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6 Reasons Why You Should Learn Data Science in 2023

Posted on by Imarticus Learning

With data science, you may enter the future and discover a world of limitless opportunities! 

Data science has become the cornerstone of business success for companies in a wide range of sectors in the constantly changing world of technology and innovation. 

Data Science Course

Choosing to learn data science in 2023 is a choice that may lead you toward unimaginable changes, regardless of whether you are a computer enthusiast, a problem solver, or a curious mind searching for new vistas. 

This blog will provide six strong arguments for why adopting the field of data science is not simply a fad but a life-changing adventure that may influence your future. So buckle in and prepare for a fantastic journey into data-driven insights and boundless possibility!

What is Data Science?

Data science ensures that massive amounts of incoming astronomical data are used effectively and efficiently to maximize profit for the targeted business or industry in a world where astronomical data are constantly being produced. Data science organizes, models, and streamlines the source data flow to the intended audience. 

Most important data science industry trends to watch in 2023:

  • Data Cleansing

It involves locating inaccurate, flawed, duplicate, or irrelevant data, eliminating unnecessary data, and replacing or editing undesirable data with desirable ones. Data purification is the first stage in data science. Possibly it’s the most crucial one. 

  • Big Data

The word itself gives away the concept, simply large or abundant data. Big data is extremely large or moving so quickly that handling it using conventional techniques is nearly impossible. Thus, the data science course that will drive the big data story emerges as the rescuer.

  • Artificial Intelligience

AI aims to create machines or devices that can observe their surroundings, compare various behaviors to them, create an algorithm, and then respond in line with the machine-created algorithm. We’ll see in a bit that machine learning is one of the extensively utilized data science course qualities similar to AI.

What are the benefits of learning data science?

Benefits of learning data science in 2023:

  • A fuel of 21st Century

Oil was referred to as “black gold” in the past Century. Oil, however, changed the course of human civilization after the industrial revolution and the rise of the automobile industry. However, when they became gradually exhausted, and people turned to other renewable energy sources, their value decreased over time. 

Data is the new industry-driven force of the twenty-first Century. In reality, data is being used by the automotive industry to enhance autonomy and increase vehicle safety. The goal is to build robust machines that think analytically.

Data science is also the current that drives today’s industry. Industries require data to increase productivity and boost profits.

  • Data science skills are adaptable and portable. 

Data science involves more than just computing data and producing code. It also involves posing the proper queries, speaking clearly, and resolving practical issues. You may enhance your career in any profession by using these talents, which are relevant to any domain. You will gain from learning data science whether you intend to work as a data analyst, data engineer, machine learning engineer, business intelligence specialist, or in any other position using data.

  • Data science is entertaining and inventive. 

Data science is not merely a dull and dry field of study. It’s also a creative and enjoyable one. You can investigate various datasets, identify patterns and trends, design models and algorithms, build dashboards, and test your assumptions. You may utilize your creativity and curiosity to learn new things and make tales using data. You have the opportunity to experiment with new methods and discover new technologies. Data science is like a mental playground.

The lack of decision-making authority is something that people frequently complain about in most traditional employment. And this becomes a key factor in the global rise in work discontent. 

  • Gives You Decision Making Power

You can fend off such unfavorable emotions by working in data science. This is obvious given that the key decision-makers are all involved in data science, and each of their responsibilities carries a significant amount of weight and credibility that is always noticeable.

  • Data science is rewarding and lucrative.

According to Glassdoor, the annual income for a data scientist is $1,04,027 in the United States. Because of this, a job in data science may be quite rewarding. It is primarily caused by a big salary bubble brought on by the shortage of Data Scientists.

The learning curve for data science is relatively high since it necessitates expertise and understanding in several domains, including statistics, mathematics, and computer science. As a result, a data scientist has a very high market value. A data scientist has a high-profile position in the organization. 

  • Data science is impactful and meaningful. 

