Contact Us
×

Category: Analytics

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

Posted on 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 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 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. 

corporate training programs

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 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

data science career 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.

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

Posted on 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 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.

best data analytics certification course

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.

 

The Perfect Guide To Understanding The Data Science Career Path

Posted on by Imarticus Learning

The Perfect Guide To Understanding The Data Science Career Path

India is rising and shining brightly when it comes to adopting new and emerging technology. Almost every significant industry segment recruits data science specialists to help them gain meaningful insights from massive data. The analytics sector has seen considerable demand for highly qualified employees who understand business and technology. Organizations nowadays are always on the hunt for specialists who can cover this ever-growing talent gap.

What is data science?

To develop insights from data, data scientists mix probability, statistics, and machine learning with domain expertise. These insights range from forecasting outcomes and trends to displaying linkages and patterns.

Data science impacts practically everything we encounter, from tailored playlists to shopping recommendations to illness diagnoses. Data scientists are also pioneers in developing self-driving vehicles, chatbots, and our data-driven environment.

A Career Path of Data Science Professional

Many data scientists have difficulty locating data science profiles and determining whether their skills match the job description. Because this is a relatively new industry, most organizations are imaginative regarding titles and career routes. This is also since these titles have no apparent precedent. Data science careers are expanding rapidly, with numerous vacancies across all industries. 

How do you begin a career in data science?

    1. Get educated – A good data scientist must have a solid math and statistics foundation. Getting extra education is essential if you’re not strong in these areas.
    2. Start playing with data – Use publicly available data sets to practice your data wrangling, analysis, and visualization skills.
    3. Get involved in the community – The data science community is vibrant and supportive. There are many online forums where you can ask questions and get advice from experienced data scientists. Community involvement will help you learn and grow in your career.
    4. Find a mentor – A mentor can be a great asset in your data science journey. Find someone experienced in the field who can help guide you as you learn and grow in your career.
    5. Keep learning – As a data scientist, you must continuously learn new techniques and tools. Many excellent resources are available, such as online courses, books, and blog posts.

Explore a data science career with Imarticus Learning

Students may start in data science and machine learning with this certificate program. Students will master the fundamentals of data science and machine learning through this curriculum, developed in partnership with iHUB DivyaSampark @IIT Roorkee, and acquire the knowledge and abilities they need to apply these concepts to problems in the real world.

Course Benefits For Learners:

  • This five-month program, developed by renowned IIT faculty members, will instruct students in using Python to comprehend data mining and machine learning methodologies.
  • The data science course will be live via online sessions with India’s best educators.
  • With the help of this data science online training, students will be able to develop a solid foundation in data science.

Machine Learning: An overview, trends and careers

Posted on by Imarticus Learning

Machine Learning: An overview, trends and careers

If you’re looking for an exciting, challenging, secure, and successful future, then you can consider choosing a machine learning career. And if you don’t already know, it was recently declared one of the most sought-after AI jobs, with rapid digitalization and a greater focus on advanced fields like machine learning and artificial intelligence. 

In the past four years, machine learning and AI jobs have increased by a whopping 75% and are continuously growing. This indicates that working in a machine learning job can help you secure your future and earn your dream salary by serving an industry that is increasing in demand. In this article, we will discuss what machine learning is, and how you can build a successful career in this field. Read on! 

What is Machine Learning?

In simplest terms, machine learning is a field of AI. It helps in building self-learning automatic systems that can enhance their performance with their experience and without any human intervention. This allows machines to make data-centric decisions. Whatever a machine learns from its experience and available data, it can be used for making predictions. For instance, if you have used Google maps, then you might have noticed that sometimes it shows the fastest route with less congestion and traffic. It is able to do so with the help of machine learning algorithms. 

Machine learning engineers build these algorithms in such a way that they get used to experiencing and exploring fresh data for making predictions. This quality of machine learning provides businesses and organizations with the ability to make better strategies and optimize their operations to grow and succeed in their respective industry. 

What Does a Machine Learning Career Path Look Like? 

A career in machine learning usually begins with a post of machine learning engineer. A machine learning engineer builds solutions and applications that automate tasks that are previously handled manually. Most of these are repetitive tasks that are based on specific action pairs and conditions — which a machine can perform efficiently without any error. 

Once you earn a promotion as a Machine Learning engineer, you become a machine learning architect. Individuals in this job are responsible for creating applications and prototypes that need development. Some other job roles available in the field are ML software engineer, ML data scientist, ML senior architect, and so on. 

What Skills Do You Need for Machine Learning? 

Given below are some ML areas as well as skills required by the professionals:

Statistics and Probability 

A majority of machine learning algorithms have their base in mathematical concepts like Markov models, Bayes theorem, and a few other areas of probability. Furthermore, concepts like mean, deviation, median, and Poisson distribution are also very important in ML. 

