover PG in data analytics with Imarticus Learning

 You might be able to find employment at Tableau with the aid of this data analyst training. Create complex models using data science to produce vital business forecasts and insights using what you’ve learned.

Course Benefits for Students:

  • Students will be familiar with the most common data science methodologies and tools and the fundamentals of data analytics and machine learning.
  • Students who complete 25 real-world projects and case studies under the guidance of business partners will receive a data analytics certification course. The data science and analytics course is an intensive program that will teach you how to use data analytics to solve real-world problems.
  • One of the most in-demand skills on the market is the capacity to display data using a data analytics tool.

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

Take This Data Analytics Course and Get Placed in The Top Companies!

Posted on by Imarticus Learning

Data analytics is one of the most happening careers these days. According to multiple surveys, graduates and postgraduates seek additional qualifications and jobs in this sector. The main reason is the handsome salary and great career prospects. Therefore, having data analyst training in today’s time can give you a significant advantage over others.

However, interest in this field alone is not sufficient. As a data analyst aspirant, you need to study well and get certified by a premier institute. The best thing about getting an education from renowned institutes is that you get a solid foundation in data analysis. You know all the techniques required to extract information from it. Due to your strong grip on the fundamentals and experience of working on live projects and with industry experts, you stand out as a candidate.

In this regard, you can look at premier institutions like Imarticus Learning for PG in data analytics.

What do you get from the data analytics training from Imarticus Learning?

Apart from getting a strong foundation in the field of data analytics, you will also get a chance to build the core concepts in data processing. With this postgraduate program in data science and analytics, you will also get to understand the prevalent practices in the industry. Their teaching methodology has projects, which require a practical approach towards solving problems. That means you will work out problems in the ways professionals do in the real world. So you will be prepared beforehand with the skills that your employer expects from you after a year of being on the job. So, you can sail through the training time and get down to the game immediately after joining. That also means you can perform better and get a quicker promotion.

With that being said, Imarticus Learning also provides you with a data analytics course with placement in the top companies of the world. The hiring partners of Imarticus are industry leaders and offer a great experience for beginners. They get a chance to learn new things like handling a project in a team, taking responsibility as a professional, etc. This way, you can build up leadership skills and can also guide your colleagues in testing times. Resultantly, you build a great reputation as an employee, which further reflects on your career progress.

The top companies where you will get placed via Imarticus Learning

Capgemini

Capgemini helps other client companies process tons of data to help the enterprise grow its revenue. They also help to improve the value chains by transforming the operations by providing the necessary insights with the help of AI and ML, giving them the edge over the other competitors. So they hire many data analysts who need to deliver data-powered solutions for these client companies.

RBS

The data analysts at RBS perform data analysis that involves the visualisation of data and mining the data for procuring the solutions and giving a predictive analysis for the problem. The data analysts also need to provide data-based warehousing along with extraction, collection and cleaning of data. As a data analyst, you need to know Tableau, Power BI and SQL data modelling, along with great storytelling abilities, to deliver a presentation to the stakeholder and team leaders. You also need to know how to make ETL packages for regulatory reporting in the company. 

HSBC

HSBC being a banking organisation, requires data analysts for financial analysis roles. It requires a lot of data analysts who can help them improve the quantity of data delivered, maintaining the same standards they have set for financial reporting. As a data analyst, you are expected to know the programming languages that are used in data analysis, and these include SAS, SQL, and Python as compulsory languages. The data analyst also knows how to build dashboards so that they can give the stakeholders a clearer view of what insights can be generated for the data. The environment at HSBC is quite fast-paced, so the data science aspirant should be able to show dynamism on the job and also be able to deliver end-to-end individual projects.  

KPMG

The data analysts at KPMG are armed with all the high-quality data analysis techniques to acquire data from primary/secondary sources. Then they need to understand the warehousing of data to store and maintain the large client databases. They also need to identify, analyse and interpret new trends from the complex data sets improving the target operations.

To sum up, completing the data analyst training from Imarticus Learning offers you the foundation you need to begin your career in this domain. The course, with its updated curriculum, live projects, experienced faculties and placement assistance, ensures that you fulfil your dream of becoming a data analyst without any hiccups.

Coding Resources for Getting Started with Your Artificial Intelligence and Machine Learning Course

Posted on by Imarticus Learning

Nowadays, AI and Machine Learning courses have become quite popular among computer science enthusiasts. Besides the traditional employment opportunities, completing these courses have opened up new opportunities for them. 