Not only is data science a technical competence. Additionally, it’s a means of altering the world for the better. You may utilize data science to address some of the most important issues confronting humanity, including social justice, health care, education, and climate change. Data science may be used to make people’s lives better, strengthen communities, and create change. Data science goes beyond a career. It has a mission, too.

The Ending Note

After reading this thrilling investigation of the six revolutionary reasons why mastering data science in 2023 is a game-changer, we hope you will be motivated and prepared to start this life-changing adventure. 

Remember that the world is changing astoundingly, and data science has taken the lead in practically all innovation, decision-making, and success areas. Imarticus Learning provides a thorough Certificate Program in Data Science and Machine Learning, painstakingly designed to jumpstart your career in data science. 

This curriculum, created in partnership with iHUB DivyaSampark @IIT Roorkee, gives aspiring data scientists the ideal foundation and equips them with crucial abilities to dig into data science and machine learning.

If you want to learn data science and machine learning, look no further

Posted on by Imarticus Learning

If you want to learn data science and machine learning, look no further

We all must be familiar with the terms data science and machine learning. These are the emerging technologies that are in high demand these days. They are the present and the future in a technologically-driven world, which is why most people opt for a career in these fields. If you’re a fresh graduate or someone who wants to elevate his career or is interested in starting a career in analytics, you have reached the right place. This article will discuss the reasons to go for a career in data science, different job roles, and the best data science course available.

Simply put, machine learning is the science of getting computers to learn and act like humans by feeding them information from the real world. Coming data science is the science that is used to process a huge volume of data using different tools, algorithms, and methods to discover hidden patterns in the raw data. These advanced technologies are not restricted to a specific area but are applicable in various fields, such as transportation, healthcare, finance, sales, and many more.

Why go for a data science and machine learning course?

  • High demand

The data science sector is highly employable and the fastest growing job market globally. It is predicted that data science will create 11.5 million jobs by 2026. The demand for data scientists is high in various industries, making it a versatile career option.

  • Eliminates boring tasks

The primary benefit of data science is the ease it has brought to operations by automating manual, cumbersome, and redundant tasks. Many industries benefit from these advanced technologies as they use historical data to train machines to perform repetitive functions in much less time.

  • Highly remunerative career

A certified data science and machine learning course paves the way for one of the most highly paid jobs. Glassdoor revealed that data scientists earn an average of $116,100 annually. Moreover, the abundance of opportunities available for people in various sectors makes it an appealing prospect.

  • Highly prestigious job

Businesses highly value data scientists as they help make smarter, data-driven decisions. They hold an essential say in companies as even the higher management relies on their expertise on some issues. They are highly reputed since they make more intelligent products, improving overall user experience.

  • Career growth

If you’re feeling stagnant in your job, a professional certification from a data science course can help grow your career exponentially. It will make you stand out among your competition and strengthen your profile. A study by Business Wire stated that a certified data science course led to a salary increase of 20% to 40%.

Job roles in data science and machine learning

A certified course in data science and machine learning is well-regarded and opens up plenty of opportunities for you in the form of the following job roles:

  • Data scientist
  • Data Analyst
  • Business Intelligence Analyst
  • Data Engineer
  • Data Architect
  • Machine learning Engineer
  • Project Manager
  • Data Statistician

Anyone interested in data science and machine learning can enter the job market as a data scientist at any career stage. A background in Mathematics and statistics would be of great help. However, you can aspire to become a data scientist irrespective of your academic background and even if you’ve never written a code, with the help of your sheer commitment and proper guidance.

Imarticus Learning offers an excellent Certificate Program in Data Science and Machine learning for working professionals and anyone looking to kickstart his career. This certified course is built in collaboration with iHUB DivyaSampark, a technology innovation hub at IIT Roorkee.

This comprehensive program is easy to understand and prepared by the acclaimed IIT faculty and industry experts for early and mid-level professionals. Thus, it focuses on building a strong data science foundation and specializes in machine learning with Python for data-driven decision-making.

