Degree vs skills: Learn how data analyst training can get you a job interview as a data scientist.

Posted on August 12, 2022August 24, 2023 by Imarticus Learning

Degree vs skills: Learn how data analyst training can get you job interview opportunities as a data scientist

How data analyst training can help you get a job interview as a data scientist? This is one of the most anticipated questions on the internet. It is often asked by people who are aspiring to become a data scientist, or already have a data analyst job and want to transition their career to the role of a data scientist.

In this blog, we will see how you can easily get data scientist job opportunities. But before that, note one thing, when it comes to degree vs skills, the field of data science always gives importance to skills no matter what your degree looks like. So, even if you don’t have a relevant degree but have the required skill set, you will be readily hired as a data scientist. Let’s find out how!

Why Become a Data Scientist?

Why do a large number of people want to become data scientists? What is something about this field that everyone is attracted to, despite so many complexities? Here are your answers. Following are the reasons why the job of a data scientist is very popular :

1. Rising Demand for Data Scientists

The demand for well-qualified and talented data scientists is much higher than the supply. A LinkedIn study has shown that the USA alone is facing a shortage of 151,717 data scientists. So, it is clear that if you become a data scientist, there will be no shortage of job opportunities.

2. More and Better Pay

Data scientists get paid amazingly well. They are among the highest-paid professionals in this field. According to Payscale, data scientists earn nearly between $67k and $134k per annum. That’s a massive rise after looking at the salary of data analysts, who get paid around $43k to $85k.

3. Constantly Evolving Field

Data scientists don’t have a fixed job role. Their position varies from industry to industry and business to business. They always have new and exciting projects and problems to work on. Note that, the demand for Data Scientists is increasing heavily in every field, be it retail, healthcare, sports, or e-commerce. In a nutshell, a job as a data scientist offers plenty of opportunities to grow and succeed.

How Data Analyst Training Can Get You Job Interview Opportunities as a Data Scientist?

If you’ve passed a good time as a data analyst and now want to enter the field in a more formal and powerful way, then below are a few steps that will help you get a job as a data scientist:

1. Take the Right Data Scientist Course

The very step for transitioning your career from a data analyst to a successful data scientist is to take the right data scientist course with job interview. The right course will not only help you learn data science online to acquire the necessary skills, but it will also help you secure a good job through its job interview guarantee.

2. Create an Impactful Portfolio

Whether you’ve completed your data analyst training or currently working as a data analyst looking for transitioning as a data scientist, build a powerful portfolio. As you slowly learn the skills to become a data scientist, you will enter the process of developing your portfolio

For instance, if you’ve worked on a real-time project, put it on GitHub, and list it in your portfolio. Create a handful of case studies and articles, and share them in your portfolio. By having your work, skills, and experience listed in one place, you will have something impactful to share with your interviewer or employer.

3. Apply for Jobs

Finally, start applying for the data scientist jobs that match your interest areas. As we have already discussed, data science is a vast area and has applications in almost all industries. What you need to do is, find the job roles in the industries that you’re most comfortable working with. This will make your life as a data scientist much more relieved and enjoyable as you get to work in the area you’re most interested in. Also, when you apply for jobs, don’t worry about rejections. Have patience and be confident because when you have the right skills, you will sooner be spotted by employers.

4. Grow Your Network

Last but not least, grow your network in the field of data science. The good thing about being a data analyst is that you already have a network in this industry. All you need to do is move towards the data scientist community. It will help you learn about the industry, different job roles, challenges, growth, and opportunities it offers.

So, these are the steps for becoming a data scientist from a data analyst. While it’s true that being a data analyst can give you an upper hand in this field, you have to build an entirely different skill set to land a job as a data scientist. The best way, to begin with, is to take the right course from a known institute.

How deep learning complements natural language processing

Posted on August 12, 2022October 5, 2022 by Imarticus Learning

How deep learning complements natural language processing

Let’s begin with some numbers. Statista estimated that the Artificial Intelligence market leveraging Natural Language Processing would exceed an evaluation of $127 billion by 2028. This indicates the surging interest in NLP applications, attracting tech-tycoons willing to invest heavily in further enhancing this technology. This – in turn – attracts more young talents who can dedicate their career to developing NLP. However, before deploying NLP at mass, there still are challenges that need to be addressed by developers.