However, the question is, where to get this certification from? Well, to help you in this quest and find the right answer, here are some artificial intelligence and machine learning courses that you can start your journey with.

Coding resources to get started with AI and ML course

  • CS50 Harvard: Introduction to AI with Python

CS50 is a public course which has been taught by David Malan. Since David is a Harvard-based professor of Computer Science, the course contains all the resources and the teaching style of Harvard. And this is a big plus for students. Being the largest course in both Harvard’s MOOC resources and on the online education platform, edX, the course has millions of followers.

 

This AI and Machine Learning course comprise the basics of AI and ML, like Graph Search Algorithms, Reinforcement Learning, Intelligent Systems, Machine Learning Algorithms, Natural Language Processing, Neural Networks and other concepts. What’s best about this course is that it is taught in an interesting way and an easy language so that beginners can also pick on the complex concepts and jargon in a super easy manner. The auditing classes are free of cost, and it is also one of the most considerable online resources for AI and ML.

  • Google’s machine learning crash course

This ML course by Google has been coupled with the TensorFlow APIs course. This course is equally beneficial for beginners and those with previous experience in programming and mathematics. The course contains lectures on video, practical exercises and real-world case studies. Within a week or two, you will be able to understand how to program ML algorithms.

  • Purdue University and IBM’s AI and machine learning courses

In collaboration with IBM, Purdue University has developed this course for advanced learners who have a basic understanding of AI and ML. It covers concepts like basic ML algorithms and techniques, reinforcement learning, NLP, neural networks and how to utilise tools like Amazon Sagemaker, Python, TensorFlow, Keras, OpenAI gym, Alexa and other popular frameworks and libraries.

As students, you will also be given live guidance sessions by faculty from Purdue or industry experts from IBM. The faculty is internationally recognized and has industrial experience in AI and ML. The best feature of this artificial intelligence and machine learning course is that you can participate in the exclusive IBM hackathons. You will also get to work on capstone projects with industrial datasets from companies like Mercedes-Benz, Twitter and Uber. To be enrolled in this course, you need to have basic knowledge of programming and mathematics. If you have work experience, then you would have the edge over others to get approved for this course.

  • AI and Machine Learning Course from freecodecamp.org

If you are looking for a free course to sample what is in store in AI and ML, then this is the best one on AI and ML available online. It is a must for those who have prior coding experiences in life. But still, it is recommended that just like the other courses, it would be beneficial if you had some programming knowledge in Python and some basics in mathematics. This course would give you a walkthrough via the beginning steps, helping you qualify for an intermediate level of understanding. From that, you would be prepared to go to the next step or the advanced level in AI and ML.

  • AI and ML course from Imarticus Learning and E&ICT, IIT Guwahati

This is a prestigious IIT AI ML course, and the faculty is also one of the best in the country. You will get to learn about basic Python programming concepts. From that, you will graduate level by level, taking you from the easy to the most complex concepts in artificial intelligence and machine learning. It is by far the most reliable course on this list.  

Not only that, you will receive training from industry-grade projects. Then you will also get placement assistance alongside mentorship on various aspects like how you should approach problems and how you should build your portfolio as an AI and ML engineer. It is a good and valuable AI and ML course offered by Imarticus Learning and IIT Guwahati.

To sum up, as the demand for AI and ML increases in the coming years, the demand for capable professionals will also be sore. So, if you can complete an artificial intelligence and machine learning course from any reputed institute and learn how to develop programs, it will help you reach the top of the field without any hassle. Hopefully, this write-up has offered you some insights on the courses to start your journey with. So, get enrolled to create your success story. 

Related Articles 

How I Learned Computer Vision Quickly In 2022

Why should a certificate program in data science and machine learning be part of your career goal?

Posted on by Imarticus Learning

Data science is a field that studies data and how they extract meaning from it. It uses different methods and tools to extract, analyse, visualise and manage to create insights from structured as well as unstructured data. On the other hand, machine learning is a field of artificial intelligence that includes the development of software and algorithms which can make predictions based on data.

The Certification Program in Data Science and Machine Learning will help you to get started with these specialised domains. This program focuses on teaching the candidates about the different aspects and fundamentals of data science and machine learning. It ensures that you are equipped with the proper knowledge for implementing and applying your skills in real-world situations.