Some of the important features of this data science program are as follows:

  • Live online training will be imparted by renowned faculty of India from IIT Roorkee, IIT Guwahati, IIT Ropar, and industry experts.
  • A 5-month program designed to equip you with the proper knowledge to implement and apply data science concepts to real-world problems.
  • Opportunity to participate in 2-day campus immersion at iHUB DivyaSampark at IIT Roorkee.
  • Startup mentorship and funding support under the program.
  • Program coordinated by Dr. Balasubramanian Raman, the top data science and ML academician.
  • Certified collectively by IIT Roorkee and Imarticus Learning under the National Mission on Interdisciplinary Cyber-Physical Systems.

Check out the program in detail on our website. You can even connect to us through chat support or meet us in person at any of our nearby training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

How Data Science is Making Personalization of Customers Feasible?

Posted on by Imarticus Learning

How Data Science is Making Personalization of Customers Feasible?

Data science opens the door to an enormous number of possibilities in customer experience management. It plays an increasingly important role in all areas of the customer relationship management lifecycle, but countless companies have yet to make this advanced technology part of their marketing tools.

One of the main reasons is the lack of full visibility of what can help them engage better with customers and the inability to quantify potential improvements. Nowadays, with the amount of information available to both consumers and businesses, the key to success is knowing how to offer personalized offers that appeal to each consumer. 

Data Science for the Hypersonalization of Customers

To better understand how data science can make sales and marketing actions more effective, it helps to think about one of the main responsibilities of these groups: acquiring new customers. To optimize commercial strategies in a highly competitive market, working around qualified leads is the basis for success. In that sense, data science can greatly improve projections and help a company increase sales by effectively identifying those who represent real business opportunities. 

Intelligent data analysis allows the segmentation of leads based on their specific criteria, such as needs, purchasing power, geographic location, and other exclusionary criteria. In this way, it is possible to optimize prospecting efforts, allowing companies to increase their closing rates and, ultimately, business profitability. 

Role of Data Science

Data science extracts value from data through the combination of multiple fields, such as statistics, artificial intelligence, and data analytics. Data science involves the preparation of data for analysis, including steps such as data gathering, scrubbing, presentation, and manipulation. Data scientists can pursuit analytical operations and are able to review results to reveal patterns and enable businesses from different fields to gain informed insights.

To optimize commercial strategies in a highly competitive market, working around qualified leads is the basis for success. In that sense, data science can greatly improve projections and help you increase sales by effectively identifying those who represent real business opportunities. Today, more and more people are opting for a Data Scientist Career, as it is in increasing demand in many industries.

Why Imarticus for data science online course?

Not only is data science being key for market forecasting and finding good investment opportunities but also for smart marketing. As competition in the market increases, it is becoming more and more necessary to shape the business according to the demands of end-users. Data science makes it possible to offer products/services that address the needs of each user. 

Here at Imarticus, we offer an industry-designed curriculum on DSP Data Science Prodegree. In partnership with many industry leaders, we will introduce you to real business projects and case studies, throughout high-quality tech-enabled education. With one of our courses at Imarticus, not only will you learn data science, but also, we will provide you full placement upon completion of the program.

Conclusion

Data science opens a door to an enormous number of possibilities in customer experience management. It gives sales and marketing professionals a new way to make key data-driven decisions on how to deploy resources and engage prospects and leads more effectively, eliminating the reliance on guessing answers and relying on gut instincts in making critical decisions. You can subscribe to a data analytics course in India offered by Imarticus and become a well-profiled professional in this field! 

Why Should Engineers Learn Data Science Differently?

Posted on by Imarticus Learning

Why Should Engineers Learn Data Science Differently?

Data science and engineers have a lot in common. They both need to know how to collect, store, analyse and visualize data. Engineers are taught these skills as part of their curriculum; however, they may not learn them as they would if they were learning Data Science from the start. The following is an overview of why engineers should learn Data Science differently than other disciplines.

