Machine learning is one of the fastest-growing technologies that has made lives easier with its ability to imitate human learning. It is a part of artificial intelligence that helps analyse data, build models and make forecasts. Machine learning’s popularity has spread across industries making it an integral part of most. With its ever-growing demand, professionals and students alike, seek a data science and machine learning course to build and secure a successful career in the field. 

Machine learning models are extremely useful in today’s technologically driven world. Knowledge of machine learning tools will help professionals arrange data, improve and discover new data models and create algorithms. A data science and machine learning course also allows professionals to learn data mining.

Read on to learn about the popular machine learning tools a data scientist must know about.

Machine learning tools

The following are the most popular and useful ML tools:

TensorFlow

It is one of the most extensively used open-source machine learning tools for developing deep learning models. Its popularity is because of a dynamic library, tools and resources that help deal with large amounts of data. It allows data scientists to create machine learning applications and build effective data models.

TensorFlow has the following features:

• Efficiently create and train data models
• TensorFlow.js allows users to effectively run existing models
• Possesses the advantage of distributed computing
• It can create neural networks
• Equipped with the facility of immediate iteration and constant debugging
• Training and deployment of the model in the cloud is easier

Pytorch

Fighters is an open-source machine learning tool with its foundation in the Torch library. This tool benefits machine learning with Python and C++. It allows users to have a better and more interactive interface that can be used to develop various applications.

The following are the main characteristics of Pytorch:

• The Autograde module is used to build neural networks
• It offers great flexibility and speed, which are important for researchers and data scientists
• It is well integrated with cloud platforms
• It has a dynamic computational graph which is unique in this library
• It has a hybrid front end and permits the random change of network behaviour without any lag

Google Cloud ML Engine

Google Cloud ML Engine provides training datasets making it easier to deal with huge amounts of data. This machine learning tool is the best choice where a company wants faster results and building models while dealing with data. The services of this tool permit the creation of ML models with any size and type of data.

Google Cloud ML engine has the following features:

• Provides training to build ML models, deep learning models, etc.
• Training and prediction can be used simultaneously or in a combined way
• It is highly suitable for locating clouds in a satellite image
• The library is equipped in dealing with complex models

Amazon Machine Learning (AML)

AML is exclusively developed by Amazon and provides a ton of machine learning tools. It is a cloud-based application that can build effective machine learning applications and make forecasts. It is dynamic and can integrate data from various sources 

The major characteristics of AML are enumerated as follows:

• It provides wizards and multiple visualisation tools
• It helps to identify data patterns and build mathematical data models
• It supports regression, binary and multi-class classification
• It allows users to make predictions for data models in bulk using different APIs

NET

Accord.net is an open-source machine learning tool that is specially used for scientific computing. This tool is highly used because it has image-processing features and audio libraries otherwise absent in many other tools. Another exclusive feature that this tool has is its ability to deal with statistical and mathematical learning.

Accord.net’s features are:

• It is equipped with more than 38 kernel functions
• It consists of a lot of statistical distribution, classified as a parametric and non-parametric approximation
• It is highly useful for signal processing, computer audition and vision
• It includes numerous hypothesis tests for analysing better results

Shogun

Shogun is one of the oldest open-source machine learning libraries. This tool is written in C++ and supports a variety of interfaces. The objective of Shogun is to provide solutions for regression and classification problems.

The main features of Shogun are listed below:

• It permits the use of precalculated kernels
• It is equipped with the ability of multiple kernel functionality
• It makes it very easy to process large data sets
• It allows users to develop algorithms in a variety of programming languages

Conclusion

Machine learning is an inseparable part of the corporate world, and a knowledge of machine learning tools is one of the required qualities for becoming a successful data scientist. The IIT data science course is an advanced module that will teach you everything you need to know about the best machine learning tools in the market.

If you are a tech enthusiast and want to become a data scientist, then register for the Certificate Program in Data Science and Machine Learning by IIT Roorkee and Imarticus. This course is your one-stop destination for getting all the insights on machine learning tools.

Imagine you’re an explorer, setting sail on the vast sea of data. Your compass? Data mining skills. Your treasure? Valuable insights are hidden within the data. Learning data mining isn’t just about acquiring a new skill, it’s like embarking on an exciting adventure. You’ll uncover hidden patterns and unravel the secrets buried deep within data.

The first step in this journey is understanding what data mining is. Essentially, data mining is the process of extracting valuable information from large volumes of data. It’s like panning for gold in a river of data. It’s about finding those precious nuggets of information that can help businesses make informed decisions. But, don’t worry. You won’t be left stranded on this adventure alone. There are plenty of resources to help you learn data mining. Let’s explore some of them.