Key Takeaways On Natural Language Processing

· Terms like Artificial Intelligence, Deep Learning, and Natural Language Processing are often interchangeably used. However, their operations, applications, and definitions are different in Computer Science.

· Natural Language Processing is constantly evolving with enterprise solutions that can handle speech analysis, sentiment interpretation, and market intelligence – making it scalable and efficient in industrial applications.

· The use of Natural Language Processing comes with its advantages – and disadvantages as well. While it’s true that businesses can cut down on costs, there are technological challenges that hold back NLP even today.

One Quick Introduction To Natural Language Processing

In the Artificial Intelligence domain, Natural Language Processing or NLP is a fundamental application evolving rapidly with new methodologies and toolkits. If you hold a Bachelors’s or Masters’s degree in Computer Science or Information Technology, you already have a fair bit of knowledge of how it works. In summary, “natural language” refers to how humans interact with one another – primarily through speech, expressions, and gestures. Therefore, NLP relates to the capability of computer systems to interpret natural language in an actionable manner.

The Current Limitations Of NLP

Over the past decade, NLP has made pretty serious progress in language interpretation. However, there are still a few major gaps – notably with generating description or data accuracy. Sometimes, performance is less stable, and humans need to double-check it. Other challenges include filtering any noise from the data it’s trained on. Interpretations are likely to be less efficient if the fed data is corrupted. Therefore, unless generative models become more flexible and human-like than retrieval models, Natural Language Processing can’t be deployed in mass applications.

The Fundamentals Of Retrieval And Generative Models

Retrieval Model In NLP: In the retrieval model, the algorithm typically leverages canned responses and heuristics for selecting probable responses according to the input text. However, retrieval models are inefficient with grammatical errors, and therefore, they cannot interpret specific conversational texts with no predefined responses.

Generative Model In NLP: Generative models – on the other hand – can interpret entirely new responses and can also dynamically address unforeseen cases. They are smart, efficient, and complex. However, the generative model has one major caveat – it requires vast pools of training data and uses complicated techniques like machine translation.

The Role Of Deep Learning In Natural Language Processing

That is where Deep Learning comes into action! Before Deep Learning, NLP relied on the Bag of Words models like Naïve Bayes, SVM, and Logistic Regression for classifying text inputs. The main model drawback was their disregard for context in conversational word orders. This landscape soon changed with Recurrent Neural Networks, designed to process sequential data and capture short-term dependencies. Additionally, Deep Learning enables better sentiment analysis, making it accurate at interpreting feelings.

This model benefits from a feed-forward neural network as a classifier and adjusts its parameters in the dependency syntax analyzer to achieve better results. What’s unique about the feed-forwarding is that the model can memorize the analysis state and history, which enables it to capture and utilize more historical information. In addition, it can model the entire sentence’s analysis process and improve the independent state’s modeling. Therefore, with further error analysis, analysts can study dependency syntax analysis based on the neural network.

What Does The Future Of NLP Hold?

Although significant advancements have been made in the generative model, the current NLP systems still function on the elementary nature of retrieval-based models. Real conversations – aren’t scripted, are free-form, and unstructured – have a finite set of responses. Therefore, retrieval models are vastly more appropriate for handling natural language.

Interested In Learn Deep Learning & NLP?

Now that you know how Deep Learning complements Natural Language Processing, here’s where you can learn it from. If you are interested in Artificial Intelligence courses certification from The E&ICT Academy of IIT Guwahati, check out our courses at Imarticus Learning, where you can excel in your career with an industry-approved curriculum.

5 Qualities The Best People In The Artificial Intelligence Industry Tend To Have

Posted on August 12, 2022March 22, 2024 by Imarticus Learning

5 Qualities The Best People In The Artificial Intelligence Industry Tend To Have

Working in the artificial intelligence industry is no easy task. This sector is growing at a fantastic rate, and this growth shows no sign of slowing down. Every day new companies are popping up, and more general businesses are looking to get involved with machine learning programs. This means there is a high demand for developers with skills in artificial intelligence.

