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Tag: best data analytics certification course

Machine Learning A-Z: Hands-on Python and R in Data science

Posted on by Imarticus Learning

R and Python are both equally great programming languages. However, each has its own set of advantages that it offers to the user. For example, when we are talking about development processes or IT operations, Python is always a better option. But when it comes to statistical tasks or analytics, R can prove to be a much more suitable alternative.

This is because R has been created for Statisticians and for statistical projects. Skilled programmers can, however, employ any of the two languages to perform any task. For instance, Python can be used for using statistical techniques like Regression Analysis or Bayesian inference on datasets. Similarly, R can also be used for building new Data Science tools and data models. 

Python is quite easy to learn with simple syntax while R has various language boundaries. One can easily learn Python online with the help of a course. However, R is far superior in graphical and statistical procedures. R is more scientific in nature and will be much easier for statisticians or professionals who have worked with MATLAB, another scientific programming language.

Python is more focused on running algorithms and makes it easy to build programs in general. In Data Science, however, both are equally important and competent languages. R and Python can work with massive databases and are equally good at Machine Learning projects. 

R in Data Science

R is used in Data Science for graphical and statistical purposes. This language can help users create advanced visualizations and high-quality graphics as well as dynamic graphics. R is also great for data mining and statistical computing in general.

R has a set of functions that allows datasets to be loaded into the memory with program statements, but that is only required if you are going to be building R programs that will keep getting used for various functions. Otherwise, you can simply use the data import function in R Studio (IDE for R). R is able to work with data in two different formats in R studio, CSV and TXT. Once you select the dataset you wish to be working with, R will load the dataset and you can then work on it.

Python in Data Science

Python is a high-level programming level that does not require compilation before running code. This makes it very fast to use for all kinds of projects, including Data Science and Data Analytics. Python is extremely flexible and is a multi-paradigm language, thus, allowing Data Scientists to use different approaches and keep improvising the language with extensions and plugins.

Before loading a dataset in Python, you must first import pandas (library) and install them in Python. After that, a custom function must be created that loads the dataset for you. By creating a load_csv function, you can fundamentally provide an argument for your dataset’s file path.

Also, the readlines() are used in order to ensure that the program returns a list containing the lines inside the .csv dataset. You can also additionally present the data in a more visually appealing way by returning the dataset in a data frame format. This makes it easier to view the data as compared to the native list format or NumPy arrays.

Conclusion

Both the languages also are open-source and have huge communities behind them to keep providing new libraries. There are also a good number of updated tools and powerful IDEs (Integrated Development Environments) available for both R and Python.

If you wish to learn Python or R for Data Science, you should definitely opt for a solid Post Graduate Program in Data Science. You can also choose to take up a Machine Learning course with a placement or a Data Analytics course with placement as well. 

A quick and easy guide to Tableau

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A quick and easy guide to Tableau

Tableau is a famous data visualization software that helps people see and understand data. If you’re looking for an easy way to get started with Tableau, this guide will walk you through how it works to what types of visualizations are available in this tool.

What is Tableau?

Corporate leadership

It is a data visualization tool that makes it easy to view and analyze your data. It helps them visualize their findings so they can see patterns quickly and easily—and then act on those trends before they become problems for the company.

Why should you learn Tableau?

A tableau is a powerful tool that both individuals and organizations can use. It’s easy to learn and use, but its true power lies in the data visualization it allows you to create. 

A tableau is a powerful tool that’s easy to learn, use and collaborate with. You can use it in many ways:

  • To make visualizations (charts, graphs)
  • To create dashboards and reports
  • To work with others on data analysis projects

Types of visualizations in Tableau

There are many types of visualizations that you can create in Tableau. Here’s a quick overview:

  • Bar charts. Bar charts show the distribution of values in your dataset (e.g., sales by month). You can use bar charts to compare deals over time or across groups, such as how many people purchased products this year vs. last year or what percent each type of product accounted for at different times during the day (or week).
  • Line charts. Line graphs show trend lines on a chart based on some measures and other data points like age and gender. However, we still want some idea about whether any change is happening over time because otherwise, it would make no sense why one person might be doing better than another even though both have been using the app since the launch date!