What Is Data Mining?

Data mining, as the name suggests, is the process of ‘mining’ insights from large amounts of data. From predicting customer buying behaviours to detecting fraud, data mining helps businesses make informed decisions and strategies.

Books to Kickstart Your Data Mining Journey

Many beginners start their journey to learn data mining with books. They offer in-depth knowledge, real-life examples, and they cover a wide range of topics. Here are a few that could be helpful:

“Data Mining: Practical Machine Learning Tools and Techniques” by Ian H. Witten and Eibe Frank

“Data Mining: Concepts and Techniques” by Jiawei Han and Micheline Kamber

“Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management” by Gordon S. Linoff and Michael J. A. Berry

Online Courses and Tutorials

In today’s digital world, online courses are a fantastic resource. They provide you with the flexibility to learn at your own pace and often include practical projects for hands-on experience.

Websites like Coursera and edX offer a multitude of courses, both free and paid, to help you learn data mining. YouTube also houses a plethora of tutorials from channels like ‘DataCamp’, ‘Sentdex’, and ‘Siraj Raval’.

Software Tools

To become proficient in data mining, you’ll need to familiarise yourself with data mining software tools. These tools, such as RapidMiner, WEKA, and Orange, are designed to aid in the extraction of data and allow you to apply various data mining techniques.

Communities and Forums

Joining data mining communities and forums is another great way to learn and stay updated. Websites like Kaggle and GitHub have active communities. Here, people share datasets, ask questions, and discuss data mining techniques.

Podcasts and Webinars

In the digital age, podcasts and webinars have emerged as popular means of learning. They provide bite-sized information that you can consume on the go. Podcasts like “Data Skeptic”, “DataFramed”, and “Linear Digressions” regularly discuss data mining topics and feature industry experts. Webinars, on the other hand, provide a more interactive learning experience with real-time Q&A sessions.

Academic and Professional Journals

If you’re interested in the theoretical and advanced aspects of data mining, consider reading academic and professional journals. Journals like “The Data Mining Journal” and “The Journal of Big Data” publish high-quality, peer-reviewed articles that discuss the latest advancements, techniques, and case studies in data mining.

Online Coding Platforms

Getting your hands dirty with coding is an integral part of learning data mining. Online coding platforms such as Codecademy, LeetCode, and HackerRank offer practice problems and projects related to data mining. These platforms help you apply theoretical knowledge and improve your coding skills.

Blogs and Articles

There are numerous blogs and articles available on the internet that provide a wealth of information on data mining. Blogs by data science and tech companies, like ‘Towards Data Science’, ‘KDNuggets’, and ‘Analytics Vidhya’, regularly publish articles on data mining techniques, applications, and industry trends.

Free Public Datasets for Practice

Practicing with real-world datasets is an excellent way to learn data mining. Websites like Kaggle, UCI Machine Learning Repository, and Google’s Dataset Search provide free public datasets that you can use to apply data mining techniques and build projects.

Exploring Different Data Mining Techniques

Finally, as you dive deeper into data mining, you’ll encounter various techniques used in the field. Some common ones include association, clustering, classification, prediction, and sequential patterns. Each technique has its own set of rules and methodologies. For example, the association is used to find relationships between items in a large dataset.

Similarly, clustering involves grouping related data points. By learning these techniques, you’ll have a wider range of tools to solve complex data-related problems.

Remember, learning data mining is a journey. It will require time, practice, and a lot of learning. But, the rewards you’ll reap in terms of knowledge and career opportunities make it all worthwhile. So, take the first step today and embark on your path to becoming a data mining expert!

Taking the First Step in Your Data Mining Journey

Starting to learn data mining might seem daunting at first. But with the right resources and determination, you’ll soon be uncovering valuable insights from datasets. Remember, the journey of a thousand miles begins with a single step.

Whether you’re taking your first step or looking to further your data mining skills, the Certificate Program in Data Science and Machine Learning by Imarticus Learning in collaboration with Divyasampark could be an excellent option for you. With comprehensive coverage of data mining and other related fields, you’ll learn from industry experts and gain hands-on experience. So why wait? Start your data mining journey today! Check out the program here.

Companies are fixing the data scientist shortage, giving ample job opportunities

Data scientists use various scientific methods such as data wrangling, data cleaning, machine learning etc. to work with structured and unstructured data. They help organisations make better decisions by solving critical and complex problem-solving, which in turn allows companies to operate efficiently, have better market strategies and generate profitable results. 