Artificial intelligence (AI) technologies have grown in recent years. Our daily lives get impacted by these artificial intelligence applications, which range from self-driving automobiles to robots serving meals in restaurants. AI primarily creates intelligent systems and software based on how human minds reason, learn, make decisions, and solve problems. It lets robots know via experience and carry out tasks similar to humans. But what exactly makes a good AI candidate?

Here are five qualities that the best people in the artificial intelligence industry tend to have:

Love of learning: AI requires constant learning and development. You’ll need to be able to learn new skills quickly so that you can adapt as technology changes over time.

Creative thinking: Creative thinking is essential if you want to create something original with AI—an algorithm that detects faces in images or an app that automatically generates high-quality music based on your taste preferences.

Emotional intelligence: Being able to deal with emotions daily will help you better understand how humans react when faced with difficult situations—and thus better handle those situations yourself when they arise in your life!

Be able to explain complex ideas: They’re able to explain difficult concepts easily. They can do this through strong writing skills or by communicating with clarity and precision.

Strong work ethic: These professionals are willing to put in the time and effort necessary to achieve their goals—and they don’t give up easily when things get complicated.

These qualities are essential for people who want to work in AI because it takes a lot of dedication and discipline to learn how it works and then figure out how you can use it for your purposes. AI is essential since it is the fundamental building block of computer learning.

Learn AI and Machine Learning Courses with Imarticus Learning.

Attend the E & ICT Academy deep learning Artificial Intelligence certificate program to discover how to become an AI engineer. This IIT AI ML Course will help students prepare for careers as data scientists, data analysts, machine learning engineers, and AI engineers.

Course Benefits For Learners:

To get practical industrial experience and prepare for a fulfilling data science career, students work on 25 real-world projects.
You may amaze employers and demonstrate your talents with a certificate authorized by the E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed credential.
This artificial intelligence course will help students land lucrative jobs in machine learning and artificial intelligence.

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

NLP for future data scientists: A comprehensive guide

Posted on August 12, 2022 by Imarticus Learning

NLP for future data scientists: A comprehensive guide

Natural Language Processing (NLP) is a computer science and engineering field that deals with human language processing. You can commonly use it to extract meaning from human-readable text, such as news articles, e-mails, or social media posts. The field applies to language modeling for speech recognition and generation.

NLP in data science comprises using algorithms to detect and extract natural language rules, converting unstructured language data into a different form that computers can comprehend.

What is Natural Language Processing (NLP)?

Natural language processing (NLP) studies a computer’s understanding of human language. You can use NLP in many applications like search engines, chatbots, and voice assistants. It can also get used in data science to analyze text data such as tweets or documents.

NLP in today’s world

NLP is used in many industries and by many people. It’s a powerful technology, and it will only get more so. It’s also becoming increasingly important as the world becomes more connected and we rely on machines for our daily needs.

NLP has been for decades, but it still comes up with new uses every day—from creating virtual assistants to helping people with disabilities communicate better with others through voice recognition software or text-to-speech devices (which can even translate languages). And don’t forget about applications of NLP outside just language processing: there are plenty of ways that NLP can get used as well!

For example, you might not think about how artificial intelligence could improve medical care systems; however, this technology could help doctors diagnose patients faster by using machine learning algorithms instead of manually analyzing test results from lab tests done earlier by doctors.

Job opportunities in NLP

NLP is used in many industries and is becoming more and more critical. This list includes:

Customer service
Healthcare
Education (e.g., teaching, tutoring)
Business (e.g., sales, marketing)
Security (e.g., anti-fraud analysis)

Applications of NLP

Language is very ambiguous; meaning gets conveyed through subtle cues and context. Computers have a difficult time dealing with ambiguity. As a result, individuals face the difficult task of interpreting meaning without complete awareness of contexts, such as common sense and culture.

We express meaning in ordinary speech without contemplating how our brains transform so much unstructured material into meaningful knowledge. On the other hand, understanding human voice and language is extremely difficult for robots.