System Design

Machine learning solutions are not generally standalone in nature. Instead, they are an important part of an integrated technical economy. This is the reason machine learning professionals have a good knowledge and understanding of software design. 

ML Algorithms and Libraries

ML professionals swear by models like Bagging, Linear Regression, Boosting, and Genetic Algorithms. 

Data Modeling

As a machine learning enthusiast, you should be able to evaluate the structure of datasets in order to identify patterns, correlations, and clusters. Further, data modeling is also necessary to make sure that data models are on point. Moreover, ML practitioners should also know how to test data for its accuracy and integrity. 

Programming Languages

Finally, if you want to pursue a machine learning career then you should have great proficiency in programming languages. Note that Python is the most important programming language for machine learning. Besides, technologies like Apache Spark, SAS, and AWS, are also crucial in ML. 

Know that this isn’t the list of only skills you need to acquire to have a career in machine learning. There are several other concepts and modules that you should learn to become an ML professional. The best way to begin your career in this field is to learn machine learning by enrolling in the right machine learning course. Further, you can also consider taking a machine learning certification program from a reputed institute. 

Scope and Salary Trends of Machine Learning 

As compared to other career options, the scope and demand for Machine Learning are very high in India as well as abroad. According to a Gartner survey, there will be more than 2.3 million jobs in the field of AI and ML by the end of 2022. 

Moreover, ML jobs offer a much higher salary than other jobs. As per the Forbes report, the average salary of an entry-level ML professional is $99,007 in the US. This converts to INR 865,257 in India. 

As you can see, machine learning is a booming career field that can help you build a successful and secure future. So, don’t wait anymore and start your career in this lucrative field by taking the right machine learning course! 

Hadoop over the years: An overview

Posted on by Imarticus Learning

Hadoop over the years: An overview

Hadoop is a large software system used to manage data in distributed systems. It originated at the University of California, Berkeley, and was developed as open-source software. Hadoop has been widely used in various industries including finance, media, retailing, and manufacturing for a long time.

The key features of Hadoop are its distributed architecture (it uses Distributed File System or HDFS), parallel processing capabilities (via MapReduce), and ability to process large amounts of data quickly. This enables users to analyze big data sets using a variety of query languages such as Hive or Pig. Hadoop is commonly used in conjunction with other open-source software, such as Apache Spark.

In its early years, Hadoop was limited to working with files that were stored on local disk drives or within web services. This meant that many tasks involving Hadoop could not be completed without additional storage resources being added to the system.

As more companies began to learn Hadoop for their own purposes, it became clear that this technology had an enormous amount of untapped potential. In 2008, Google developed MapReduce, which allowed users to use Hadoop without having to worry about managing any additional infrastructure or software components themselves. This helped make Hadoop much more accessible to small businesses as well as large corporations—and it also made it easier for these organizations to store their valuable data in one place rather than on multiple servers across an entire organization’s network space.

Hadoop, over time, has become more efficient, and this evolution is completely technology-driven.

Hadoop has progressed significantly in recent times through its advancing technology and today, there are many ways to use Hadoop in your organization and business model. For example, you can run MapReduce jobs on top of HDFS (Hadoop Distributed File System) or S3 (Simple Storage Service). These nodes can be either standalone machines or cloud instances running in Amazon’s AWS EC2 service or Microsoft Azure cloud environment, respectively.

You can also run Hive over HDFS by using Apache Hive instead of using Pig as an alternative implementation on top of HDFS. In fact, Pig was originally developed as an alternative implementation

Hadoop is now a developed distributed storage and processing platform. It helps you store, manage, and analyze large amounts of data while allowing you to work on multiple tasks at once. Some of its features include:

– Distributed computing: Hadoop can be used across many machines in a network, distributing the work across each machine’s resources to increase throughput and minimize latency

– MapReduce: MapReduce allows you to analyze large datasets using an efficient programming model that can process data in parallel and run without user intervention

– Parsing and text analysis: Hadoop lets you parse text files quickly with regex expressions or a Java API, then analyzes them for sentiment analysis and sentiment classification

– Machine learning: With Hadoop’s support for Apache Mahout, machine learning can be performed on the distributed filesystem with no need for additional

infrastructure

Importance of Hadoop in today’s world

Hadoop is commonly used in a number of industries, including manufacturing, finance, and retail. Its capabilities make it an excellent tool for managing large data sets and mining information from them. Hadoop’s versatility makes it suitable for a wide variety of applications.

It’s popular in the world of machine learning, data-driven business analytics, and digital marketing. Hadoop allows you to efficiently manage huge volumes of unstructured and semi-structured information by allowing for parallel processing on clusters of computers.