Data scientists have become a vital part of the process, and companies have now realised that they are creating ample job opportunities to fill their shortages. People who were earlier interested in this field but couldn’t pursue it due to unstable opportunities have now started out. Finding a good data science and machine learning course in India is not as difficult as before. Educational institutions provide comprehensive data science courses, such as IIT Roorkee data science online course and various others throughout India. 

Why was there a Shortage of Data Scientists?

Quality of Skills was Compromised

The job of data scientists is to use their technical skills and communicate their findings to the clients in a comprehensive way that helps their marketing strategies to make the organisation more successful. This requires a highly skilled professional with ample knowledge of computer skills, mathematical skills and machine learning skills. Therefore, any below-the-mark candidate is not given any opportunity in any organisation. Companies found a lack of skills in the candidates, which is why not many passed the test. 

Small Businesses Couldn’t Afford Them

Data scientists were consistently in high demand. Since this profession requires a lot of professional knowledge, not many people are able to make it till the end. However, those who do, are highly demanded by high-paying companies. Well-established companies offer incredibly high salaries for data scientists. Small businesses, on the other hand, couldn’t afford them. This created a shortage of good data scientists for small-scale companies.

Frequent Upskilling is Required

Data scientists need to have the utmost knowledge about every technology functioning with its full use. Technologies undergo updates and developments as their top-most execution potential. Due to the constant modifications, data scientists must improve simultaneously as they should be able to guide these updates and navigate solutions to any potential problems. MBA is a compulsory data science and machine learning course in India, without which candidates will not be hired. Compared to other computer and mathematical professions, data scientists must be an ace in their field to be hired.

Insufficient College Courses in Data Science and Machine Learning

The profession of Data Science and Machine Learning demands excellent skills from its candidates. Good colleges offering quality education in this field were less known. With the existing online courses, students were getting well-trained in theoretical knowledge, but their practical experiences needed to be included. For such reasons, companies denied applications by most data science learning students.

Steps Taken by Companies to Fix the Data Scientist Shortage

Fixing Concrete Criteria

Unlike before, when there was no benchmark for expected skills from data scientists, the companies have now clearly set forth their demands and criteria. This helps potential students know whether they are fit for the job role. Those who lack any mentioned skill by the employer can work on them and be better prepared for the job hiring.

Offering Competitive Salaries

Most data scientists were trying to get jobs in high-paying well-established companies. Due to this, small businesses that were in dire need of these data scientists were at a disadvantage. Companies have now decided to offer competitive salaries, which will be equal in comparison to the market’s average salary for this profession. Data scientists will be willing to work in budding businesses and not run after luxurious salaries in more prominent companies.

Offering Beneficial Packages

a part from recruiting data scientists and expecting them to work tirelessly in this field, additional packages to their jobs will be provided. They will be engaged in professional tasks and pleasant initiatives, which will help them maintain healthy stability between their personal and work lives. Since their job includes most of their time sitting behind a screen and looking after the well-functioning and keeping data, this additional perk will act as a motivation. Their output productivity will also increase highly.

Providing Additional Educational Programs

Companies have now taken the initiative to run workshops and teach important programs to employees who can benefit from them. Unlike expecting perfect candidates who know everything about the job or those who lack specific criteria set by the company, they can be moulded in the right direction. Skills necessary for a particular organisation will be taught to them directly. This will increase potential candidates for the job and allow more talent for the company’s progress and succession.

Conclusion

Companies nowadays are in search of talented recruits. They are willing to hone their skills and provide an environment that will yield more profitable results for the company. However, candidates need to step up. As a data science student, you should have a certificate program in Data Science and Machine Learning. Many institutions provide quality knowledge in data science and machine learning. Therefore, efforts shouldn’t be lacking on the applicant’s part.

An IIT course that your data science career will thank you for

No doubt. Data Science is a demanding field. It’s a field that is constantly evolving, and one has to be on their toes to keep up. And if you’re not, you’ll likely find yourself being left behind. So, what can you do to ensure that you’re keeping up with the latest in data science? One way is to take an IIT course.

IIT courses are renowned for their rigor and depth of coverage. This course will cover the skills you need to master in order to be successful at solving problems, as well as allow you the opportunity to learn various techniques that build your knowledge base.

So, In this post, we’ll discuss the rising need for data science courses and the benefits of taking an IIT course.

Rising Need for Data Science Courses.

Data science has become an extremely valuable skill in the modern workplace. With companies increasingly looking to data to drive their business decisions, the demand for data scientists has skyrocketed.

However, the supply of data scientists cannot keep pace with demand. This has created a situation where there are numerous jobs available for data scientists but not enough people to fill them. The result is that companies are spending dollars on data scientist talent.

