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5 Impressive Quora Questions On Data Analytics

Posted on by Imarticus Learning

5 Impressive Quora Questions On Data Analytics

Data analysis is becoming a highly sought-after career path both in and outside of India. Data is an asset, as the saying goes in modern society. Every enterprise, regardless of size, heavily relies on data.

For instance, ABC is a clothing-related manufacturing business. While the business in Arunachal Pradesh was shrinking in 2020, ABC made enormous profits in West Bengal. The conclusion that was reached above rests on a solid foundation of data analysis. What actual figures pertain if West Bengal has been a prosperous market for ABC? Which products are less popular and which ones are in high demand? It’s all based on available data.

Likewise, exact amounts and figures should be presented if Arunachal Pradesh proved to be a dubious market for ABC. A data analyst’s responsibility is to compile a thorough report of the information and keep it in the database for future use.

What is Data Analytics?

Data analysis is a field that encompasses anything and everything related to data. From management to storage, a data analyst helps an organization create a voluminous database for frequent referencing. The advent of newer technologies makes this field even more exciting.  

Don’t we all know what “Big Data” implies? Large volumes of unstructured and structured data comprise “big data.” In simpler words, big data is a combination of data that varies in complexity, volume,  and mobility. Data analysts are responsible for handling and managing massive amounts of data.

5 Impressive Quora Questions On Data Analytics

People are curious about data analytics. Particularly the tech-savvy generation is relying highly on this stream as a lucrative career choice. Thus, it is no wonder that you will come across numerous queries online regarding data analytics. Some of the common questions are answered below. 

Is Data Analytics a good career choice?

The field of data analysis is constantly expanding, and new technology is being introduced on a regular basis. The data analysts’ repertoire has been expanded with new equipment and tools. Particularly since AI technologies emerged, there have been many job prospects for data analysts that promise good pay.

How can I start a career in Data Analytics?

Before you ponder about the best data analytics certification courses, let us be clear that you should focus more on the long-term outcomes. If you go through the grinding of the conventional undergraduate/ postgraduate/ diploma course on data analytics, you will be favored higher by the recruiters. Aim to join trusted institutions like Imarticus and undertake proper training. This will prepare you for the upcoming days when you may be working with leading companies like Infosys, HSBC, Standard Chartered, Deloitte, and many more.    

What are key areas of employment for a Data Analyst?

Business management,  quantitative data analysis, data management, big data data management, predictive data analysis, and business analytics are just a few of the domains where data analytics has a bright potential. One of your primary duties as a data analyst will be to turn raw data into a structured compilation of insights that a company can use to refer to. Data analysis is necessary for all industries, including sports and education. Therefore, you can enjoy seamless opportunities if you learn data analytics from an esteemed institution. 

How Data Analytics is the future of IT?

Data analysis offers you chances you could never have imagined. One of the most pervasive myths regarding data analysis is that it is considered to be the new big thing. Data analysis is already here, not just in the future. Since the 1990s, when the value of data analytics in organizations was discovered, a large number of companies have benefited greatly from it. Data analytics is the most scientific method of business analysis, and decisions for the company’s profit can be made based on the technical research of a data analyst.  

Is there any scope for Data Analysts outside India?

Data analysis is now a popular career option both in and out of India. As the saying goes, data is a valuable treasure. Each business, no matter how big or small needs data. Western countries depend highly on the mechanical interpretation of data and thus a thorough analysis is an integral part of their life. You will often hear about mass recruitment happening in India where international MNCs and enterprises are hiring competent data analysts with handsome salaries. 

Best Data Analytics Certification Course

Imarticus is among the leading institutions that offer the best data analytics certification course. You will incur in-depth knowledge from the veteran tutors. Special care will be taken to make you absolutely job-ready. Complete a postgraduate program in data analytics today and become a highly sought-after professional tomorrow.  

Data Analytics Online Training

It is no secret that data drives today’s commercial sector. You can learn everything there is to know about Data Management, Data Integration, Governance, and Data Quality Control with data analytics online training. 

The top analysts in the country work in a specialized area of data analytics called data visualization. If you want to have a safe and wealthy future, learn data analytics today. It will help you grab the greatest career opportunities as a data analyst. 

Data science and machine learning professionals are career optimistic – The statistics show why.

Posted on by Imarticus Learning

Data science and machine learning professionals are career optimistic – The statistics show why.

Advanced technologies like artificial intelligence and machine learning have grown rapidly in recent years. They are expected to grow further in the upcoming years at the same lightning speed.