You can apply NLP in a variety of domains, including:

Search engines
Social media (Twitter, Facebook)
Business and commerce (e-commerce websites, customer service)
Healthcare (diagnosis and treatment planning)
Education (language translation services for teachers or students)

These applications are examples of how NLP can help people around you.

Discover a career in data science with Imarticus Learning

This data science course with job placement will teach students data science in a practical setting. Students will create complex models that will generate critical business forecasts and insights.

Course Benefits for Students:

Students will be familiar with data analytics, machine learning basics, and the most extensively used data science tools and methodologies.
To get a data analyst certification course, students must complete 25 real-world projects and case studies led by business partners.
The ability to display data using a data analytics tool is one of the most sought-after skills in the industry today. As a result, new graduates and those just beginning their jobs may want to consider enrolling.

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

I learned these 7 skills from my data science and machine learning course

Posted on August 11, 2022August 11, 2022 by Imarticus Learning

I learned these 7 skills from my data science and machine learning course

Data Science is concerned with programming in which the raw data is transformed into actionable insights. A substantial amount of data is analyzed to prepare a final report. At the same time, machine learning is the branch of Artificial Intelligence closely related to data science. Machine learning predicts outcomes and enhances performance by using historical data as input. You can gain certification and develop your skills by learning Data Science and Machine learning.

Suppose you believe that learning data science and machine learning will merely lead to a certification. However, you might think that programming is the only aspect of data science that is true! It undoubtedly provides vital abilities that enable you to transform unprocessed info into extraordinary results. The course will teach you various skills that will help you advance your profession.

Programming Skills

You may learn a variety of programs through data science. These include Python, SQL, Java, R, and MATLAB, which can be used to develop a career across many industries. You can master the

Data Wrangling

Data Wrangling is an essential skill you can master and excel in your career. If you are currently working on a project and are unaware of untangling the data, then data wrangling will surely help you. Data wrangling is a crucial skill that aids in getting the data ready for transformation and mapping for future use. You will have completed the first level of the course once you have mastered this talent.

Data Visualization

It is pretty simple to create graphs, pie charts, and other pictorial presentations of data. However, the ability to communicate facts effectively before concluding is aided by data visualization skills. Your data presentation skills will improve after taking a data science course. This skill helps you in turning simple data into creative insights. Once the data has been displayed, you may create a narrative and comprehend the challenging datasets.

Cloud Computing

Understanding the idea of cloud computing is essential for managing massive amounts of data. Since Data Science Course requires the compilation of hast amount of data, you need to be familiar with cloud computing. You would require the essential skill of managing the data and processing it. This includes analyzing and visualizing the data to store it in the cloud. Since data Science and Cloud computing are mutual concepts, cloud computing enables you to use Google Cloud and Azure to store the data. Once you’ve completed this phase successfully, you can easily handle the database, operational tools, and programming languages.

ML Libraries & Algorithms

Since the job of a machine learning executive involves using algorithms and libraries which the original developers have already developed, this includes the Microsoft CNPK and Apache Spark’s MLlib. Once you have learned different concepts, you can use other concepts and integrate them into various systems.

Applied Mathematics

Since the Data Science course requires you to stay quick and perform efficiently, it also improves your math skills. The Data Science course improves your mathematical skills and polishes the concepts learned in school. Math plays a prominent role in learning machine learning. This skill equips you to use the correct ML algorithm and set appropriate confidence levels. Here, you can understand simple statistical models easily, such as distributions like Poisson, Normal, Binomial and probability, and statistics.

Domain knowledge

A thorough understanding of the topic is crucial because machine learning depends entirely on software and solutions optimization. The course provided insight into the domains that required specific design and information. The study also provided knowledge on different parts available for working.

Therefore, doing a Data Science Certificate Course would give you a variety of abilities and boost your effectiveness at work. Additionally, it improves your capacity for excellence in your tasks and clever work. You can contact us through our program’s webpage for more information about the Data Science Certificate Course. Even better, you can browse our centers and chat with support. Additionally, you can get in touch with us using the 24/7 chat assistance. Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, and Ahmedabad are the locations of our training facilities.