A blog post intro paragraph engages professionals about why engineers should learn data science differs from other disciplines. Engineers are taught these skills as part of their curriculum but may not understand them simultaneously or efficiently without exposure to them earlier in life.

Why is Data Science important for Engineers?

Engineers always like to think about their work in processes and systems, also known as Systems Thinking. It is what enables them to build more efficient products by efficiently running those processes. By thinking of the world in this way, engineers can quickly solve data-related problems because they see all sides of an issue that deals with data.

It’s important to remember that engineering can be applied in any industry, including Data Science. As a data scientist, it’s often necessary to run specific processes and analyze the results. Engineers excel as they can take these processes and incorporate them into the current system that the company may already have set up, saving time and money in some cases.

Benefits of Learning Data Science for engineers.

Therefore it is necessary to run specific processes and analyze results where engineers excel in taking these processes and incorporating them into current systems that a company may already have set up.

Learning Data Science is important because of the benefits that engineers will gain. Engineers overall will be able to learn more efficiently about their field and how it fits into the bigger picture. By taking this information, they will be able to make smarter decisions in data-related situations.

Engineers should learn Data Science differently from other disciplines because it will make them understand better and more thoughtful about their field and how it fits into the bigger picture, enabling them to make smarter decisions in data-related situations.

Why Enrol in the Data Science program at Imarticus learning

Industry specialists created this postgraduate program to help students understand real-world Data Science applications from the ground up and build robust models to deliver business insights and predictions. The Data Science program is for recent graduates and early-career professionals (with 0-5 years of experience) who want to pursue Data Science and Analytics, one of the most in-demand fields.

Twenty-five in-class real-world projects and case studies from industry partners will help students become masters in data scientist careers. Exams, hackathons, capstone projects, and practice interviews will help students prepare for placements.

Some course USP:

  • The course lets the students learn job-relevant skills that prepare them for an exciting Data Scientist career.
  • Impress employers & showcase skills with a certification endorsed by India’s most prestigious academic collaborations.
  • World-Class Academic Professors to learn from through live online sessions and discussions. It will help students understand the practical implementation of real industry projects and assignments.

Contact us through the live chat support system or schedule a visit to training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

Does Data Science Require Coding?

Posted on by Imarticus Learning

Data science has been gaining significant traction over the past few years. Myriads of people working in several areas including, business and IT look to shift to this emerging career option. Moreover, individuals with immense expertise (over 10 years) want to switch to data science.

Going for a data science course begins with numerous queries such as “Does data science require coding?”, or “What are the requisites to learn data science?” It is not necessary to be an expert coder to become a data scientist. Insufficient coding skills should not preclude people from pursuing a data science career. There has been a notion recently that people need excellent coder to become a data scientist.

Undoubtedly, coding is essential in data science but that does not imply that you need to be a hardcore coder to go for a career in the field. Industry executives reckon that anyone who knows the fundamentals of coding – functions, loops, and programming logic – can flourish as a data scientist. Having coding skills already is a plus point in a data scientist job but not compulsory. Then, what about those who have never learned to code earlier? Is there any other way they can become data scientists?

Tips for Non-Coders Learning Data Science

Become an Excellent Storyteller

If you think that vital business decisions rely on data and other quantitative parameters, you are wrong. Even after a machine learning (ML) model is developed and assessment is done by people expert in coding, somebody has to present the outcomes to the shareholders who are well oblivious to programming languages or statistical models. This accents for the need of a story woven around the insights to convince shareholders quickly. You can become that individual with exceptional storytelling abilities in spite of having mediocre programming skills.

Get a Grip on GUI-based Tools

If you are not much of a coding person, then the first thing you can do is to learn the application of GUI-based tools. There are many graphical user interfaces (GUI) supported data science tools that exclude the coding aspect and offer a user-centric interface that aids everyone with the fundamentals of algorithms.