As per a forecast, the artificial intelligence market is expected to grow at a Compounded Annual Growth Rate (CAGR) of thirty-eight percent from 2022 to 2030. The adoption of artificial intelligence and machine learning can be seen across various sectors like healthcare, finance, automobile, and finance, to mention a few.

This will give rise to the demand for data science and machine learning professionals in various job roles across these sectors. Individuals having the skills and expertise in artificial intelligence and machine learning will be recruited from the junior-most to the senior-most levels on a large scale.

Job Roles Available for Data Science and Machine Learning Professionals

As stated earlier, there is a myriad of job roles available for data science and machine learning professionals in various industries. Some of the job roles include:

  • Machine Learning Engineer
  • Business Intelligence Developer
  • Software Developer
  • Natural Language Processing (NLP) scientist
  • Computational Linguist
  • Data Scientist
  • Data Engineer
  • Marketing Analyst
  • Business IT Analyst
  • Data Architect

Why Data Science and Machine Learning Professionals Are Optimistic

We are living in a world of big data. The amount of data produced is increasing with each passing day. It is estimated that the volume of global data will reach 180 zettabytes by 2025. There will be a huge demand for professionals who can handle, manage, and convert this huge volume of data to derive actionable insights that can help businesses enhance and expand their operations.

As per a report, there were over one lakh job opportunities in the data science domain in India in June 2021. Data science jobs witnessed a forty-seven percent increase in requirements in 2021 compared to 2020. This is despite the COVID-19 scenario.

Another report has monitored the continuous rise of artificial intelligence and machine learning. It found out that data science jobs have witnessed a tremendous six hundred and fifty percent growth since 2012. The rise is set to continue in future years. It is estimated that the growth of data science will create more than eleven million job openings in the field by 2026.

These trends, therefore, indicate that now is an opportune time to start a career in data science. Thus, you will be required to acquire the requisite knowledge, expertise, and skills in artificial intelligence and machine learning domains.

Benefits of Choosing a Career in Data Science and Machine Learning

So, why choose data science as a career option? Let’s look at some of the major benefits of being a data science and machine learning professional.

  • Ever-Increasing Demand

As stated earlier, the demand for data science, artificial intelligence, and machine learning professionals is only expected to increase further in the future. Thus, there will be no shortage of jobs in this field.

  • High Salaries

Data science and machine learning professionals earn handsomely, irrespective of their job position, experience, and organisation. Some of the average annual salaries in different job roles are discussed below.

Thus, we can see that data science and machine learning professionals are some of the best-paid individuals. In addition to such fat packages, they are also entitled to bonuses, incentives, paid vacations, stock options, and other perks, depending upon the organisation.

  • Versatile Field

Professionals can find job opportunities in various sectors like manufacturing, retail, eCommerce, and healthcare. They can also switch easily from one field to another if they want to explore other domains. Thus, unlike most other career paths, data science and machine learning professionals aren’t tied to one particular field.

Skills Required for Data Science and Machine Learning Professionals

To be successful, professionals need to possess certain skills that can help them excel in their work and enable them to climb the professional ladder quickly. Some of the skills include:

  • Problem-solving intuition
  • Analytical and critical thinking
  • Business sense
  • Communication
  • Mathematics and statistics
  • Programming
  • Management
  • Leadership
  • Cloud computing
  • Data visualisation
  • Calculus
  • Data wrangling
  • Machine learning
  • Deep learning
  •  DevOps
  • Business Intelligence tools

To acquire these skills, you will need to complete a certification course in artificial intelligence and machine learning. You can opt for such courses after completing your bachelor’s or master’s certification.

While there are tons of courses out there, we recommend you check out Certification in Artificial Intelligence and Machine Learning offered by E&ICT academy, IIT Guwahati. Some of the program highlights include:

  • Industry-approved curriculum
  • Real industry projects
  • Certification by IIT Guwahati
  • Live online training

The 9-month course will impart the foundational skills that can prepare you for diverse roles in the data science and machine learning domain. Individuals have landed lucrative job roles in top companies like Accenture, Wipro, HSBC, and Oracle, to name a few.

Want to learn Machine Learning IIT AI Course? Feel free to contact our chat support. Alternatively, you can also visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. We would be more than happy to serve you.

The role of Mathematics in learning Data Science

Posted on by Imarticus Learning

The role of Mathematics in learning Data Science

Advanced Mathematics is not about number crunching. It is more focused on telling the reason behind things, the systematic processes which make concepts a reality. And due to this, Mathematics plays a crucial and irreplaceable role in the field of data science.