Top 6 fun uses of artificial intelligence and machine learning

Posted on August 11, 2022August 11, 2022 by Imarticus Learning

Top 6 fun uses of artificial intelligence and machine learning

Artificial intelligence (AI) is used in almost all electronic devices to make them capable of human use. AI has gained popularity in recent years because of its multiple benefits. For example, AI allows software applications to understand data, analyze it, and present reports and insights.

Machine learning (ML) is part of artificial intelligence. In the current era, it is essential to learn an Artificial Intelligence course to master the skills needed for machine learning.

Here are some fun ways of using Artificial Intelligence and Machine Learning.

1. Personalized online selling

Artificial Intelligence helps software understand the customer’s likes and creates algorithms based on the same.

AI also helps generate a list of products to meet the interests, enabling e-commerce websites like Amazon to identify the search pattern of customers and then recommend the latest developments.

With the help of Artificial Intelligence, it becomes easy to access personalized selling.

2. Video Gaming

Artificial Intelligence has increased creativity in the gaming industry. It makes the game more thrilling and attracts vast customers.

Artificial Intelligence understands the pattern of games played by people. Once this is known, the next step is creating a character that AI controls. This gaming character understands the player’s technique and produces counter-attacks.

To explore the field of AI in video gaming, attend the Artificial Intelligence Course.

3. Smart Homes

The usage of Artificial Intelligence apps is increasing in intelligent homes. Smart locks, voice-controlled appliances, switches, and other gadgets. The gadgets have taken the urban lifestyle to the next level.

The usage of Artificial Intelligence has made homes energy-efficient systems. For instance, smart homes can automatically switch off the light and fan once the user steps out of the room, thereby saving electricity.

AI uses a tremendous amount of information to imitate human intelligence essentially. As a result, intelligent home appliances with AI capabilities may interact and communicate with one another, which enables them to pick up on human routines.

AI innovative home technologies gather data to forecast user behavior and provide situational awareness.

4. Machine Learning as a Chatbot Friend

Multiple mobile applications have friendly chatbots powered by Machine Learning. It studies your data and then communicates as a friend. Machine Learning helps the chatbot speak about users’ interests and send text messages similar to humans.

Replika is one of the most well-known and influential AI companions, with over 10 million users. Replika can detect photos and carry on the discussion with them, unlike conventional chatbots.

You can pick and give your AI buddy a name with Replika. You gain points as you chat with it and can use these points to unlock your AI friend’s interests, characteristics, outfits, or appearance.

It can act as a mentor, assisting you in forming good habits. When you provide personal information with Replika, such as the names of your pet, nation, and friends, it keeps a record of it and uses it in chats.

5. Hum to Search

The ‘hum to search’ concept was invented through Machine Learning. You hum a song to the particular app, and it identifies the song for you. Machine Learning works by embedding the melody from the music and finding the right piece. You can use that to search for the oldest and the most recent songs from the database.

Shazam and Pixel Sound Search are both good. However, they can only identify the exact song when pitch, speed, and instruments are present. But Google went a step further and developed “Hum,” which can even identify song names if you “hum” at it for 15 seconds while using a tone corresponding to a specific song.

6. Facial Recognition

Machine Learning is the magical element that enables apps to recognize the facial features of humans. Moreover, it also allows beauty apps to detect faces and apply filters. Machine Learning teaches these apps to see the face, align it, and extract and recognize the facial elements.

Almost every industry uses Artificial Intelligence and Machine Learning to enhance the user experience. Artificial Intelligence and Machine Learning applications have expanded to extended cloud service.

An Artificial Intelligence Course is essential to understand the dynamics of the software. If you are interested in learning about Artificial Intelligence and Machine learning, you can visit our training centers in Bengaluru, Pune, Chennai, Delhi, Mumbai, Gurgaon, Ahmedabad, and Thane.

You can also visit our website for a chatbot that will clarify your doubts 24/7. You can subscribe to the email and receive an update from our executive.

Welcome to the world of unlimited potential with Artificial Learning. Get busy creating!