Tableau course helps people analyze their data by allowing them to visualize their information visually in a way that makes sense. For example, they might want to see how many products were purchased by customers at different times or the average price for each product sold during the month of last year. Tableau allows you to accomplish these things quickly to make informed decisions based on what your data tells you about your business or project.

Discover a career in data science with Imarticus Learning

Become a data analyst with this data science course that guarantees job assurance. Learn data science practically and create complex models that 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 analytics 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.

The Most Influential People In The Data Analytics Industry

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The data analytics industry is growing at an exponential rate. Simply put, there is a lot of innovation and creativity in extracting knowledge from any data to make decisions based on past performance or future possibilities. Many professionals are driving the industry’s evolution by seeking and employing the best practices in this sector. This post lists the most influential people in this field.

Rohit Tandon, vice president and strategy WW head of HP Global Analytics

He is an experienced business leader well renowned for inventing and launching new companies into success. HP Global Analytics expanded under Rohit’s direction from a small team to a sizable analytics company. Global Analytics is now tasked with leading HP’s analytics delivery ecosystem and bringing together related departments to generate innovations that support HP’s corporate goals as a member of the Corporate Strategy team.

Pankaj Rai, Director of Global Analytics at Dell

The Director of Dell Global Analytics is Pankaj Rai (DGA). Pankaj has worked for Dell for around eight years and DGA for over five years. Before this, he supervised all strategic and corporate planning-related efforts for Dell in India while working with the office of the president of India. In this capacity, he was in charge of aiding Dell in diversifying and expanding its footprint in India and serving as Dell’s external representative in industry forums.

 Sameer Dhanrajani – Business leader, Cognizant Analytics.

As the head of Cognizant Analytics’ end-to-end business spheres, Sameer is in charge of developing differentiated strategies for the company’s analytics consulting, platforms, and services. He is also responsible for producing best-in-class GTM, business development, operational excellence solutions exercises, and transformational analytics engagements.

Amit Khanna- Partner at KPMG 

Amit has also put in a lot of effort to help organizations strengthen their analytics capabilities. He has spent much time developing numerous colleges’ analytics and data scientist curriculum. In addition to working with significant international customers to create their analytics organization and adopt a fact-based culture, he individually has two analytics patents.

Anil Kaul, co-founder, and CEO of Absolutdata

Dr. Anil Kaul is a well-known authority in the field with more than 16 years of expertise in marketing research, strategic consulting, and quantitative modeling. Over his four years at McKinsey & Co. in New York, he provided consulting services to over 20 Fortune 500 businesses. 

Learn Data Analytics with Imarticus Learning

This is the best data analytics certification course with a placement that will help you learn data science in the real world. Students will develop sophisticated models that yield crucial business forecasts and insight.

Course Benefits for Learners:

  • Data analytics, machine learning fundamentals, and the most widely used data science tools and approaches should all be familiar to students.
  • To receive a tableau certification, students must finish 25 real-world projects and case studies directed by corporate partners.
  • One of the sought-after abilities in the market today is the ability to visualize data by utilizing data analytics online training. Therefore, recent graduates and those just starting their careers might 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 To Master Data Analytics In 6 Simple Steps

Posted on by Imarticus Learning

How To Master Data Analytics In 6 Simple Steps

Data analysis follows a strict, sequential method, much like any scientific profession. Each step calls for a unique set of abilities and knowledge. But it’s crucial to comprehend the process as a whole to gain relevant insights. A solid foundation is essential for developing outcomes that withstand examination. This post will examine the key phrases in the data analysis process. This will cover how to specify your objectives, gather information, and conduct an analysis. 

Step 1: Defining the question

Identifying your purpose is the first stage in any data analysis procedure. This is frequently referred to as the “problem statement” in the context of data analytics.

Creating a hypothesis and planning how to test it is a necessary step in defining your purpose. Start by determining what business issue you’re attempting to resolve. Although it may seem simple, it might be more complicated. A data analyst must thoroughly understand the business and its objectives to frame problems appropriately.

Step 2: Gathering Data

This leads to the following action, data gathering. It’s time to specify the data you’ll need to get the answers to your queries now that you have a clear notion of them. You should check to see if the information is easily accessible within your company, such as through employee survey results or yearly performance assessments.