The tools are quite easy to use to develop top-notch ML models sans coding. The majority of these GUI-based tools can be accessed for free and allow you to assess and elucidate data via charts, graphs, and other special graphics.  You do not have to display exceptional coding skills to efficiently leverage these tools but instead having a knack of visualization does help.

Enhance your Credibility with Business Intelligence

If you an expert in insurance or have comprehensive experience working in the retail sector, it is good news for you. You certainly are aware of the nitty-gritty and intricacies of businesses compared to expert coders. If you are highly skilled in areas such as healthcare, and e-commerce, you will be an asset to any company. No certification of expert coding skills can beat business intelligence in a particular area for a long period. Capitalize on your domain expertise and abilities and become the data science wizard.

Final Words

At present, the success mantra to grab a data scientist job in any company is, “The More You Know, The Better It Is.” Although companies prefer professionals with specialized coding knowledge, they are increasingly channelizing their attention towards candidates exhibiting a diverse skill set.

To wrap up, you need not be a die-hard coder or programmer to become a great data scientist.

Why Do Data Scientists Need To Learn Java?

Posted on by Imarticus Learning

Java has today regained its prominence as the most popular language suite for developers and has outrun both R and Python. This is not surprising since Java boasts of the largest community of developers and also has applicability, compatibility, and ease of learning to aid it. AI, ML, and data sciences are all relying on the JavaScript suite and its applications and these are the areas seeing rapid evolution and need for personnel.

Further, when demand rises the payouts get better. Career aspirants and career-changers both are ready to learn data science and are flocking to these fields and this only adds to the popularity of Java as the ultimate weapon in the developer’s kit.

Here are the top reasons to learn data science and Java.

  1. The old-gold class: Being the oldest language in enterprise development it is frequently found that legacy systems have their infrastructure already running on Java. This means you have probably used R or Python for modeling and have to rewrite the models to suit the system running in Java.
  2. Wide frameworks: The Big-Data tools and frameworks like Flink, Spark, Hive, Hadoop and Spark are Java-based. Familiarity in the Java-stack is thus easier for analysts working with large data volumes and big data with Hive and Hadoop.
  3. Libraries aplenty: Java has toolsets and a great variety of libraries for ML applications and data science applications. Take a look at Deeplearning4j, Java-ML, Weka, or MLlib to quickly resolve and issues in data science.
  4. REPL and Lambdas: While Lambdas that came with Java 8 altered the verbosity in Java, the recent REPL of Java 9 adds iterative development to the developer kit. It is now easy to learn and work in Java than it initially was.
  5. Virtual Machine in Java:  JVM helps write multi-platform identical codes facilitating rapid customization of the tools required. With the IDEs variety on offer, developers can be more productive.
  6. Strongly Typed: This does not refer to classic static typing. Rather it deals with Java being able to specify the types of variables and data the developer needs to work with. The strong typing feature is especially useful in large data applications and is a feature that is well-worth the developer’s time in avoiding trivial unit test writing and in maintaining the code base of applications.
  7. Scala in JVM: Heavy data applications make learning Scala easier when you code in Java. The Scala framework is awesome since it provides data science support and other frameworks of the likes of Spark can be built atop it.
  8. Provides jobs: Other than the SQL requirements, it is Java that is most popular in the job-space as per the chart indexed below. All the more reason to learn data science and Java for developers!
  9. Scalability: Application scaling in Java is rapid and excellent making it the developer’s choice for writing complex and larger AI ML applications. Especially so if you are writing the program ground-up since then you only need the one language of Java coding.
  10. Speed: Java is fast and provides for fast integration in heavy large-scale applications. The likes of LinkedIn, Facebook and Twitter rely on Java for heavy data engineering.

A data scientist/ developer is the one who is the single point of contact for the data itself. They take the data both structured or unstructured and use a wide variety of engineering, statistical, mathematical, and programming skills to spot trends and arrange the data organizing and managing the data to resolve the targeted outcomes. In essence, they are the people the analysts look up to for the data they need to analyze.