The career path of a supply chain manager

Posted on August 11, 2022March 28, 2024 by Imarticus Learning

The career path of a supply chain manager

Supply chain managers are in charge of creating and maintaining the supply chain for their company. They also ensure everything runs smoothly, from manufacturing to delivery. They’re responsible for ensuring that all the parts come together when needed and your supply chain is functioning correctly.

What does a supply chain manager do?

A supply chain manager manages the logistics of a company’s supply chain. They oversee all aspects of the process, including planning, purchasing, storing, and transporting products to ensure they’ve been received and distributed correctly.

Supply chain management is the systematic process of designing, implementing, and improving the supply chain. Supply chain managers are responsible for the suppliers and forecasts behind your company’s material and information flow.

You may be wondering what precisely a supply chain manager does. The role has been growing in recent years, and it’s not just about ensuring your company has enough materials to keep its factories running smoothly. It also involves managing relationships with suppliers, customers, and other stakeholders, understanding how various parts of the supply chain work together, and ensuring that you’re getting the best possible price for goods or services.

Critical skills for supply chain managers

Analytical skills: A good supply chain manager can analyze the data and information their team provides.
Communication skills: This person must communicate effectively with other departments and stakeholders to get things done.
Problem-solving skills: A good supply chain manager will have an eye for details that help them find solutions to problems quickly and efficiently.

Salary and benefits for supply chain managers

Supply chain managers can expect an average salary of $87,000 per year. The pay scale is relatively standardized, and organizations typically offer some benefits packages to employees in this position. When negotiating your salary with employers, remember that what matters most when discussing compensation is how much value your skills add towards their bottom line goals—not just how much money they want from each employee every week (or month). It’s also essential to consider costs associated with living expenses and taxes, which could affect salaries depending on where employees live!

So, what are you waiting for? Become a supply chain manager and help your business operate more efficiently.

Discover a Career in Supply chain analytics with Imarticus Learning

Managers might use a supply chain management certification course to make strategic, operational, and tactical decisions. By combining conventional supply chain planning with data-driven decision-making, get ready to contribute to developing more tactical and inventive global supply chains in the future.

Course Benefits For Learners:

Students are exposed to significant technologies, including six real-world projects, to give them a thorough grasp of the industry and prepare them for a successful career.
Learners may get ready for highly sought-after jobs like demand planners or data scientists by finishing a supply chain management and analytics degree!
Python will teach aspirants to become data-centric and enhance supply chain decision-making.

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

SQL concepts you must read before going for a data scientist interview

Posted on August 11, 2022March 28, 2024 by Imarticus Learning

SQL concepts you must read before going for a data scientist interview

Data science is one of the most in-demand professions, and everyone has been trying to get a job in this field. But before you go for the interview, it’s always good to have an idea about the concept and things related to data science. So here, we will discuss some data science interview questions.

What is the difference between MySQL and SQL?

SQL, or Structured Query Language, is used to create and manipulate databases. It can be considered a programming language that allows you to write queries and get results from them.

MySQL is an open-source database management system. It’s an RDBMS (Relational Database Management System), which stores data in tables rather than files or memory buffers like other DBMSs do.

What is a Database Management System (DBMS)?

A database management system is a program that allows you to store, organize and retrieve data on a computer. It’s a collection of programs that manages the database.

Explain SQL.

SQL is a database management language. It creates, modifies, and queries databases. It is a declarative language that allows you to create and manipulate tables in your database using commands like CREATE, INSERT, and UPDATE.

What is an Index?

It is a data structure that makes finding information faster. The index stores the same information as the original table but can be searched much faster because of its optimized system.

What is a Foreign Key? Demonstrate How to Implement it

It is a set of columns that refer to a primary key in another table. It enforces referential integrity and ensures that data from the parent table is related to the child table.

Assume you have a database with one customer row per person and their orders (a list of products bought by each customer). You want to add some additional information about each order, such as when it gets placed, how much it costs, etc., which means you need another table called “Orders” with four fields – date_of_order (date), product_name(product), quantity(quantity) and price($).

What is the Difference Between DML and DDL?

Data Definition Language (DDL) is a programming language that enables users to define database data structures. It also allows you to create new tables or insert data into existing ones.

Data Manipulation Language (DML) is another programming language used by database administrators and developers who work on relational databases like Oracle or MySQL, which store information in tables with columns and rows.