Step 3: Data Cleaning

The next step after collecting your data is to prepare it for analysis. Ensuring you are dealing with high-quality data requires cleaning the data. Getting rid of significant mistakes, duplication, and outliers—are all issues that always arise when combining data from several sources. Adding structure to your data—general “housekeeping,” such as correcting spelling mistakes or layout flaws, will make it easier for you to map and handle your data.

Step 4: Analyzing the data

You’ve finally cleared up your info. The fun part will now be examining it. Your aim will significantly impact the sort of data analysis you perform. But there are a lot of methods out there. Regression, time-series, and univariate or bivariate analysis are a few more you may be familiar with. But how you use them is more crucial than the wide varieties. What insights you hope to get will determine how to proceed. 

Step 5: Sharing your results

You’ve completed all of your analysis. You possess unique insights. Sharing these insights with the general public is the last phase of the data analytics process. This includes more than just disclosing the unprocessed results of your study; it also entails interpreting the findings and communicating them in a way that is understandable to various audiences. Because you’ll frequently present information to decision-makers, your insights must be completely transparent and unambiguous. 

Explore a career in data analytics with Imarticus Learning

customized corporate training

 This data analytics course with placement will help you learn data science in the real world. Students will develop sophisticated models that yield crucial business forecasts and insight.

Course Benefits for Students:

  • Data analytics, machine learning fundamentals, and the most widely used data science tools and approaches should all be familiar to students.
  • To receive a data analyst certification course, students must finish 25 real-world projects and case studies directed by corporate partners.
  • One of the sought-after abilities in the market today is the ability to visualize data utilizing a data analytics program. Therefore, recent graduates and those just starting their careers might 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.

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. 

How SQL and Python are Changing the Future of Data

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How SQL and Python are Changing the Future of Data

Introduction

Machine learning and AI may be making headlines, but did you know that the most critical talent in the data science sector is over half a century old! SQL has remained an essential data-processing language despite its age. It’s hard to believe that a language that has been around for five decades is still relevant in today’s fast-paced data science industry. 

SQL is not the only thriving aspect of data science. Python is another high-level programming language that is thriving in data science. Nobody likes unorganized, unfinished, enormous data just lying around. Python shines the brightest here as Python can easily manage this unorganized, unfinished data. If you are interested in honing your skills in this department, consider enrolling with Imarticus Learning programs, as it can propel your learning of Python for data science. 

How Python is changing the future of data

Python has a bright future as a large-scale, dependable, efficient, and ready-to-use technology. If you’re interested in data manipulation and visualization or machine learning and evaluation, this tool can do all of that and more. You can learn Python through various Python tutorials available on the internet. Imarticus Learning Programs is a major brand in the field of future technology-based professional education, devoted to sculpting the future workforce via innovative new age programs like Python for data science and analytics, artificial intelligence, and machine learning.

 Popularity of Python

The popularity of Python may be defined in a variety of ways. In addition to developers, Python is widely used for deployment management and web development, making it one of the most widely used computer languages in the world today. The Python language and its framework are also preferred by non-developers for data work when they first learn about it.

Python is becoming the first-choice programming language for prospective and current programmers who want to get “real employment.” Aside from online and mobile app development, the technology is also being utilized in data science. Python is extremely popular within the data science field. Since it is in high demand, you can find Python tutorials in Imarticus Learning Programs. Imarticus utilizes innovative technology and training methodologies to transmit information and a cutting-edge Learning Management System to merge online and live education.

Uses of Python

Python has a remarkable amount of adaptability. It is a versatile language that may be used for a variety of purposes. Data science’s ascent has led to Python is the number one programming language in the world. That brings us to AI. A language specifically designed for machine learning doesn’t exist, but Python’s strengths in this area make it the ideal option for most programmers who want to use ML. For Machine Learning, Python is one of the most widely used and finest languages.

 Python is unquestionable “the rage” these days. Python is a welcoming environment thanks to its widespread use and supportive community. It encourages developers to express themselves more concisely. Learning Python is quite simple, so you can get started right now. 