Thus, if you aspire to learn data science to make a career in the field, you must have a strong understanding of mathematical concepts. You must be well equipped with pattern identification and designing algorithms if you look up to a data science career.

Besides defining a systematic approach, Mathematics is also necessary for learning the latest and most commonly used technologies in the field of data science, such as Machine Learning, Deep Learning, and Artificial Intelligence. This is because all these technologies derive their foundation from Mathematics.

We at Imarticus Learning offer a Certificate Program in Data Science and Machine Learning which helps you not only understand the concepts of data science but also help you build a stronghold on the mathematical concepts you will require during your data science career journey. Our course focuses on the mathematical branch of Statistics, which forms the basis of all data science tools and concepts.

Mathematical Concepts Which You Must Know As A Data Scientist

Following are some of the key mathematical concepts which you must be well versed in if you aspire to a data science career:

  • Probability

Probability refers to the mathematical concept that lets you evaluate the likelihood of an event. It comes in really handy for making future predictions based on data sets using the latest technologies like Machine Learning. As a data scientist, probability helps with the reasoning for your decision-making.

A large number of real-life data problems are solved by data scientists with the help of probability and its allied concepts like Baye’s Theorem and Theory of Central Tendency.

  • Hypothesis Testing

Hypothesis Testing refers to the statistical concept of testing a hypothesis concerning the assumptions made for a population parameter such as its mean, variance, etc. Data scientists use hypothesis testing in several real-world data problems, such as finding the average order value for an e-commerce website or how much fuel wastage is avoidable by a petrol pump.

It also allows data scientists to make reliable predictions, such as how much an investor can expect in return from a financial instrument. As an aspiring data scientist, you must clearly understand concepts like null and alternative hypotheses, p-value, test statistics, and significance levels. 

  • Linear Algebra

Data scientists use linear algebraic concepts of matrices and vectors to speed up their analysis processes. Linear Algebra also finds its basis in Machine Learning and Deep Learning. It allows you to model complex algorithms and represent complex data in a simplified manner for easy data interpretation and decision-making.

  • Calculus

Calculus plays a very fundamental role in developing forecasting models for data scientists. If you aspire to make a career in the field, you must understand how the derivatives of a function work. However, the good part is that, unlike in school and college, you need not do the algebraic calculations for calculus manually because, as a data scientist, you can use computers and other advanced technologies for solving differential equations.

  • Regression

Regression is a statistical concept that lets you estimate the relationship between various dependent and independent variables. It finds an in-depth use in the field of big data for estimating trends and forecasts. Some real-life examples in which data scientists make use of the concept of regression are the estimation of demand and supply, inventories, sales figures, etc. 

Our Certificate Program in Data Science and Machine Learning not only equips you with the above-mentioned mathematical concepts but also introduces you to the concepts of machine learning and data visualisation along with programming languages. In addition to the diversified yet focused curriculum, we also provide career services such as resume building, mock interviews, and Capstone Project. 

Take Away

Data Science is one of the most promising fields of the future regarding job prospects and career growth. And this is the reason why programs in data science certification in India are becoming highly popular. 

According to the latest Analytics India Magazine report, around 1,400 data science professionals in India earn more than Rs. 1 Crore annually! And with the advancement in technologies and the growing importance of data for analysing consumer behavior, the demand for data scientists will only grow in the coming times. 

Are you looking for some professional data science career advice? Contact us through chat support or visit our nearest training centres in Mumbai, Thane, Pune, Chennai, Bengaluru,Gurgaon and delhi.

Tips and tricks for a successful career in AI and machine learning

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Tips and tricks for a successful career in AI and machine learning

Artificial Intelligence (AI) and Machine Learning (ML) are two of the most in-demand skills in the tech industry today. And with good reason, these cutting-edge technologies are transforming how businesses operate.

Learning about these technologies is the best way to prepare and excel in this change.

So, if you’ve ever wondered about making a career in AI and ML, you’re in the right place. Here are five tips and tricks to help you succeed in this exciting field.

1. Define Your Goals and Narrow Your Focus

Do you want to become an expert in a specific area, or do you want to use these technologies to solve particular problems? 

Once you have a clear goal in mind, you can start to narrow down your focus area. For example, if you want to use ML to solve problems, you may want to focus on data mining, predictive modelling, or natural language processing. 

To become an expert in a specific area, you may want to focus on research or developing new algorithms. Whatever your goals, it is essential to choose a focus area you are passionate about to stay motivated and succeed in your AI and ML career.

2. Build A Strong Foundation

A career in AI or ML can be enriching, but it requires a strong foundation in both theoretical and practical skills. It is essential to work with data and have strong math skills.