The Certification Program in Data Science and Machine Learning will consist of 5 months of live online training where you will use Python to learn more about data mining, data exploration, artificial intelligence, etc. This course will help and guide you to become professionals who can give meaningful insights from data and guide businesses to make correct decisions for their growth. 

Top 5 Advantages of Data Science 

Data science combines principles and practices from the field of statistics and mathematics to analyse data. It includes massive benefits and some of them are as follows: 

  • Data Science is Versatile 

Data science is a versatile field as it is widely used in banking, healthcare, consultancy services and e-commerce industries. Hence, you will have opportunities to work in different fields. 

  • Data Science Makes Data Better 

Every organisation requires skilled data scientists to process and analyse their data. This is because they enrich the data and make it better for an organisation. 

  • Data Science can Save Lives

Data science has greatly improved the healthcare sector. It is used in healthcare for a variety of purposes, including improved diagnosis, drug development and prevention. Various healthcare industries are using data science to help their clients.  

  • Data Science Makes Products Smarter

 Data science involves machine learning, which helps industries to create better products for better customer experiences.

  • Abundance of Positions 

Data science is a wide field that will give you various opportunities to grow and it is high in demand. This makes it a lucrative career option for you. 

 Skills Required to Build a Career in Data Science

The skills which are required to pursue a career in data science are as follows: 

  • Good communication and teamwork skills
  • Strong knowledge of programming languages
  • Understanding of maths and statistics
  • Data visualisation skills 

Top 5 Advantages of Machine Learning 

Machine learning is an area of artificial intelligence that includes the development of software. Some of the benefits of machine learning are as follows:

  • Fraud Detection

Detecting and preventing fraud in today’s time is very essential. Therefore, machine learning is a great source for detecting fraudulent activities in financial transactions.

Both machine learning and data science can help to predict future trends and events. These predictions further help businesses to keep up with these trends and make better decisions for their organisation. 

  • Healthcare   

Machine learning has a role in healthcare too. It can identify cancer cell and heart complications. It is also used for personalised medicine, which involves treatment based on a patient’s genetic makeup. 

  • Finance 

Machine learning can improve financial forecasts. Having a better understanding of risk can help businesses to make more informed decisions about their investment of money as well as how to protect their assets.

  • Data Mining 

Machine learning can be used for mining big data. By using this information, a data scientist can find new customers, can predict trends and can also improve business operations. 

Skills Required in Machine Learning

Some of the skills required in machine learning are as follow: 

  • Programming knowledge such as Python 
  • Ability to conduct data analysis 
  • Understanding of statistics and probability 
  • Expertise in computer science 

Conclusion

Data science is vital for almost every field. With new advancements and discoveries, you always get the opportunity to learn something new. If you decide to pursue a machine learning course you achieve an IIT Roorkee machine learning certificate upon completion of the course successfully.  We see that the importance of these courses is increasing day by day. There is the flexibility of live online sessions with top faculty of India. They aim to upgrade your knowledge and skills to set you ahead of the competition. This course will not only help you to build a career but also helps you in your personal growth.  

We analysed the most popular data analytics courses with guaranteed job-interviews: Our verdict

Posted on by Imarticus Learning

Are you looking to get into data analytics but are overwhelmed by the number of courses available? The prospects that a successful career in data analytics can offer may seem distant and out of reach, yet with the right course, this dream could become a reality. 

Data Analytics Course

A data analytics course offers a real opportunity to gain the skills and experience needed to land yourself a great job. A successful course backed by an established organization will help you get your foot in the door and secure the position of your dreams. 

The Data Analytics course gives you the best of both worlds, combining a comprehensive syllabus with a guaranteed job offer upon completion.

We’ve conducted rigorous research to clarify the most popular data analytics courses with guaranteed job interviews – ensuring your success in gaining employment and your peace of mind knowing that committing to one of these courses will lead to tangible results. 

Unlock the potential of your career with comprehensive data analyst training.

Are you looking for the utmost data analytics courses with job interview guarantees?

Let us show you how to locate the top-rated programs that will get your career off and running!

  • Do Your Research

The first step is to do your research. Look for data analytics boot camps that offer comprehensive courses covering topics such as predictive analytics, machine learning, natural language processing, and more. Make sure the program has a strong focus on hands-on projects and internships so that you gain real-world experience and skills. Also, check out reviews from past students to get an idea of how effective the program is at helping students land jobs after they complete their studies. 