Why should you learn Hadoop?

There are a number of reasons why you might want to learn Hadoop. Perhaps you are interested in using big data to improve your business operations or to conduct a research project. However you use it, it is extremely worthwhile for you to learn Hadoop.

Hadoop is an open-source platform for managing and processing large data sets. It enables you to easily query and analyze massive data sets using simple programming languages. This makes it a powerful tool for you to explore complex patterns, predict future trends, and more.

In addition to its big data capabilities, Hadoop also offers robust security features. You can protect your data against unauthorized access or destruction, while also maintaining control over who has access to it. This makes Hadoop a powerful tool to help you safeguard sensitive information.

If you’re interested in learning more about Hadoop, be sure to check out the following link and learn how to become a data analyst: Imarticus learning offers a data analytics certification course with a placement that takes you through every concept to help for a successful career transition.

Book a call today or visit our offline training centers for a fulfilling experience.

Why you should learn Artificial Intelligence and Machine Learning from an IIT.

Posted on by Imarticus Learning

Why you should learn Artificial Intelligence and Machine Learning from an IIT

The Indian Institutes of Technology (IITs) are globally renowned for their academic excellence. IITs have been at the forefront of research in various fields, including artificial intelligence and machine learning. As two of the hottest topics in the tech world today, there are only a few better places to learn about the subject than IIT. 

analytics and data science jobs

If you’re looking for an artificial intelligence course or a machine learning certification, this article will help you decide.

We’ll look at five reasons you should learn artificial intelligence and machine learning from IIT.

 

  • Course Curriculum 

 

The course curriculum at IIT offers a unique blend of theory and practice, which is essential for mastering cutting-edge technologies. It aims to provide students with a comprehensive understanding of AI and ML.

Combining detailed knowledge of machine learning, deep learning, and artificial intelligence with general computer science principles makes this possible. By doing this, students receive a well-rounded education. 

In addition to offering an academic curriculum, students are also allowed to apply their knowledge in real-world scenarios through mentorship and industry-led internships. This will enable them to build an impressive portfolio of AI and ML projects for future employers. 

Students get the opportunity to learn from AI leaders while developing their skills and experience.

 

  • World-class faculty

 

IIT’s faculty are some of the best in their fields, with extensive experience in academia and industry. Their knowledge and expertise are unrivaled, and they are passionate about teaching and helping students succeed. 

With a commitment to excellence, the IIT faculty are dedicated to helping students reach their full potential. This makes them uniquely qualified to provide students with the skills and knowledge they need to succeed in today’s competitive marketplace. 

But that’s not all.

In addition to academic professors’ sessions, industry experts will teach you real-world applications of machine learning, deep learning, and artificial intelligence.

 

  • Network

 

IIT provides an ideal environment for collaborative learning, with ample opportunities to network with like-minded individuals from all over the world.

The student population is highly diverse, and the faculty is committed to providing a supportive and stimulating environment. The environment is ideal for networking and sharing ideas. There are many opportunities to learn new things and grow as a person.

Moreover, building a strong network opens up the potential for good placement opportunities. 

 

  • Alumni track record 

 

IIT is known for its rigorous academic program and its commitment to excellence. The school has a long history of producing top-notch talent in all fields, and AI and ML are no exceptions.

You can check Imarticus Learning’s AI and ML course in collaboration with IIT Guwahati. Alumni from this course have gone on to work in senior management positions in brands like GitHub, ANZ, JP Morgan, Cognizant, Oracle, and Deloitte, to name a few. 

 

  • Brand value

 

IITs are located in India, a country with a rapidly growing economy and a large pool of talented engineers and scientists.

As one of the country’s leading artificial intelligence and machine learning research institutions, the institute has a long history of excellence in these fields.

IIT students have access to world-class facilities and the latest technologies and techniques. It is also a leader in education, training the next generation of AI and ML researchers. A certification endorsed by one of India’s most prestigious academic collaborations will impress employers and showcase your AI skills.

Conclusion

Artificial intelligence and machine learning are two of the hottest topics in the tech industry today. 

One way to make your mark in this field is to become certified by a reputable institute, either through an artificial intelligence course or a machine learning certification. 

Fortunately, if you’re studying at the Indian Institute of Technology, you’re in a great position to do so. 

IIT is home to some of the world’s leading experts in AI and ML, so you’ll have access to the latest technologies and techniques. Plus, by working on projects with other students, you’ll be able to develop a strong network of contacts in the industry and build a portfolio that your employers will appreciate. 

You can check out the artificial intelligence and machine learning course offered by Imarticus in collaboration with IIT Guwahati. You can learn more about the program by reaching out through chat support or by visiting one of their training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.