How SQL is changing the future of data

Before we jump to why SQL is the “rage” these days, let us understand what SQL is exactly. 

What is SQL?

An SQL query language is a specialized computer language intended to enable communication with databases. SQL is still used today for searching, updating, modifying, adding, and removing data in relational databases, even though it has changed quite a bit over the years. SQL is often used in conjunction with other computer languages, such as Python or R, in data science projects. SQL allows data scientists to extract specific data from an organization’s database. Using Python or R, users may then dig further into the data that their SQL query retrieved.

 What’s the point of learning SQL?

 The prevalence of SQL databases is undeniable.

 Most businesses depend significantly on their SQL databases. As a result, SQL abilities are expected to be in high demand for years to come.

 Nearly every job description that includes the word “data” calls for the use of SQL. SQL is the most commonly requested technical expertise for entry-level occupations such as data analysis (including Python, R, machine learning, and so on).

 SQL abilities (and some knowledge of spreadsheets) are sometimes the sole technical skills needed or assessed during the interview process for many data positions.

Conclusion 

Python and SQL have both taken data science by storm. The demand for these applications is not likely to stop anytime soon. If you are interested in learning Python or SQL, sign in for Imarticus Learning Programs. It is one of the best platforms for future data science experts out there. You can also contact us through chat support or drive to our training centers in Mumbai, Thane, Gurgaon, Pune, Chennai, Bengaluru, and Delhi. 

Does data analysis using SQL for software libraries?

Posted on by Imarticus Learning

Introduction

If you love tackling complex algorithms, solving tricky mathematical problems, or are simply attracted to your computer or similar electronic/digital devices by nature of being a geek, then the life of a data scientist is what you should be running after.

One of the most sought-after jobs in the 21st century, becoming a data scientist requires some basic knowledge of core concepts of big data training. These concepts are discussed briefly in the article below.

What is Data?

Fundamentally, data refer to bits and pieces of information that are stored and formatted in a manner that is consistent with the rest of the data for a particular purpose. Data can be found to exist in any format, whether it be on paper, in figures or as bytes in an electronic device, or even as nuggets of information in a person’s brain. However, in the era of the 4th industrial revolution, any mention of data generally denotes the kind that can be transmitted electronically.

Since data has become the lingua franca in the IT industry, it is imperative that we also explore the many dimensions of data through its many phrases old and new:

  • Structured data

Data existing in a fixed field such as spreadsheets and datasets are referred to as structured data

  • Unstructured data

Information or data that is not arranged in a column-row format

  • Raw data

Information yet to be analyzed and formatted

  • Metadata

A data set that has been summarized

  • Big data

A huge corpus of both structured as well as unstructured data that cannot be processed in the traditional manner of software technologies and database

  • Big data analytics

The method of organizing, collecting, and synthesizing data to explore useful information

  • Data mining

Data applications are used to figure out patterns that cannot be seen with the naked eye from a group of data in order to predict the behavior of something in the future.

How is SQL Relevant for Data Science?

SQL or Structured Query Language is a type of programming language used in standard databases for data management systems. It was conceived in the 1970s by IBM and has now become a standard process recognized by International Organization for Standardization (ISO) and American National Standards Institute (ANSI).

This programming language is employed for better management of relational databases and performance of operations on the data contained within them.

When we speak of SQL for database management, we speak of language’s capability to engage with more than one database at the same time. SQL is highly popular for data science since it is highly flexible and offers a great accessible learning curve with respect to complex depth. This enables users to create advanced data boards and tools for analyzing data.

To create and engage with databases efficiently, SQL has been utilized in a variety of tools, each with its niche market and focus. This includes big names such as Microsoft Access, PostgreSQL, and MySQL.  

Nowadays, big data is a huge concept, and learning how to use SQL for big data analysis can be a great skill that will open up big opportunities for you worldwide.

Benefits of a Big Data Training

To understand how a big data analytics certification course with a SQL specialization is helpful, let us look at the points below:

  1.     Big data training as part of business analytics courses will be a significant skill for top organizations
  2.     Data specialists are in high demand, and a big data analytics certification with SQL specialization will be a wise career choice for you for a guaranteed upward trajectory in terms of progress.
  3.     The role of a data specialist is a high-paying job
  4.     You can work across industries such as data quality, higher education, sales, financial institutions, marketing, business intelligence, and more!
  5.     Your big data training and SQL skills will put you at the forefront of important decision-making groups in your organization.