The difference lies in how they work together. While DBAs use DMLs for manipulating your database’s contents using SQL statements, developers use DDLs for creating/updating them using SQL statements too!

Discover a career in data science with Imarticus Learning

Course Benefits for Students:

Students will be familiar with data analytics, machine learning basics, and the most extensively used data science tools and methodologies.
To get a data analyst certification course, students must complete 25 real-world projects and case studies led by business partners.
The ability to display data using a data analytics tool is one of the most sought-after skills in the industry today. As a result, new graduates and those just beginning their jobs may want to consider enrolling.

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

How IIT Roorkee is creating a mark in the data science and machine learning industry

Posted on August 10, 2022August 10, 2022 by Imarticus Learning

How IIT Roorkee is creating a mark in the data science and machine learning industry

India’s data science and machine learning industry is proliferating, fueled by the digital revolution. With the country witnessing a digital transformation, the demand for data analysts and software developers in India has proliferated over the past few years.

Several global corporations like Microsoft, Google, Amazon, Facebook, and Twitter also have their R&D centres in India to tap into their talented workforce. The country has seen several prominent players emerge in the last two years, focusing on building world-class ML projects.

Why IIT Roorkee?

IIT Roorkee offers a two-year program aimed at helping students and researchers with AI and ML expertise to transition into corporate jobs. The program also seeks to create a pool of future talent for the Indian data science and AI ecosystem by connecting top research institutes, academia, and corporate partners.

It has been designed for researchers, academicians, and industry partners to realize their AI and ML aspirations through research and project collaboration. It also aims to build a talent pipeline for the industry.

Program participants create their projects based on their specific expertise and can also work on projects proposed by corporate partners. The program is supported by academic experts, technopreneurs, corporates, and investors. Participants can apply for the program through an online application process.

Why Build A Data Science And Machine Learning Centre?

Roorkee’s approach to AI and ML Development is one of the first Indian institutes to create a Centre for AI and ML Development. This decision to focus on artificial intelligence and machine learning was based on the need to prepare the country’s talent for an “AI-powered” future.

The vision is to become a world-class AI & ML research, training, and entrepreneurship centre. AI is a set of computer technologies that lets machines learn how to perform tasks, process data, and make decisions. It is also known as strong artificial intelligence (AI). ML studies how to automatically build systems that use AI to learn and improve over time.

Roorkee has also started an AI & ML development centre focusing on developing a strong talent pool in the country and building a robust ecosystem of AI & ML startups.

Major Projects at IIT Roorkee

Some of the achievements from IIT Roorkee that have left an impression on its contemporaries include successful projects like the development of large-scale deep learning models for Breast Cancer Detection at a Multi-Institutional Collaboration Project and improvement over other research institutions such as Google Brain’s AlphaGo Zero result. Apart from traditional academic research, this Institute has also been involved in industry collaborations and has developed innovative products such as the IIT-developed speech recognition algorithm for Google Assistant.

Since its inception, IIT Roorkee has always strived to create an environment where students can develop their skills in cutting-edge research areas. This is done by providing a supportive infrastructure and encouraging interactions with industry partners. Several programs at this Institute are designed to help students get hands-on experience with real-world problems and solutions related to data science and machine learning. For instance, the mentor program pairs experienced professionals from various industries with bright college students for project guidance.

With an approach to a research-based, collaborative and integrative research model, the programme focuses on core research areas, including natural language processing (NLP), computer vision, and reinforcement learning. The programme helps participants transition from research to product development in a short time through a three-month boot camp and six-month programme.

They conduct workshops, lectures, and hands-on classes to help participants understand their research domain’s fundamental concepts and technologies. It also provides mentorship and guidance to help participants build a strong research team and business model. The Institute also provides support through research publications, grants, and internships.

Conclusion

With the demand for data scientists and machine learning experts rising rapidly in India, the country is facing a significant problem in finding such talent. This is where IIT Roorkee, with its innovative approach to AI and ML development, comes into the picture.