You’ll need to understand algorithms and data structures well and experience working with large data sets. Familiarity with popular AI and ML libraries and frameworks will also be helpful. 

Plenty of resources are available online in the form of courses and in libraries to help you get started. You can also consider an AI or ML certification to dig deeper into the subject.

3. Develop A Portfolio Of Projects 

One crucial aspect of any successful career in AI and ML is having a solid portfolio of projects. This portfolio can showcase your skills and abilities to potential employers and help you land your desired jobs. 

When developing your portfolio, choose projects highlighting your strengths and showcasing your skills. If you’re starting, you may want to consider choosing smaller tasks that you can complete quickly. As you gain experience, you can add more complex projects to your portfolio.

There are a few things to keep in mind when developing your portfolio of AI and ML projects:

  • Make sure to choose projects that are interesting to you and that you can complete within a reasonable timeframe.
  • Try to choose projects that will showcase your skills in both AI and ML.
  • Don’t be afraid to ask for help from others when needed.

With these tips in mind, you’re well on your way to developing a solid portfolio of AI and ML projects.

4. Find A Mentor

Finding a mentor is critical for anyone wanting a successful career in AI and ML. 

A mentor can provide guidance, support, and advice regarding career choices and opportunities. Having a mentor can also help you stay motivated and focused on your goals. It allows you to navigate the often-complex world of AI and ML and can provide invaluable insights.

Your mentor is someone who has already made the journey you’re looking to complete. You can find your mentor in your workplace, social media platforms, communities, etc.

5. Network

In today’s competitive job market, having a solid professional network is more critical than ever. 

A strong network can provide access to mentors, colleagues, and collaborators who can help further your career in AI and ML. In addition, networking can help you find a job, get promoted, and advance your AI and ML career. 

By networking with other AI and ML experts, professionals can stay up-to-date on the latest trends and developments, share ideas and best practices, and find new opportunities.

You can get involved in the ML community, whether attending meetups or conferences or participating in online forums.

You can look for online platforms and communities to find enthusiasts like yourself and network with them.

Conclusion

The field of AI and ML is constantly evolving, so it’s essential to keep updated about these changes. 

But if you’re starting, learning the basics will require you to enrol for AI and ML certification. And if you wish to learn from the best of the best, check out Imarticus Learning’s dedicated Artificial Intelligence and Machine Learning course in collaboration with the Indian Institute of Technology.

Imarticus Learning offers chat support and has excellent training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. Please reach out for further clarity.

Imarticus in the news: Best education brand in Analytics

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Imarticus Learning in the News: Best Education Brand in Analytics

In an event ceremony organised in Delhi, Imarticus Learning was awarded the Best Education Brand in Analytics, 2022. In its 5th year, The Economic Times – Best Education Brands 2022 had the attendance of eminent dignitaries from the field of education and leadership. The guest list included personalities like Dr. Ranoj Pegu, Hon’ble Education Minister, Government of Assam; Mr. KK Aggarwal, Chairperson, National Board of Accreditation (NBA); Dr. Anil Sahasrabudhe, Chairman, All India Council for Technical Education (AICTE).

We, at Imarticus Learning, have always trusted the power of academics and education, and we are extremely thrilled to receive an award for being the best EdTech Company in analytics. Our achievements in the domain of analytics will inspire both students and new players. That will be beneficial for the collective good of society. 

How did we Achieve This Distinction? 

We have always been motivated by an innovative and collaborative spirit at Imarticus. This motivation constantly drives us to put extra effort into the development of courses of inclusive learning, which provide a great experience in person. If a student gets extra attention from the brightest minds, then they also improve their performance and become better with their skill sets.

We shall continue bringing newer and advanced concepts with the best analytics programs to our learners. We aim to become more than just the best education brand in analytics in India. Our aim is to create a platform that is accessible and helps the Indian youth to be ready for the professional field.

Mr. Nikhil Barshikar, the CEO of Imarticus, received a prestigious award at this event. He dedicated this achievement to all the students, faculty, staff, alumni, and partners of Imarticus. He thanked everyone involved for his/her unshakable loyalty and support.

This event organised by Economic Times brought together the best education brands and emphasised the importance of the role that the education sector has been playing. It has constantly been nurturing tomorrow’s leaders.

So, receiving an award as prestigious as this will only boost our confidence and prompt us to achieve greater success in the coming years.

Our Aim and Vision

India is one of the most populous countries in the world. Hence, the scope of the education sector is massive. Even though there are various prominent educational institutions in the country, they can only seat a selected few.