Therefore, if you’re looking to get into this field, now is the time. You must have the skills that companies are looking for. And there is no better way to acquire these skills than by taking an IIT course.

Benefits of Taking an IIT Course

Taking an IIT course will help you learn key skills and knowledge for success in data science. Here are some of the benefits:

You will learn from data science experts: IIT courses are taught by the world’s leading data science experts. This means that you will be getting the best possible education. In addition, you will also have access to state-of-the-art facilities and resources.

You will get a world-class education: IIT courses are designed to give you a world-class education. This is clear from the fact that they are recognized by employers all over the world. In addition, you will also have access to top-quality resources and facilities.

You will be prepared for a successful career: IIT courses will provide you with the required knowledge necessary to be successful in data science. Moreover, they prepare students for the challenges of a data science career. Therefore, an IIT course is the best way to get on board with data science, as companies all over are seeking people who can handle large amounts of information.

You will have access to the latest technology: Last but not least, IIT courses give students access to the latest data science technology. This ensures that you will be ahead of the curve and well-prepared for a career in this rapidly-growing field.

Learn Data Science and machine learning with Imarticus Learning.

Imarticus certificate program in Data Science and Machine Learning is offered to prepare learners for a career in the fast-growing field of data science. This curriculum will provide students with a foundation in artificial intelligence, data science, as well as machine learning.

Course Benefits For Learners:

• This course developed by IIT faculty members to aid students in understanding machine learning methodologies.
• The data science career with IIT Roorkee is promising. This course will provide you with a solid foundation in data science and machine learning.
• Our online program provides students with the opportunity to lay a solid data science foundation.

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

5 Business Skills Critical For A Data Scientist’s Career

The emergence and widespread acceptance of technology, especially internet services, has significantly impacted how businesses are run these days. The amount of data available has helped companies to dissect and analyze them to serve their consumers better. In this process, a data scientist becomes an important individual.

As a professional, a data scientist works to study and interpret that data in simpler terms to help everybody understand what it represents. Doing so helps other departments to comprehend the strengths and weaknesses of the organization or a particular product or service and plan accordingly to pave a path for future success.

Nonetheless, besides having the right technical know-how, to have a successful data science career, you need to know a few business skills as well.

5 Best Business Skills to Become a Successful Data Scientist

Business skills are primarily the soft skills that one needs to work in an organization. These skills primarily determine the type of employee one is and helps in building a perception. So, you don’t want a negative one, do you? Well, then, keep the following pointers in mind –

Finding why you have been hired

Following the completion of your data science course, you apply for a job. After getting hired, you need to understand the reason behind your appointment.

Well, yes, you know the designation you have received, but understanding the job at hand is essential to perform your duties better. Along with that, you also need to learn your company’s expectations of you.

Once you are clear of these objectives, it will give you a clear roadmap on how to work and behave. More importantly, what is the goals to fulfill during your tenure in a company?

Negotiating office politics

Another skill concerns interpersonal relations with your office colleagues. How you tackle cultural misunderstandings or how you handle disagreements, and how to deal with office politics. Although young data scientists neglect these soft skills, you need to take them seriously. These are some small aspects that can have a significant effect on your career. Here your technical expertise does not matter. What matters is your presence of mind in various tricky situations.

How to communicate effectively

It is an extremely trivial skill, but it is the most important of all business skills. You should be crystal clear in communicating your messages with other parts of the team. It will also help you to deliver presentations effectively. Top experts in the field of data science have the knowledge to produce statistics that deliver the inference to the spectators. Communication is easy to learn, and mastering it might help you go a long way.

How to set project objectives

If you get the responsibility of handling projects, then you will need to master the art of setting goals and managing the expectations of the team and stakeholders. It will ultimately help you in starting a project and completing it successfully. This will help you win the trust of people in the organization and rise high in your career.

Delivering project goals while handling your career

The core of your technical skills acquired in a data science online training program depends upon your understanding and utilization of some key concepts and data frameworks developed by software developers like agile or scrum, ML ops, and Jira boards. Sticking to these concepts, you will be able to steer towards your goal despite variable expectations and the absence of clarity in a data science project. Mastering these will help you in choosing between various job opportunities in the future. It will also help you strengthen your CV. You could even work independently or handle a freelance career.

Final Words

Becoming a data scientist is not a tricky job, with various data science courses available online from education institutions like Imarticus. However, these business skills, or soft skills as they are called, should be cultivated by you. So, to sum up, take good care of this side of your professional life as it will make a similar impact on your career as securing a great grade in a data science online training.