Practical skills required:

Let the truth be told, even if you do your master’s or a Ph.D., to be a good and effective data scientist you will need to also garner training for technical skills in:

  • Proficiency in social sciences
  • Programming in R and Python
  • Coding and writing with the Java suite
  • BigData querying  on Hadoop framework
  • Coding and SQL-Databases
  • Apache Spark
  • AI, ML, and Neural networks
  • Visualization of data
  • Working with unstructured data

You could also bolster your knowledge in managing data through online MOOCs, tutorials, and courses. Ensure your training partner for paid courses is a reputed institute like Imarticus Learning as they offer to train you for professional certifications and also award certifications that are valued in the industry.

Conclusion:

If you’re an analyst, Data Scientist, Deep Learning or ML Engineer the Java skill quotient is worth improving when you are eyeing lucrative and in-demand development jobs. You should learn data science and Java at Imarticus Learning if you want to stay ahead of the job-curve.

For more detailed information regarding this and for further career counseling, you can also contact us through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Bangalore, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

Sandeep’s Review of Imarticus’ Data Science Course

Posted on by Imarticus Learning

We caught up with Sandeep, a recent graduate of the Post Graduate program in Analytics, for a quick chat to get his perspective on the program, the curriculum, Imarticus Learning’s placement process and more.
Tell us a little bit about yourself.

Sandeep: My name is Sandeep Singh. I recently completed my B.Sc. in Computer Science and was looking for an avenue to enhance my analytics skills and start my career.

Data Science Course in MumbaiI came across Imarticus’ data science course and, after thorough research, decided to enroll for it. I completed the course and have been placed at M Technologies through Imarticus.

How has your experience been with Imarticus Learning?
Sandeep: My experience with Imarticus Learning was super! The course focused on practical training with hands-on learning of various analytical tools and thorough practice with numerous datasets.

Looking back, I see the importance of actually applying Analytical tools and techniques to the projects I worked on because it gave me a running start when I began working.

What has changed since you joined Imarticus Learning?
Sandeep: Since the day I joined Imarticus my confidence has been boosted to a very high level. Through the practice of various analytical tools such as R, Python, SAS, Tableau, etc. I’ve come to believe in myself. My soft skills have also been elevated with the help of business communication workshops, mock interviews, and soft skill sessions throughout the course.

Would you recommend the program to someone else?
Sandeep: While researching various institutes, I came across some reviews that say Imarticus Learning is fake. Well, I wanted to see for myself and now that I have, I would definitely recommend Imarticus. If you’re looking for an institute, the first thing that comes to mind is the faculty and the learning material.

The faculty and staff are very cooperative and help you both inside and outside the classroom. The learning material is extensive and covers every aspect of data analytics. The best part is all of the lectures, notes, datasets, and quizzes are stored in an online Learning Management system and is available to students anytime, anywhere.

What do you like most about Imarticus?
The best thing about Imarticus Learning was the course content, the cooperative staff and the informative notes that are easily accessible. The resume building workshops and mock interviews definitely prepared me for the placement drives and I was able to crack the interview and land a job at M Technologies.

Looking to get started on your data science career, Speak with a counselor and get matched with the best course for you.

How Can You Start Learning Data Science and Become a Master in it?

Posted on by Imarticus Learning

 

Being a new and fast-growing field, Data Science is in desperate need of skilled individuals. With lucrative opportunities and pay scales, enterprises around the globe have been in search of skilful professionals to work for them.

You too can make use of this possibility and have a career of your dreams. But becoming a data scientist isn’t an overnight thing. It takes time and effort. So, How do we start to learn data science at right foot? We will find out.

Following are the few steps you could follow to learn data science.