Conclusion

In the information era, if you want to carve a place for yourself in the digital world big data training with SQL specialization will be highly beneficial for you.

Data Analytics, Productivity and Well-being: Are they inter-related?

Posted on by Imarticus Learning

Forms and benefits of data analytics have shifted majorly in the last few years. Major firms have also been using it as a way to decipher the habit patterns of their employees to take care of their well-being. Needless to say, their well-being directly relates to their workplace productivity. However, with the evolution of data analytics, data analysts also have to be able to evolve constantly.

And that is only possible when they have the proper training to adapt to situations, and that can only happen if they learn data analytics from a proper institution. Imarticus Learning has come forth with a great opportunity for people who would like to polish their skills with their new PG program with data analytics certification. 

Coming back to the impact of the well-being of employees on company productivity, studies have found that being comfortable in their workplace can make the workers about 12% more productive.

Data analysis as a tool to ensure happiness

Major firms have been trying to gather and decipher the patterns of their employees’ behavior to provide a personalized experience to them for some time now. There are a lot of ways companies have decided to approach it. Some offered wearables to their employees that will teach how much time they spend, sitting, talking, writing, or moving about. Some have chosen the company intranet to trace their online tracks.

Now it falls to the data analytics team to extract, and decipher these patterns. It is fruitful in the sense that these patterns always give indications of not only their physical health but also their mental ones. This is also a way where companies can provide personalized suggestions for their well-being. And the employees get benefitted from it in a way that impacts their daily life. As a result, they feel more loyalty to the company.

Hurdles to jump over

There are some evident advantages of exchanging data for the betterment of the employees’ well-being, and in turn, increase their productivity. However, it is also a possibility that when it comes to data gathering and analysis, the employees might have some privacy concerns about them. Which in turn, might make them unwilling to participate actively in the bandwagon.

This is why, there are a few things that should be kept in mind when it comes to the interrelation of well-being and productivity of the workers, such as:

  • The first and most important thing is to make sure the workers consent to the exchange of data for the company’s use, as many might have privacy concerns relating to that.

  • Companies will need to have experts in the analytics team to properly extract and use the data and make it a priority for both the main wing of the business and the analytics team to prioritize the employees well being.
    They need to communicate properly to the workers how it benefits them and the company both at once.

  • The key is to recognize what the employees want and be able to cater to it. Otherwise, even after using data analytics to define the workers’ needs, it will be utterly irrelevant.

Conclusion

Using data analytics as a mode of communication between the employer and employee needs time and expert skills. And it can only come if you learn data analytics from a good place.

Many institutes in India offer a data analytics certificate course. Imarticus Learning is one of the topmost among them, so do check out their PG program in data analytics and machine learning.

The career outlook for data scientists with a Postgraduate degree in Data Analytics

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Data science is one of the most buoyant fields with myriad career opportunities and lucrative pay now. As the world is progressing towards big data and metaverse, the role of data and artificial intelligence will impact our lives more than ever before.

However, individuals must note that the role of data science includes a legion of disciplines and include multiple job titles such as data analyst, data engineer, program analyst engineer, and machine learning specialist. Therefore, to stay ahead of the pandemonium concerning job seekers, a PG in data science in India can significantly boost the chances of employment.  

big data analytics courseFuture of Data Science Jobs

Businesses and other allied sectors have now realized the importance of big data; thus, the demand for data scientists is soaring. As per a report by the Times of India, the volume of global data is projected to touch 180 zettabytes by 2025. To manage this enormous volume of data, the skilled workforce is bound to surge more in the upcoming years. 

LinkedIn’s Emerging Job Report has ranked data science as the fastest-growing field in the world and has estimated the market to reach USD 230.80 billion by 2026. Also, ‘The Humans of Data Science’ reports that data science will create around 11.5 million jobs by 2026. So, a data scientist career will reach new heights soon, and for new professionals, this might be the correct time to step into this booming field. 