Over the last few years, the Indian Institute of Technology (IIT) Roorkee has emerged as one of the leading institutions in India for data science and machine learning research. The Institute facilitates research and development by building a talent pool in AI and ML. It is finding data scientists and machine learning experts, thus relieving this country of a major problem.

Think You’re Cut Out to Do a PG in Machine Learning? Read On

Posted on August 10, 2022March 28, 2024 by Imarticus Learning

Think You’re Cut Out to Do a PG in Machine Learning? Read On

Are you intrigued by the concept of self-driving vehicles? Do you find your life made easier with voice assistants? Do you find your Netflix recommendations helpful in technology? If you’re eager to learn about the principles that drive such technologies, a degree in Machine Learning or Data Science is the right choice for you.

Machine Learning, a sub-topic under the umbrella of Artificial Intelligence, was introduced in the mid-20th century. It was followed by the invention of the Turing Machine in the year 1950 to examine the intelligence of computers. Harboring a career in these domains has become a popular choice for tech enthusiasts with the increasing amount of Big Data and the general Industry 4.0 requirements of Artificial Intelligence and Machine Learning technologies.

Although having a bachelor’s degree in a related specialisation would aid in learning further, you can still prepare yourself for the upcoming advancements in Data Analytics and Machine Learning.

If you are looking for a holistic course, which can help you chart out a robust Machine Learning Career, then you must check out our Postgraduate Program in Data Analytics and Machine Learning developed by industry experts.

Our Data Analytics Course, equipped with Machine Learning, offers an optimal mix of various algorithms and techniques. Completing a postgraduation in this field prepares you for viable job opportunities in government and private organisations for roles like Machine Learning Engineer, Data Analyst, Data Scientist, Data Engineer, AI Engineer, Computer Vision Engineer, and more. It has been statistically predicted that the field of Data Science will be the fastest-progressing sector in the coming decade.

What Skills Do You Need to Study Machine Learning?

The learning path towards a Machine Learning career should provide great knowledge about these essential skills that make you job-ready –

Programming Skills – Preferably in Python or R, understanding and creating models using different algorithms account for the basic practice of Machine Learning professionals. The coding skills make working on real-world challenges possible.
Data Analysis and Visualization – Data is a very valuable resource and nearly all companies today rely on data and business analytics for better organisational design, increased revenue, and streamlined productivity.
Statistical Modeling – Most industries generate numerical or textual data in great proportions. Discovering the logic hidden inside that information is only possible through formulations of applied mathematics and statistics. The math behind Machine Learning models is what fosters better decision-making rules.

Why is Data Analytics and Machine Learning A Booming Field?

One of the major advantages of studying Machine Learning is that it enables you to understand the world more closely and identify the impacts of Artificial Intelligence in this digital era. You would be astonished to know how deeply we are surrounded by such technologies. From the personalised ads you see on YouTube to Spotify’s song recommendations, from the auto-pilot mode of Tesla to robotic surgeries, it is all Machine Learning.

Machine Learning complements the analysis of large amounts of data. A degree in the field will help you to identify hidden patterns and insights from data that would not make sense to humans in their raw format. However, feeding that data to machine learning models might flip the existing perspectives, providing another great advantage for tech and business advancements.

A PG in Machine Learning is the most advanced stage of deep research, where one can learn to create complex Machine Learning models and solve complex problems in finance, healthcare, education, or manufacturing.

Conclusion

Machine Learning and Data Analytics have become the driving forces for all sorts of decision-making processes across businesses. All these skills require you to work on projects that have data at their core, which can be extracted and recorded in various formats – tabular, numerical, pictorial, graphical, etc. Data is being generated in every business, ranging from small startups to large multinational corporations. And machine learning is the tool that helps make sense of this pool of big data.

If you are searching for a comprehensive curriculum to begin or advance your Machine Learning journey, our PG course in the field of Data Analytics and Machine Learning is the ideal choice. Whether you are a beginner, who has just started to learn Artificial Intelligence and Machine Learning, or an expert in the field, completing a Postgraduate certification course will improve your job opportunities and/or growth significantly.

For more detailed information about the course or the career prospects in the field, feel free to contact us through chat support or visit our nearest training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, and Ahmedabad.