  • Look For Guaranteed Placements

Once you’ve done your research, it’s time to look for programs that offer guaranteed interviews upon completion. These types of programs are ideal because they ensure that you will have a job lined up before or shortly after graduating—which means no more months spent searching for jobs in vain! Plus, these programs usually provide career counseling services so that you can make sure your resume and other job search materials are up to snuff. 

  • Check Out Online Courses: 

Finally, remember online courses! Online courses can be just as practical as classroom learning when preparing for a career in data analytics. They are more flexible and affordable than traditional schools or boot camps. Make sure the online school offers robust support services like career counseling, so you don’t feel alone during your job search journey!  

Now that you thoroughly understand how to identify the best data analytics course with job-interview assurance let us take an in-depth look at our top pick.

Unlock Your Potential in Data Analytics with Imarticus Learning!

Unlocking the true potential of data science and constructing models that will maximize business results is now possible with this job-interview program. Perfect for fresh grads or professionals seeking to establish an influential career in analytics, you’ll gain a hands-on understanding of how analytics can produce tangible outcomes within businesses. 

With the end goal being successful employment as an experienced data scientist in this revolutionary field, get ready to witness your knowledge come alive!

Highly-experienced faculty deliver a comprehensive program using an engaging platform and hands-on training approaches to get you ready for success in several data science roles. You will gain a complete understanding of the most in-demand analytics tools with lectures, workshops, and projects based on real-world datasets. 

Plus, with real-time feedback from industry experts, you can rest assured that your journey toward data science mastery is secure.

Gain a competitive edge in the job market with expertise in data science, Python, SQL, data analytics, and more. Unlock hands-on knowledge of Power BI and Tableau to support decisions that will truly transform your business!

Course Benefits for Students:

  • Students can learn data analytics online without leaving their home comfort.
  • Gain hands-on experience with data science and analytics codes.
  • PG in data analytics certification provides learners the complete theoretical and practical knowledge of data analytics.

Effects of Demand Forecasting Errors on Operation Planning in Supply Chain

Posted on by Imarticus Learning

Demand forecasting is the procedure of predicting future customer demand for a product or service. Demand forecasting can be accomplished in three ways: top-down, bottom-up, and middle-out. In each approach, the goal is to analyze historical data and make predictions. 

However, there are a lot of techniques to do this, and some methods are more effective than others. Through this blog, we will explore how inaccurate demand forecasts affect operation planning in the supply chain.

What is a Demand Forecast?

Demand forecasting estimates future customer demand over a predetermined period using historical data and other information.

For managers to make wise decisions about pricing, business growth strategies, and market potential, effective demand forecasting provides valuable information about their potential in both their current market and other markets.

Without demand forecasting, companies risk making wrong decisions about their products and target markets. Wrong choices can significantly affect inventory maintenance costs, customer satisfaction, supply chain management, and profitability.

What are the Causes of Demand Forecasting Errors?

Distributors may believe that the same demand for the same goods will occur simultaneously and in the same amount every year when planning demand. This complacency can lead to forecast errors, which are detrimental to the business and its clients. 

Reducing forecast error is even more crucial when an external shock significantly shifts demand, like the global COVID-19 pandemic. Distributors can no longer solely rely on past sales to predict future ones.

The gap between expected and actual demand is known as the forecast error. The impact on your money increases with the size of the difference. 

The Effects of Demand Forecasting Errors on Operation Planning in Supply Chain

  • Effect 1: Complexity in Operations Planning

Operations planning involves the management of an organization’s resources to achieve desired output levels. Operations planning requires accurate forecasting of demand, supply, and other related variables. The success of operations planning depends on the accuracy of demand and supply forecasts. However, demand forecasting errors will always exist, even with sophisticated supply chain management techniques.

  • Effect 2: Poor Performance in Forecasting Demand

Subtle changes can occur, like a break in the supply chain. Or they could be significant, like when new laws drastically alter the playing field. Over-reliance on outdated data is a typical cause of forecasting failure because historical patterns can diverge from current events.

  • Effect 3: Increased Variability in Supply Levels

 Variability in the context of the Supply Chain refers to the degree of irregularity or volatility in the movement of materials from one end to the other.

 

  • Effect 4: Change in Scheduling of Operations

The order of operations gets specified on the production route. The scheduling sets aside space for the resource groups based on the defined operation times for the production route.

Discover a Career in supply chain management with Imarticus Learning

Managers will benefit from taking the best supply chain certification program when making tactical, operational, and strategic decisions. 