Data Scientist Salary in India

India currently holds the second position as the most prominent recruiter in the field of data analytics and data science, next to the United States. In India, the average salary of a data scientist is approximately INR 698,412 per annum. But, for freshers, the salary hovers around the INR 500,000 mark per year. Also, an early-level data scientist can earn around INR 610,811 per annum with around 1 to 4 years of experience. Additionally, with experience and expertise, the salary increases significantly and might reach around INR 1,700,000 per year.   

Responsibilities of a Data Scientist 

Although the job responsibility might vary with the sector, in general, the responsibility of a data scientist remains the same. A few of these are: 

  • Analyzing large amounts of information and data to discover underlying patterns and trends 
  • Pre-processing unstructured or structured data
  • Building predictive models and ML algorithms 
  • Identifying valuable data sources for automating the collection process 
  • Provide impactful solutions for business challenges
  • To form an ensemble modeling by combining models

Skills Required for Data Scientists 

Individuals looking to learn data science online must understand that the job role of data scientist demands specific skills. So, they must enroll in a course that will provide adequate knowledge and skills that will allow them to sustain themselves in this field. Nevertheless, a few of the most demanding skills are: 

  • Knowledge in data mining
  • Skills in Python, SQL, and R 
  • Familiarity with Java, Scala, or C++
  • Understanding operation research and machine learning 
  • Strong mathematical skills
  • Problem-solving attitude
  • Strong communication skills 

In case individuals are looking to pursue a career in data science, it is always important to know the employer’s perspective. A master’s or diploma degree with prerequisites skills is often demanded. Hence, a postgraduate degree in data science in India might help secure a job.

And, to proceed with this career, individuals need to acquire skills with time. Also, as more and more businesses incorporate machine learning and artificial intelligence into their systems for better productivity, the jobs will soon expand to new horizons. Hence, this is clearly the most suitable time to jump into data science.

Python Training: Eliminate the skill gap in the modern workforce

Posted on by Imarticus Learning

There is a well-known skill gap in the present-day workforce. Many job roles remain unfilled because employers can’t find workers with the necessary skills. However, one skill can bridge this gap by 2022: Python training. 

Python is a universal language that you can use for various purposes, from data science to web development. This blog post will discuss why Python is so popular and how you can get started with Python training today! 

Python’s popularity in the tech industry

Python is becoming the third most-requested language on Stack Overflow and LinkedIn. Due to its versatility, ease of use, and popularity among data scientists for machine learning tasks. Many people who are just starting with programming languages choose Python because it has a simple syntax and is easy to learn. 

There are several reasons for Python’s popularity in the tech industry.

  • Python is easy to learn.

One of the main reasons Python has become so popular in recent years is that it’s relatively easy for beginners. It has a simple syntax and fewer lines than other languages such as Java or C++, making learning how to code more accessible for new programmers who want to get started coding quickly without having too much experience.

  • Python is versatile.

Python has many different uses, and you can use it for web development to machine learning. You’ll find that most people know how to code using this language because it allows them the flexibility they need when working on projects in any industry.

  • Python is open-source

One of the best things about using an open-source language like Python is that anyone can contribute to it or make changes if they see something wrong with how something works. It means there’s always a community willing to help each other out when needed, making coding less intimidating than ever before! 

The benefits of learning Python for both personal and professional development

 Python continued to be one of the most popular programming languages in 2021. The demand for Python developers is to grow exponentially in the next few years, with an Increase market share that will only widen further.

Many enterprises utilize Machine Learning (ML) and Artificial Intelligence (AI), which require vast amounts of data to be processed. Python has emerged as the leading language for data science and machine learning projects mainly because of its readability, comprehensibility, and ease of use. 

Professionals and students alike must learn this powerful programming language to bridge the skill gap in the modern workforce. There has never been a good time to start learning Python with its growing popularity than now. Don’t miss out on this opportunity!

Discover Post Graduate program in Data Analytics with Imarticus Learning

This data visualization program is by industry specialists to help students master real-world Data Science applications from the ground up and construct challenging models to deliver relevant business insights and forecasts. 

Course Benefits For learners: