A Tale Of Tech: Become A Qualified Data Scientist

Posted on July 1, 2022August 24, 2022 by Imarticus Learning

Reading Time: 2 minutes

A Tale Of Tech: Become A Qualified Data Scientist

Are you searching for an exciting career opportunity in a profession that is expanding daily? Consider working as a data scientist. Nowadays, most businesses use critical information gathered from their data to monitor success, make educated decisions, plan for the future, and so on.

Data science is among the most buzzed-about fields, and data scientists are in high demand. For a reason: data scientists are working on everything from self-driving vehicles to automatically captioning photographs. Given all the exciting applications, it’s no surprise that data science is a highly sought-after vocation.

Why should you opt for a data science course in 2022?

As the data science field grows, more individuals realize the importance of having a trained data scientist in their team. To undertake data science, you must be able to discover and handle enormous amounts of data. You will frequently be required to grasp and use programming, arithmetic, and technical communication abilities.

How to Become a Data Scientist?

If you do not have any data-related job experience, you can still become a Data Scientist; nevertheless, you will need to establish the necessary foundation to pursue a data science profession.

Data Scientist is a high-level profession; before achieving that level of expertise, you need to broaden your knowledge in a related topic.

Data Scientist Skills

Mathematics
Engineering
Programming
Statistics
Data analysis
Information technology

Data science training is an excellent approach to improving essential data science skills. Expect to master the fundamentals of data science, such as gathering and storing data, analyzing and modelling data, and displaying and presenting data using every tool in the data science toolbox, including specialist applications like visualization packages Tableau and PowerBI, among others.

It is significant to make an excellent first impression in any industry. However, this is especially vital when starting a new job. Everything begins with your portfolio and CV.

Your portfolio must contain the following characteristics:

Your portfolio should emphasize your most successful work.
It must be well-designed and convey a compelling tale about who you are outside of your work.
You should add value to your visitors’ experiences by emphasizing any effect you’ve had via your job.

Data Science Programming Languages and Tools

Python
RStudio Server
R
Hive
Jupyter Notebook
h2o.ai
Tensorflow
Apache Mahout
SQL

Data science is increasingly using machine learning – methods that use artificial intelligence to offer systems the capacity to learn and grow more accurately without being explicitly programmed.

Learn Data Science Courses with Imarticus Learning

Learn how to apply data science in the real world and create predictive models that improve business outcomes. This data analytics course with placement is suitable for recent graduates and professionals looking to advance their careers in data science and analytics.

Course Benefits For learners:

Learn the fundamentals of data analytics, machine learning, and the most in-demand data science tools and methodologies to become job-ready.
These concentrated sessions with hands-on exercises make learning more effective and efficient.
Students can clear all of their doubts in live sessions and take part in discussions throughout the course.

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

Why Should You Learn Python For Data Analytics and Artificial Intelligence?

Posted on February 23, 2022April 1, 2024 by Imarticus Learning

Reading Time: 3 minutes

2022 has seen a huge increase in both the number of data science applicants and also future aspirants all around the world. In India alone, LinkedIn, the global job search leader, announced a 25% spike in data science professionals as compared to 2021, and that is a huge number by a number of standards.

But one of the most common questions that ponders the mind of data science aspirants most often is why they should learn Python to get an edge in this profession?

Thus if you are planning for a career in data analytics and artificial intelligence in the future, and too have this question in your mind, in this article, we will answer exactly that.

Let’s get started.

Why Is Python Important for Data Science?

At the present moment, there are more than 35 different programming languages that are actively used by developers and coders all around the world. But among all of these, Python is undeniably one of the most versatile and well equipped, especially in the field of data science.

The reason behind this is simple; if you take a look at some of the most common tasks that are executed by a data scientist on an everyday basis, starting from data extraction and ELT (Extraction, Loading, and Transformation) all of them require a solid knowledge of Python coding and operation.

Along with this, another important reason why Python is so often relied upon as the go-to programming language for data science professionals is the fact that it comes with a suite of different packages, starting from SciPy, NumPy and pandas, which make complicated and time-consuming tasks easier, more efficient and effortless.

For instance, Matplotlib, which is one of the leading Python packages, is often used by data science professionals when they want to include visualizations or any sort of graphics in their simulations.

If all of this is not enough good reason, as to why you should learn Python

To get an edge for your career in artificial intelligence, here are some of the biggest advantages of the standalone programming language in itself.

Advantages of Python

Easy to Learn

If you are a beginner at coding and you are looking for a programming language that is easy and fast to learn, then Python should be your choice.

The programming language has been around since the late 1980s and has thus undergone several developments and improvements in the last couple of years, which has made the current version extremely user and beginner friendly to learn and execute.

Since data science is such a fast-paced career, where developments are literally happening overnight, the need for a language that is easy and fast to learn is a no-brainer, thus making Python one of the most obvious choices.

Scalable

When you would have spent a considerable amount of time coding, one of the first things you will realize is the fact that Python as a programming language is immensely scalable. Compared to programming languages like Matlab and Stata, which are industry leaders in their own might, Python makes it very simple and straightforward for anyone to scale. The language comes inbuilt with a suite of features that allows you to have multiple approaches and perspectives to solve the same problem, along with having a wide range of flexibility to try out new things as and when they are developed.

The scalability aspect of Python is the second reason why companies prefer their data science professionals to know Python. Scalability is immensely important in both data science and artificial intelligence, mainly because of the fact that new discoveries are being made on the regular.

Conclusion

Thus, if you want to give your career in data science an edge, now is the time to start enrolling for an Artificial Intelligence Training that comes packed with a course in Python.

We offer analytics and artificial intelligence courses at our centers in Mumbai, Thane, Pune, Jaipur, Delhi, Gurgaon and Bangalore.

What Skills Are Needed to Be A Data Scientist?

Posted on September 27, 2021March 22, 2024 by Imarticus Learning

Reading Time: 3 minutes

A career in data science is highly attractive owing to its payment structure, job opportunities, and future career prospects. There is any number of Data scientist courses that you can find and that makes you qualify for the job.
The major criteria for this career are a few skills that one can easily master through the right path.

These skills could very well be different from any former experience in the career thus far. Developing these skills will help the recruiters to identify you as the best option for what they are looking for!

Programming language
A strong knowledge base of any major programming languages such as Python, R, or SQL is the foremost requirement to be an expert in data science. No matter what the company or the job profile is, this is one field of expertise that is non-negotiable.

Statistics
Statistics hold more value in data science since it helps to deal with the raw data of the companies. It helps with the evaluation, designing, and making decisions in the later stages.

Deep learning
This machine learning technology enables computers to work like the human brain.

An enormous amount of data is managed through computing power to make it possible. A career in data science, especially that in the automobile and AI industry requires this particular skill.

Working with unstructured data
Data science is mainly about the gigantic amount of data from various sources. The vast majority of this data is in a raw and unstructured format. A skilled data analyst can easily go through them to find and identify what they are looking for to make it useful.

Appetite for problem-solving
Simply looking at the data is not what makes the analyst skillful. It also calls for the right appetite to identify the problems underneath and finding the ideal solution as well. For which the analyst needs to have the drive for problem-solving and look in the right areas.

Data visualization
This is the skill that enables a data scientist to identify and decode the raw data into an identifiable visual to use it to convey. This skill enables the analyst to see what the data is useful for with the help of the various data visualization tools.

Communication skill
It comes next to the visualization part. The visualized data needs to be explained in a simple and well-constructed plan to the stakeholders. AT this juncture, the analyst must have strong communication skills to convey the key points and make them believe in the same. Polishing communication skills would be an added advantage to improve career prospects.

Familiarity with data science tools
Data science involves various types of tools to help with data processing. An analyst must have a fairly good idea about the working of most of the tools. Since each type of data requires different tools, it is highly imperative to be on familiar terms with these tools. Most of them are pre-programmed, so you just need to know how to use them in the proper way.

Intuition
Last but not the least, having a strong intuition on what to look for, how to use it, and which tool needs when to get the best result out of the data analysis happens to be the strongest point of being a successful data scientist.

Conclusion
Most of these skills are covered in the Online data scientist course in India available from various sources online or otherwise. What needs more work would be on soft skills which also have an equally important role in a successful career. A career in data science does not have refined eligibility criteria, instead, it mainly depends on these acquired skills.

Welcome to the Data Science Club of Imarticus Learning!

Posted on July 8, 2021March 26, 2024 by Imarticus Learning

Reading Time: 3 minutes

Imarticus Learning is among the top online education providers in India. After its data science course helped many data science aspirants to build a successful career in the industry, it has now come with a new campaign i.e. the ‘Data Science Club’. This club will aim at addressing the shortage of data scientists in India. It will also help in unifying data science aspirants from all over the country & giving them a chance to interact.

You can bring the data science club to your college/university with just a simple process. They already have registered 30 colleges from locations like Delhi, Tamil Nadu, and Karnataka.

The registration process is open & you can experience a whole new aspect of data science. One can also join the data science community of Imarticus on various social media platforms.

Mission & Vision of the Data Science Club

To promote students across India to build a successful career in data science.
To address the talent gap in the data science industry & shortage of skilled data scientists in India.
To facilitate the exchange of ideas & information relating to data science between club members across PAN India.
To provide industry-oriented learning of data science involving technological advancements & tools used in the industry.

Registration Process

Generally, most of the colleges don’t even have a data science club. You could be the first to introduce a data science club at your college/university. You can visit the Imarticus website and can easily register your college/university for the data science club. You will be required to fill a google form asking for a few details like college name, address, department, designation, email address, etc. The Imarticus panel will get back to you and will inform you about further proceedings.

Benefits of Being a Club Member

This data science club will facilitate its members from various colleges across India in understanding the importance of data science. It aims at motivating aspirants for building a successful career in data science and bridging the talent gap in the current data science industry. The benefits of joining the data science club of Imarticus are as follows:

Students of member colleges can attend any event/competition under the data science club for free.
You will get to attend lectures or webinars from industry experts/professionals.
The members of the club will get to test themselves by participating in the national level hackathon.
You will get to attend data science workshops under this club. You will also get a certification from Imarticus Learning for being a part of the data science club.
The members of the club will also undergo the faculty development programme.
Eligible members/students of the club will also get full placement support from Imarticus.
You will get to know about the industry practices & trends by being a member of this club. You will also get to know about the right career roadmap in the data science industry.

If you want to make a transition from data science aspirant to an expert, you have to grab this wonderful opportunity which will bring you closer to the data science community in India. One can also opt for the data science course provided by Imarticus Learning to know about the data science aspects in detail.

Which Is Better, Becoming a Financial Analyst or a Data Scientist?

Posted on April 14, 2021September 1, 2025 by Imarticus Learning

Reading Time: 2 minutes

2020 is a year of opportunities for a lot many different fields and industries around the world. Although it has been a year of disarray, every difficult situation has always given rise to upliftment in certain industries, and this year is no different.

LinkedIn, which is the world’s number 1 job search portal, reported that in 2020, there was a 15% increase in the demand for financial analysts and a 25% increase in demand for data scientists. This data clearly shows that these two industries are booming in their own might and rightly so.

If you are planning for a job in either of these industries, in this article, we will draw a Let’s get started.

The Difference Between a Financial Analyst and a Data Scientist

One of the first and most important aspects to understand in this regard is the difference between both these job roles, so let us quickly take a look at the definitions of each.

Data Scientist

The role of a data scientist can be simply understood as being a professional who is responsible for analyzing, extracting and determining conclusions from the vast amount of data that is being collected by companies on a regular basis. The job role of a data scientist is to understand the data that is present and then determine business decisions, which will be most beneficial for the company both in terms of growth as well as profitability.

Financial Analyst

Now that you understand the role of a data scientist let us understand what a financial analyst does.

A financial analyst can be understood as a professional who analyses the financial information of a company and then takes decisions on the way forward so that the company can either increase their profit or take better decisions on their overall growth. The job of a financial analyst is to consider all the verticals that affect the financial health of a company and then determine if the company is making sound progress, or if it should make better decisions on the way forward.

Requirements for Each Career

One of the most fascinating aspects of both these careers is the fact that neither of them imposes hard and fast rules on the educational qualification you need to obtain to pursue these careers. Unlike other professions such as lawyers and doctors which mandate you to pass either the bar or the medical boards, these professions embrace all standard college degrees and put more emphasis on the skills a professional has.

Depending on the amount of competition each of these job roles have in the geographical location of your choice, the criteria for getting hired and the skills you need to acquire keep changing, and thus it is always a good measure to assess the demands of the employer before you proceed.

Conclusion

If you are looking for a career choice that embraces ambitious professionals like you and offers a lifestyle that is competitive, then both these career choices will be well suited for you. Along with this, both these career options offer high pay and other perks across the board, and thus you can be sure to get properly reimbursed for your job.

The choice between choosing either options comes down to you. If you fancy only financial data, choose online Finance course or if you want to work with a variety of data sets, choose the other.

Also Read: Difference Between Financial Analyst & Business Analyst

Stay Competent with most In-Demand Data Science Skills!

Posted on April 11, 2021April 8, 2024 by Imarticus Learning

Reading Time: 3 minutes

What is Data Science?

The Science of combining capital processes, algorithms, and many such best tools to collect, manage and analyze the most important data to make business decisions is Data Science.

Who is a Data Scientist?

A computing professional beholding the skill of data collection, data storage and management, and data analysis enabling the organization to make data-driven decisions quickly are Data Scientists.

In-Demand Data Science Skills

Some of the most In-Demand Data Science Skills are:

Understanding of Math & Statistics

Online Data Science course in India is all about extracting the required information from the data. A depth understanding of mathematical probabilities and statistical methodologies helps in data analysis.

The majority of the data science models are built using one or more, known or unknown variables. Thus, the in-depth understanding of multivariate calculus is the key requirement to develop Machine Learning models.

A detailed understanding of functions such as Logit, Cost, rectified Linear unit, Step, Sigmoid, etc. is very much required to deal with the large data. Apart from these functions, the detailed understanding of Matrix algebra.

vector Algebra and Differential and Integral calculus help the Data Scientists to develop and understand the systems at a faster pace.

Programming Skills for Data Science

In order to achieve the objective to transform the raw data into business insights, Programming skills plays a crucial role. Among all the programming languages, the go-to languages are Python and R, Python being the lingua franca in the data science field.

Skill to wrangle the Data

The process of removing imperfections from the raw data to get the data that can be easily analyzed is known as Data Wrangling. The entire process includes acquiring the data, combining the data with relevant fields, and cleansing the data. In short mapping the raw data from one form to the other to set up the data to get business insights.

Management Skills

Database management is a prerequisite of Data analysis. The basic requirements for a Database Management System is the family of programs to edit and manipulate the data and the operating system to provide the specific data.

Data Science Career

The special skills set will definitely make you stand out from the crowd when the field and hence the number of jobs in the market are increasing at a faster pace.

Data Science Career	Job Requirements	Average salary
Data Scientist	· Data collection and organization · Find the pattern in the data to help the strategic business decision	$139,840
Data Engineer	· Batch Processing of the database · Build and maintain data pipelines · Make the information available to the Data Scientists	$102,864
Machine Learning Scientist	Research for the new data approaches and deep learning techniques.	$114,121
Machine Learning Engineer	· Create data funnels · In-depth understanding of statistics and programming · Designing and developing machine learning systems	$114,826
Data Analyst	· Transform the large Database to meet the purpose. · Prepare the reports to facilitate the decision-making process by communicating trends and insights from the data.	$62,453
Business Intelligence Developer	· Design and develop the strategies to make the specific information accessible for business decisions in lesser time. · Facilitate the system understanding to the end-users to use the data effectively	$81,514
Statistician	· Facilitate the Data Collection process. · In-depth Data analysis · Data interpretation · Identify the relevant trends from the data · Design data collection processes · Advise the overall organizational strategy	$76,884
Applications Developer	· Keeping track of the applications used in the business and internal interaction · Design the overall process flow of applications with the inclusion of development of user interface components etc.	$113,757

Average Salary data is taken from https://www.glassdoor.co.in/Salaries/data-scientist-salary

10 Data Science Careers That Are Shaping the Future!

Posted on April 9, 2021March 26, 2024 by Imarticus Learning

Reading Time: 3 minutes

Data is wealth in modern days and data scientists will be in huge demand in the coming years. Firms require skilled professionals to analyze the generated data. Data analysis is also predicted to surge with the rise of new-age technologies like machine learning, artificial intelligence, etc.

According to reports, there is a shortage of expert data scientists in the market. One can opt for a post-graduate program in machine learning to gain the skills needed in the data science industry.

Let us see about ten data science careers that are shaping the future.

Data Scientist

Data Scientists have to organize the raw data and then analyze it to create better business strategies. Data is analyzed for predicting trends, forecasting, etc.

Data scientists are technical personals who are fluent in data analysis software and use them to predict market patterns. Firms will require more skilled data scientists in the future due to the need to process & analyze big data.

Business Intelligence Analyst

Business Intelligence (BI) analysts & developers are required to create better business models. They also help in making better business decisions. Policy formation and strategy development are key responsibilities of a BI analyst. Firms have to face market disruptions and need good business models/strategies to tackle them. BI analyst/developer will be in demand in the coming days.

Machine learning Engineer

Machine Learning (ML) Engineers are required for creating better data analysis algorithms. They have research about new data approaches that can be used in adaptive systems. ML engineers often use other technologies like deep learning, artificial intelligence, etc. to create automation in data analysis.

Applications Architect

Firms require good applications and user interfaces to run business processes smoothly. Applications architects choose or create the right application for their firms. Due to the rise in the complexity of data, firms will require better applications to manage it.

Statistics Analyst

A Statistics analyst or statistician is required to interpret the data and present it in an understandable way to non-technicians. They have to highlight the key insights in big data to stakeholders/fellow employees. Data analysis results are also used to make predictions and identify potential opportunities. You need to be good with numerology if you are thinking to become a statistician.

Data Analyst

They have to convert large data sets into a suitable format for data analysis. They also help in finding the data outliers which can affect the business. There is a lot of data generated every day as humans analyze less than 0.5 percent of data produced! Data analysts are already in huge demand in the data science industry.

Infrastructure Architect

Infrastructure architect in a firm makes sure that the applications, software(s), databases used by the firm are efficient. Infrastructure architects also help in cost optimization. They make sure that their firm has the necessary tools for analyzing big data.

Data Architect

Data architects mainly focus on maintaining databases.

They attempt to make the database framework better. With the rise of automation in data science, data architects are in huge demand to provide better solutions.

Enterprise Architect

Enterprise architects are IT experts and provide firms with better IT architecture models. They suggest stakeholders & senior managers in choosing the right IT applications for data analysis. Top companies like Microsoft, Cisco, etc. hire enterprise architects for maintaining their IT framework.

Data Engineer

Data engineers are required to create a good data ecosystem for their firms where the data pipelines are maintained. Data Engineers are required to choose better data analysis applications to provide real-time processing. They also help in making the data available to data scientists.

Conclusion

Data science is a growing field and there are a lot of job opportunities. You can learn Data Science Courses in India from a reliable source like Imarticus learning. One can also target any particular job role in the data science industry and should learn the necessary skills. Start your post-graduate program in machine learning now!

How Freshers Can Get Real-World Job Experience In Data Science

Posted on October 12, 2020March 26, 2024 by Imarticus Learning

Reading Time: 3 minutes

Introduction

For most freshers, landing a Data Science job seems like a chicken-or-egg situation. You need to have hands-on work experience to get selected for such a job, but how do you get any work experience without first being hired?

By now, you must have heard, read or seen a lot about the scope for immense growth that a Data Science career can offer. However, for many aspiring Data Scientists, the reality appears to be hard-hitting.

The career potential of a Data Scientist is undoubtedly very rewarding once an individual gets the job, but getting the job without prior work experience is the main obstacle they face. Below, we examine some practical solutions to this dilemma:

Work on personal Data Science projects

This is an interesting and highly practical way to gain real-life Data Science experience. Once you finish a project, you can showcase your work on a platform like GitHub. Focus on small projects, and try to demonstrate important Data Science skills in your efforts.

The advantages of working on your own project are that you gain hands-on experience in generating ideas, collecting data, cleaning data, analysing data and building predictive models.

Therefore, you gain a comprehensive understanding of the entire process. As far as possible, try to script clean codes and develop clear visualizations that potential stakeholders can find easier to follow.

Do not attempt to display too many skills at once, as you might end up unnecessarily complicating matters for your audience. Simple and small projects will illuminate the core skills you wish to draw attention to. For example, consider obtaining a complicated datasheet and cleaning it up. This simple project will demonstrate your prowess in:

Scoping a data project and formulating a suitable plan
Gathering data using different collection methods
Contemplating different data cleaning methods and choosing the most suitable one
Handling different data formats such as XML, CSV and JSON

Contribute to open-source projects

The best way to enhance your coding skills and get hands-on Data Science experience is to join an open-source community. Providing solutions to projects that are already in progress will help you deal with real-world problems, while giving you a taste of what working in a Data Science team would be like.

As a member of an open-source community, you need to constantly communicate with the other stakeholders when making your contributions. Open-source projects are an excellent way to access Data Science libraries, such as NumPy, Pandas, Scikit-learn, and more. Above all else, being a part of these communities will help you build a professional network with relevant people in the Data industry, and also significantly add to your existing knowledge.

Make tutorial / educational content

If you have confidence in your Data Science skills and knowledge, you can try authoring a Data Science blog feed, or creating tutorial videos that explain the core concepts of Data Science. These are excellent ways to highlight your abilities to prospective employers.

In-person meetups

After you complete a Data Science course, in-person meetups can present great opportunities for face-to-face interactions with industry leaders and representatives. Meetups are essentially corporate events being held in your city, such as business conferences, presentations, seminars, expos or coding competitions.

These events are excellent venues for networking with like-minded professionals who work for a range of different organizations. A simple Google search with keywords like Data Science meetups, along with the name of your city, will generate information about ongoing or upcoming events near you.

Volunteer for a good cause

Many non-profit organizations need Data Science professionals to volunteer for them. This is a good way to give back to society, while at the same time, you could get to work alongside experienced Data Scientists who can guide you and offer valuable career advice.

The tasks you perform can be showcased in your resume, and will be considered as valid work experience. Poverty, Environmental Protection, Equal Education, Public Health and Human Rights are some of the non-profit areas that you can contribute to.

Conclusion

The career scope for a Data Scientist is tremendous, but it often proves difficult to get a Data Science job without a certain amount of relevant work experience. The key is to show recruiters that you possess the requisite expertise and skills to do justice to the job if you are given the opportunity, and the steps listed above will go a long way towards accomplishing that.

What is the Role of Data Scientist?

Posted on September 29, 2020September 30, 2020 by Imarticus Learning

Reading Time: 3 minutes

A data scientist is someone who systematically organizes the large volume of raw data in any given field. This individual will then analyze the entire specifics to process it according to the needs and present it in such a way that helps solve a problem. The overall objective here is to improve the business prospects for the stakeholders. Though each field differs in their requirements the basic role of the data scientist remains the same.

What does the role demand?

This particular role demands skill in various fields such as computer science, mathematical, analytical, and statistical skills. Today, there are unlimited raw data available from various sources. A skilled scientist should be able to analyze and compile them into a useful form for the field they work in.
In order to identify and use the information in the right manner, all these skills would be necessary for the various stages of this analysis. Here are the major stages of data analysis by scientists.

Research: The primary stage is doing the research on the specified details and identifying which is relevant and what to ignore. This step could be termed data mining which literally means to dig deeper to find the best and relevant input.
Once the relevant details are identified, the next step is to acquire it. The information is scattered and it needs to be collected, cleaned, and duly and specifically stored according to the requirements. This will help with the next stage of data analysis.
Analysis: The analytical stage involves several processes where the scientist will have to use the information and implement the algorithms and other skills. From the collected details, the scientist must identify the scope and methodology to transform it into the specific model for usage by the business. The ultimate aim is to make use of the data in a beneficial way. So, this analysis and integration of input into a workable model is an important step.
Design: The final stage is where the collected facts and figures undergo processing to make it suitable for the final implementation for the business. It is processed and designed in such a way to present the best model. Prior to its presentation, the analytics specialist must evaluate the results and review them properly. Once presented the scientist would then collect feedback from the stakeholders to change it to the best version for the field. Though this stage is not exactly about any design, the data scientist is responsible for the model making and its final output. This role demands the application of the various techniques learned by the individual and the right usage of the same at the key areas.

How to qualify for this role?

Anyone who has a basic knowledge of computers can learn the field and be a data analytics specialist. Even if there is no formal education in computer science, there are various degrees and certifications courses available to qualify for the role.
One can enroll for any data scientist course to polish the skills and qualify for the role.

Conclusion

The role of a data scientist is performing the processes in repetitive mode but the overall work specifics changes according to the requirements and feedback. The role also calls for good communication skills and a creative mind to present the data in the form of compelling storytelling. This is a great career opportunity at this juncture since everything revolves around the abundant data available and utilizing them into a useful model is a real skill. If you are planning to fit into this role, start developing, polishing, and practicing your skills now!

We offer data science course at our centers in Mumbai, Thane, Pune, Jaipur, Delhi, Gurgaon, Bangalore, Chennai, Hyderabad, Coimbatore.

What Does It Take To Be A Good Data Scientist?

Posted on September 18, 2020April 2, 2024 by Imarticus Learning

Reading Time: 3 minutes

What does a data scientist do?

The importance and applications of data science have grown exponentially over the past decade. Data science is still in its nascent stage and there’s a whole lot to be identified about this discipline. Businesses have started implanting strategic decision-making tools that leverage data science.

Data helps businesses by providing them with hidden insights and helps them predict the future outcome of their decision. This helps organizations to make a better business decision.

Let’s delve deeper into what these data scientists do and how it helps the organizations.

Finding a solution to business problems

One of the most basic and key responsibilities of data scientists in an organization is to identify existing challenges and problems that a business is facing and finding solutions to remedy the situation. This might seem like a generic responsibility of every important professional but the main difference here is that data scientists use tons of relevant data to find the problem.

They try to come up with solutions after properly assessing the situation using various analytical tools that provide them with useful insights. They leverage statistical analysis, data visualization and mining techniques to provide effective solutions.

Find out relevant data using complex research

The 21^st Century businesses are complex than ever, there are various factors that determine the fate of an organization. With the number of complexities that exist, it’s very difficult to figure out what impacts your business and how it does that.

Data scientists simplify this for organizations by studying all variables affecting a business. They use complex research work to identify the variables that have a maximum impact over the business and which are highly relevant.

Identify patterns and trends

Another important work of a data scientist that helps businesses is to identify patterns and trends. Data scientists use sophisticated data analysis techniques to find trends and patterns from the data sets at hand. These data sets are generally historical records of the organization. It helps them to identify the existing patterns and trends which is used to make predictions regarding the future movement of the variables.

How to become a data scientist?

Data science is one of the most in-demand skills in the industry and given the wide range of applications that it has, the demand for a data science professional will continue to rise in the future. One of the most common questions in the minds of data science aspirants is how to become a data scientist? There is no specific answer to this particular question. It depends on what stage of your career you are at and the skillset that you have.

A data science course by reputed institutions such as Imarticus Learning guarantees placement with top-notch firms in the industry in addition to providing relevant knowledge and skills. It also helps you provide guidance from the industry experts who are highly experienced in this domain.

Let’s delve deeper into some of the most prominent skills for data scientists that you should hone if you are planning to opt for a career in this field.

Analytical skills

One of the key skills that are required in this profession and that forms the base of all your work is your analytical skills. One should have an analytical mindset and should be able to identify trends and patterns from a big chunk of data. You should be able to assess a situation from a different perspective to reach a successful conclusion. One should be trained to work with software like Python and R and should be equipped enough to handle large volumes of data.

Problem-solving skills

Another important skill that you need to work on is your problem-solving skills. You need to use data to figure out challenges that exist in the business. After you have figured out the problems you will have to provide a solution using data analytics tools that will help the business to achieve its goals and objectives.

Tag: Data Scientist