So, does that mean others will be deprived of a world-class education? Well, no, and the aim of Imarticus Learning is to fill that gap.

Our vision at Imarticus Learning is not just to become the best EdTech Company in India, but we strive to serve society too by providing an opportunity for everyone to access the course from leading universities and be ready for the challenges of the professional world.

Imarticus is a rare organisation that uses its aspirations to fuel the students’ ambitions by providing the highest quality of education. Our curriculum is approved by global academic institutions, and they aim to solve a problem. To elaborate, the focus here is not only on providing a course of study just to gain knowledge, but we, at Imarticus Learning, emphasise creating better professionals too who will solve critical problems in the coming days. So, our courses focus more on the application part of a subject rather than just its theoretical knowledge.

This award recognises our contributions to becoming one of the best and most reputed education brands in the country and also at an international level. That is why we are making a significant impact on the analytics sector with cutting-edge technology and a globally reputed curriculum.

What Else Happened at the Event?

The Economic Times – Best Education Brands event was a meeting and union of leading thought leaders who have been leading from the front in starting educational reforms. They have been contributing with both expertise and better financial setups in the education sector.

What’s Next?

In recent years, new and reputed brands have helped transform India into a knowledge sanctuary. They are developing individuals in the field of analytics. Analytics as education is increasingly gaining importance in the complete progress of India as a nation. The development of academic infrastructure will be the key focus in the present decade. In this situation, there will be an investment in academic infrastructure. Subsequently, the education sector will see much progress in the next ten to twenty years.

Speakers at this event also stressed the significance of encouraging pioneering institutes in the space of higher academics. An EdTech company like Imarticus Learning could help reshape the education sector and prepare the Indian youth for a fast-evolving world. 

2022 Data science job trends, careers and industry insights

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2022 Data science job trends, careers, and industry insights

Without data, everything is just an opinion. And business decisions are not made on opinion; they are made based on facts and details. This is where a data scientist enters the business realm. 

But, what is data science exactly? Well, data science is the study of large volumes of data using advanced technology and programming tools to extract meaningful information from them. These data points serve as the foundation for making both primary as well as key and strategic business decisions.

Today, data scientists are quite high in demand in the job market. This can be primarily attributed to two reasons – the growing shift of businesses to the digital space and rise of the consumer behavioral analytics. 

Suppose you also want to ride this wave of growth in the space of data analytics. In that case, you can learn data science by getting enrolled in our Certificate Program in Data Science and Machine Learning and saying yes to your data science career dreams!

Top Data Science Job Trends and Industry Insights 2022

If you aspire to make a career in the field of data science, you must keep your skill set and knowledge base updated for the following job trends in the domain –

  • Demand For Data Scientists Increased by Over 30%

The demand for data scientists in India increased by 30.1% in April 2022, as compared to the last year. With this, India’s share in the global demand for data scientists increased from 9.4% in 2021 to 11.6% in 2022.

  • BFSI Sector Emerged as the Biggest Employer for Data Scientists

In FY2022, the BFSI sector accounted for the highest demand (26.6% ) for data scientists in India, according to the latest Analytics India Magazine (AIM) report. After the BFSI sector, the e-commerce and internet space hired the largest number of data scientists in the country.

  • Bengaluru – The New Hub For Data Scientists

The city of Bengaluru created the maximum number of Data Science jobs in India in 2022, with as many as more than 51,000 positions. This can be attributed to the city’s bent on the IT sector and the presence of several emerging startups and unicorns there. After Bengaluru, Delhi-NCR registered the highest number of data science jobs.

  • Employers Prefer Engineers Turned Data Scientists

In 2022, the majority of Individuals who got hired for data science job roles belonged to the engineering stream. As high as 56% of them were engineering undergraduates, and 25.9% were engineering masters. Non-engineering undergraduates comprised 35.2% of the sphere, whereas MBAs accounted for 17.4% of the hires.

  • Most Popular Data Science Designation – Business Analyst

As many as 39% of the data science jobs which were advertised in 2022 came with the designation of ‘Business Analyst’. The second-most popular title in the space, appearing in 34.6% of the job openings, has been that of ‘Data Engineer.’

A Sneak Peek into Data Science Careers

To bag a job in the data science domain, you need to have a good mix of both technical and non-technical skills.

Top Technical Skills For Data Science Career

Today, organisations are hiring individuals who are not only good at evaluating data using basic data analytics software but who can also automate them using augmented analytics technologies like Artificial Intelligence, Machine Learning, and Natural Language Processing (NLP) for real-time insights.