Course Benefits For Learners:

  • By integrating conventional supply chain management certification courses with data-driven decision-making, get ready to contribute to creating more innovative and tactical global supply chains in the future.
  • Students who complete the IIT supply chain analyst course can get ready for highly sought-after careers as demand planners or data scientists!
  • Python will help students make better supply chain decisions by teaching them to be data-centric.

Visit one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or contact us via chat support. 

Things your artificial intelligence and machine learning course should be teaching you

Posted on by Imarticus Learning

Artificial Intelligence (AI) and Machine Learning (ML) are technologies that have the potential to revolutionize virtually every industry. AI is an umbrella term for various methods and algorithms used to create intelligent machines that can analyze data, recognize patterns, and make decisions on their own. ML is a subset of AI that uses algorithms to learn from large amounts of data sources in order to identify patterns, trends, and insights without being explicitly programmed or supervised.

These two technologies transform businesses by enabling them to become more efficient, accurate, faster-paced, customer-focused, cost-effective, and responsive.

Making a career in Artificial Intelligence and Machine Learning?

Making a career in Artificial Intelligence and Machine Learning requires gaining knowledge and experience:

You should understand the fundamentals of AI and ML, such as how algorithms work, identify patterns in data and apply machine learning models to solve problems.

You should also gain practical skills by building AI/ML projects using open-source libraries and frameworks.

It is important to stay up-to-date with AI research and technology advancements and learn new strategies for tackling complex problems.

Seek out professional opportunities where you can gain valuable hands-on experience working on real-world applications.

Dedication and hard work make it possible to craft a promising career in this burgeoning field.

How to choose an ideal Artificial Intelligence and Machine learning course?

Choosing an ideal AI/ML course depends on your current skill level, preferred learning style, and goals.

Start by looking for a system that covers the fundamentals of AI and ML, such as basic algorithms and statistical methods.

Additionally, take courses that provide hands-on practice with tools such as Python, TensorFlow, Keras, and Scikit-learn.

Finally, look for courses tailored to specific application areas such as natural language processing (NLP), computer vision (CV), or robotics.

With so many online options available today, there is sure to be a course that perfectly fits your needs.

After completing an AI/ML course, you will have gained many skills, such as:

-Data analysis and modelling techniques to extract insights from data

-Programming algorithms in Python or other common programming languages

-Building machine learning models using popular libraries such as TensorFlow and Keras

-Understanding the fundamentals of deep learning and applying it to different tasks

-Using computer vision and natural language processing (NLP) for complex applications

-Developing strategies to solve complex problems with AI solutions

-Creating real-world projects that demonstrate your knowledge of AI/ML principles. With these skills, you will be able to build powerful AI/ML systems that can help businesses become more efficient, innovative, and cost-effective

By mastering these skills, you can pursue exciting opportunities in the AI/ML field.

Transform your career and Grow Exponentially with Imarticus Learning:

Empowering a new generation of professionals, Imarticus Learning offers exclusive learning and training through this Artificial Intelligence and Machine Learning course. We bet this is the best Machine Learning & AI certification to kick-start a Data Science Career.

An industry-approved program designed by E&ICT Academy, IIT artificial intelligence course this program is made for future Data Scientists & ML Engineers.

This AI certification program is designed with the E&ICT Academy, IIT Guwahati and industry leaders. It provides in-depth insights into basics, resulting in the best learning outcome for aspiring Artificial Intelligence and Machine Learning professionals. You go through a 9-month extensive learning schedule and prepare for the different roles as Data Scientist, Data Analyst, Machine Learning Engineer, and AI Engineer.

With goals to bolster your foundational skills in Artificial Intelligence, this AI Certification fits into the couch rightly. With an expert mentorship facility, students enrolling in this course gain a practical understanding of AIML. The best part is that this course helps you unlock lucrative career opportunities in the coveted fields of AIML.

Course USPs:

  • Learn Job-Relevant Skills
  • E&ICT Academy, IIT Guwahati Campus immersion
  • World Class Mentorship
  • Flexible Learning Process

You get an exciting opportunity to participate in a unique 3-day Campus Immersion module at the E&ICT Academy, IIT Guwahati Campus, where you interact with peers and learn from expert faculty.

For further details, contact the Live Chat Support system or plan a visit to one of our training centres in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

Get a free 1:1 Imarticus counselling
Get a free 1:1 Imarticus counselling