You must also be well equipped with programming languages like C++, Python, R, Java, and SQL and data visualization tools like Tableau to get your desired data science job. Knowledge of platforms like Hadoop and Apache Spark is also a plus.

Top Non-Technical Skills For Data Science Career

Just being technically sound is not enough; you must also possess the following non-technical skills to make a career in the field of data science – 

  1. Analytical skills
  2. Ability to work and collaborate in a team
  3. Good communication skills to translate your understanding of data to the stakeholders

Final Words

Data Science has been touted as the future of jobs, not only in India but all over the world. 

According to the latest Mckinsey report, almost all organizations will become data-driven, becoming a default setting. This indicates that in the near future, the reliance on data and the need for data scientists will only be a steep upward curve. So, if you wish to make a career in this emerging and growing field, you must start now and get a data science certification in India.

For detailed guidance and advice on the data science course, contact us through chat support, or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

Building A Data Science Portfolio From Scratch

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Building A Data Science Portfolio From Scratch

Data Science is one of the most popular fields of work, especially among the millennials and Gen Z. But what is it exactly? Well, it is the field of study of tons of data to extract meaningful information for efficient and effective decision-making.

If you aspire to be a data scientist, it is important for you to understand two things really well. Firstly, you should be a master of your skills be it programming languages, use of statistical methods, or data visualisation, you should know all of these in and out. 

If you are looking for a short-term online course, which will help you upskill and enhance your knowledge base, come join our Certificate Program in Data Science and Machine Learning with iHUB DivyaSampark @IIT Roorkee.

Besides learning the concepts and methodologies of data science, you must also focus on building a strong portfolio of your work in the domain. Unlike management and engineering professionals, creating a resume is not enough to get your desired data science job.

You must have a strong portfolio of your projects and overall profile so that you can stand out among millions of other applicants. As part of our data science online training, we also teach you how you can build an impressive profile for yourself from scratch along with grooming you for mock interviews! So, what are you waiting for? Come join us today and take the first step toward your bright data science future.

Tips to Build An Awesome Data Science Portfolio From Scratch

Following are some of the tried and tested strategies that you can make use of to build an amazing data science portfolio – 

  • Let Your Portfolio Reflect Your True Passion

It is often said that you should fake it till you make it. But, that’s not advisable when it comes to your work portfolio. Mentioning projects and interests in your portfolio which look fancy but fail to inspire you does not help get the job you really want. 

Your portfolio must be authentic. It should capture who you want to be and the projects you like or wish to work on in the future. You can do this by walking recruiters through your journey in the field, and what inspired you to enter the data science space. 

  • Highlight Your Strong Technical Understanding

Data Science is all about how well you understand all the technical concepts and implement them to solve real-life problems. You must mention all the data science certification courses completed by you along with the projects you have worked on, highlighting the specific techniques of which you made use. 

There are two important things which you must remember in this regard. Firstly, don’t clutter your portfolio with all the ML techniques and projects which you have worked on, mention only the important ones. The second thing which you must keep in mind is that you must customize this section as per the requirements of the job you are applying for. This helps you grab the attention of the recruiter and rank among relevant profiles.

  • Show Off Your Communication Skills

In order to solve complex real-life problems as a data scientist, you must possess good communication skills so that you can effectively translate the identified data insights to the leadership so that they can make key strategic decisions. Thus, you must showcase how good you are as a communicator. 

You can do so by mentioning narratives along with your work samples. Highlighting your strong communication side also helps recruiters understand how you approach problems and infer data to solve them.

  • Limit the Length of Your Portfolio to One Page

While creating a work portfolio, think like a recruiter who has tons of applications and profiles to go through. Keep the portfolio short in length, but to the point to ease the job of the recruiter by bringing their attention to the qualities and skill set they are looking for.  While doing this, ensure that your portfolio is well organised and categorised to speed up the screening process.

Take Away

Your work portfolio is like your first impression for the recruiter who can be offering you your dream data science job. Thus, it is important to get this first impression right by creating a stunning portfolio that highlights both your technical and non-technical skills. Your portfolio should mirror your capabilities, knowledge base, and your zeal for the role. 

Still unsure how to go about it? Feel free to contact us through chat support, or just visit our nearest training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. We are always happy to help you!

Explore Machine Learning: Here’s How to Find Your Way Through the Data Science Maze

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Explore Machine Learning: Here’s How to Find Your Way Through the Data Science Maze

The term ‘Machine Learning’ was coined in 1959 by then-IBM computer scientist Arthur Samuel while designing a computer algorithm for the classic game of Checkers. Today, this term is immensely popular owing to the technology’s wide application across industries.

But what is Machine Learning or ML? It is a computational method that is used to obtain artificial intelligence by making a machine learn how to solve problems on its own rather than requiring explicit programming software. 

Machine Learning is widely used in the field of data science as it helps find the way through tons of data instantly and accurately! But how? By using statistical methods and algorithms to train computers so that they can accurately classify data sets and make reliable predictions to uncover key data insights.

Does all this sound interesting to you? Do you aspire to use advanced Machine Learning technologies to solve real-life problems and arrive at data-driven solutions? If yes, then you should check out our data science courses which are equipped with not only data mining techniques but also machine learning tools along with Python, SQL, and Tableau.

Machine Learning Concepts Which Every Data Scientist Must Know About

Data science learners must be able to develop a solid foundation and specialise in machine learning with Python for data-driven decision-making. Ultimately, you want to assist organisations to make smart decisions for growth and offer insightful data analysis.

Following are some of the key Machine Learning tools which you must know about if you are aspiring for a data science career:

  • Clustering

CLustering is the simplest unsupervised ML method that lets the algorithm define the output for mining data. The most famous clustering method is ‘K-Means’ under which the letter ‘K’ refers to the number of clusters into which the miner wants to divide the unlabelled data. 

The clustering method is used for drawing analysis in varied fields such as for creating customer segments for different marketing techniques as well as for identifying earthquake-prone areas.

  • Neural Networks

If you are interested in the Deep Learning subset of ML, then you must know Neural Networks in and out. Neural Network is a network of algorithms that identify patterns or relationships among different data points in a set in a way similar to the working of a human brain. 

It is widely used for making forecasts and improving decision-making in fields like stock market trading, medical diagnosis, etc. You can learn more about neural networks in our data science online training programs.

  • Regression

Regression is one of the fundamental supervised ML techniques which help data scientists in creating predictive models by defining a relationship between dependent and independent variables. 

There are various types of regression models, however, broadly they can be classified into three groups: Simple Linear Regression Model (SLRM), Multiple Linear Regression Model (MLRM), and Logistic Regression.

  • Natural Language Processing (NLP)

Natural Language Processing (NLP) forms the basis of Machine Learning as it trains machines to learn the language of humans. You can find some of the everyday applications of NLP in voice-controlled applications like Apple’s Siri, Google Assistant, Amazon’s Alexa, etc. NLP is also found in execution in the fields of text summarization and sentiment analysis. 

  • Ensemble Methods

The concept of the Ensemble Method is quite similar to that of assembling. For instance, if you are not happy with all the car options available in the market and wish to come up with a car design, you can assemble your favorite car parts of different cars and design a car of your choice. 

Similarly, if as a data scientist, you are not convinced with the results of different predictive models, you can combine all of them to arrive at better predictions.

  • Transfer Learning

Transfer Learning is one of the efficient ML techniques which lets you use parts of previously programmed neural nets to develop a similar model. For instance, if you are a data scientist who has developed a technique to filter different styles of men’s clothing in buckets like shirts, t-shirts, kurtas, etc., you can use parts of transfer learning to develop a mechanism that can be used for categorising women’s clothing in say, dresses, jumpsuits, tops, etc.

Takeaway

Machine Learning has become a crucial part of the data science field today, which has made the process of analysing and predicting data faster and more accurate than before. 

Be it for real-time navigation, or product recommendations, as a data scientist you will always find Machine Learning and Data Science going hand-in-hand. And the future of data science is expected to be even more promising with the advancements in ML techniques and methods.

Thinking of kickstarting your data science career? Contact us through chat support, or just visit our nearest training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon.

Our Certificate Program In Data Science And Machine Learning is created by iHUB DivyaSampark at IIT Roorkee and will instruct you on the fundamentals and features of data science and machine learning and give you the skills necessary to put these ideas into practice and apply them to real-world issues.

IIT Machine Learning: Introduction To The Machine Learning World

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Machine Learning has been a buzzword in recent years, possibly due to the large quantity of data produced by applications, the rise in processing power, and the development of better algorithms.

Machine Learning is employed everywhere, from automating monotonous operations to providing sophisticated insights; companies in every area are attempting to capitalize on it. You could already be using a gadget that makes use of it. 

Introduction to the machine learning world

You may apply machine learning in prediction systems as well. Supervised learning, reinforcement learning, and unsupervised learning are the three categories of machine learning. The computer is given a set of training data together with the intended output and subsequently learns how to produce the desired output using the training data. This process is known as supervised learning. 

When the computer gets a collection of data but not the intended result, it must learn to recognize the structure in the data on its own through unsupervised learning. Reinforcement learning is where the computer gets a set of data and a reward function, and the computer has to learn to produce the desired output to maximize the reward.

Machine learning is a powerful tool that may apply to many tasks, including predictions, voice recognition, and face and facial expression detection. 

Application of Machine Learning

 Speech recognition is the procedure of converting spoken words into text. Speech dialing, call routing, and appliance control are all examples of voice user interfaces. You may also use it for simple data entering and structuring papers.

One of the popular uses of machine learning is image recognition. It recognizes items, people, places, digital photos, etc. Facebook has an auto friend tagging recommendation option. When we submit a picture with our Facebook friends, we instantly get a tagging recommendation with their names, powered by machine learning’s face identification and recognition algorithm.

Machine learning techniques are currently widely employed in various voice recognition applications. Google Assistant, Siri, Cortana, and Alexa use speech recognition technologies to respond to spoken commands.

Machine learning is a subtype of AI that allows machines to learn from data, improve performance based on previous experiences, and make predictions. 

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Course Benefits For Learners

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  • You may impress employers and exhibit your abilities with an E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed credential.
  • This machine learning certification will assist students in obtaining lucrative professions in artificial intelligence and machine learning.

10 Beginner-Friendly Steps To Learn Machine Learning

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10 Beginner-Friendly Steps To Learn Machine Learning

Machine Learning is believed to be the future of data science. According to Forbes insights, the global Machine Learning market is valued at $21.17 billion and is expected to surpass $209.90 billion by 2029. But what is Machine Learning? 

Machine Learning is an advanced technology for making machines learn to work without direct programming or commands from humans. It uses various statistical methods and algorithms that help computers and software identify patterns and produce the desired results.

If you aspire to learn Machine Learning and explore the field of data science, you can start with the steps provided below:

Step 1: Learn Python

The first step toward mastering Machine Learning is learning a programming language to analyse data and derive meaningful insights from it. The most popular programming language in this regard is Python. 

Step 2: Sharpen Your Mathematical Skills

Brush up your mathematical and statistical concepts like probability, regression, calculus, linear algebra, and hypothesis testing. These are necessary as they come in handy for designing and understanding different algorithms and predictive models.

Step 3: Understand How Machine Learning Works

Once you have mastered a programming language and revisited mathematical concepts, you can start picking up different Machine Learning concepts. For starters, you can research the different types of Machine Learning and their applications. Essentially, there are three types of Machine Learning concepts: Unsupervised Learning, Supervised Learning, and Reinforcement Learning.

Step 4: Get Hands-on With Data Science Tools

Start learning different data science tools like the Jupyter Notebook, Anaconda, Apache Hadoop, etc. These tools teach you to create and share documents containing codes, equations, and data visualizations.

Step 5: Learn How To Design and Select Algorithms

An algorithm is a set of rules you use to process a data set. Since a data set contains a large number of data points that are varied in nature, a single algorithm cannot be used to solve it. Thus, you must know how to design diverse algorithms and select the ones that can be used for different data sets. You will acquire this skill only with practice and over time. 

Step 6: Learn Data Visualisation and Manipulation

To implement Machine Learning, you must be able to visualise data with the help of software like Tableau to make sense of it. For this, you must familiarise yourself with software like NumPy, Pandas, and Matplotlib. These tools teach you to visualise and manipulate data and extract meaningful information.

Step 7: Build Your First Machine Learning Model

Once you have mastered all the preliminary tools and software, you should devise your first Machine Learning model. You can use any online platform to create your machine learning model. 

Step 8: Tune Your ML Model

After devising your Machine Learning model, use it to train an algorithm over a data set and see how it works. Based on the results, tune it and add features that can improve its accuracy and speed. 

Step 9: Learn Deep Learning

Move on to acquire Deep Learning skills as Machine Learning works well only with small sets of data; to deal with large sets, you need to know Deep Learning. 

Step 10: Get Practical Experience

As a final step, get some hands-on experience to test your knowledge and skills. You can take up projects or join a Machine Learning internship. Practical experience will help you implement theoretical concepts and boost your confidence by providing actual results.

Take Away

Machine Learning is a rapidly evolving domain. If you aspire to make a career in Data Science and Machine Learning, it will be helpful to start as early as possible. You can either learn the fundamentals through free resources on the internet or take up paid courses to get a better understanding. 

Imarticus Learning offers a certificate program in data science and machine learning, a 5-month weekend course offering comprehensive understanding and live training facilities by the IIT faculty and industry experts. Feel free to contact us through our chat support. You can also visit your nearest training center in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

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