  1. Find If Its Right for You
    Before fixing on to this career choice, you have to make sure you are totally interested in this. You can ask following questions yourself to find if its right for you.
    • Do you really enjoy programming and statistics?
    • Are you willing to work in a field where you have to learn about the new techniques and technologies constantly?
    • Are you okay with job titles like Data Analyst, business analyst etc. ?
    If you have yes for an answer, then you can start learning Data Science right away.
  2. Mathematics
    You have to get familiar with a few topics in Maths in order to conquer data science. The main topic you need to study are the following
    • Probability – A lot of data science works are based attempting to measure the probability of events. Textbooks are a good source of information for this subject.
    • Statistics – This branch of mathematics deals with interpreting and analyzing the data. Fortunately, great textbooks are available online for you to refer.
    • Linear Algebra – This branch of maths covers the study of vector spaces and linear mapping among this space. Linear algebra is a must to understand how machine learning algorithms work.
    Once you are familiar with programming and various libraries, you may not have to dive deep into these mathematical details. But to understand them properly, you will need a sound base in these mathematical topics.
  3. The Programming
    Data Science community has chosen Python and R as their primary languages for programming due to various advantages. You have to learn and practice programming in these two languages at least for the following topics.
    • Data Analysis – NumPy and Pandas, are the two common libraries used for data analysis in Python. Tidyverse is a popular compilation of packages in R for data analysis.
    • Data Visualization – Matplotlib is the most used data visualization tool in Python. The most popular plotting library in R is ggplot2.
    • Machine Learning – Python mostly make use of SciKit-learn library to do the machine learning works. When it comes to R, it offers a huge variety of packages including CARET, PARTY, random forest and many other.
    When you complete these steps, you have a solid base required for a Data Scientist. Even if you find it hard to learn all this stuff on your own, the courses on data science prodegree by Imarticus is available to help you master the Data Science. The course provides comprehensive coverage of statistics and data science along with hands-on training on the leading analytical tools. so, stop wasting your time start preparing for your data science career right away.

7 Reasons Owning Data Science Will Change Your Life!

Posted on by Imarticus Learning

Data Science is paving the way for a new future, but how much do we understand about the career of a data scientist? How much have we learnt about courses which help us learn data science? Or a data science salary?

Data Analytics is proving to be a complete breakthrough which is changing how industries work, and not just on a technological level, but on a very basic operational level too. In just a few years, it has emerged as the most incredible and lucrative career option. You might opt to learn data science, but you must know what it entails.

A data science program, even a data science online course mainly trains tech enthusiasts to process an immense amounts of jumbled up data extract information out of them, and to draw comprehensive information out of them.

From politics to retail to technology, data science is making companies equipped to cope with the access to data they have in the age of information technology. A data science salary is so high, mainly because with time it is emerging to be the strongest asset of companies. Amazon, Google, Microsoft and all the other corporate giants are spending millions of dollars to create a highly functioning data science team, and are even encouraging their employees to learn data science. Here’s why getting into data science will change your life.

Incredible career opportunities

Major tech giants have woken up to the truth that the smartest way to gather, process, understand and make a productive use of data in the age of IT is by having a strong data analytics team, with a specialized skill set. If you take a look at any leading job portals, you will see thousand of recruitment postings which are specifically looking for people who have undergone a data science program or even a data science online course. With the increasing demand of people in this field, it is no wonder that more and more young people are being driven to learn data science.

It’s all about big money

According to a survey by Indeed, an average data analyst earns something around $64,483 a year. And with the increased demand of data scientists in the corporate sector, young professionals will be able to negotiate a substantial hike in their salary, as the supply of good data analysts still remains low.

You can be choosy

If you do study data science you will be spoilt for choice when it comes to your field of interest, and eventually, when it comes to choosing a career, you can choose from titles like Big data engineer, Data analyst consultant, or an analytics specialist.

You’ll get to be irreplaceable

You must understand how lucrative the branch of data analytics is right now, and how much it is valued in the corporate market. As a data analyst or engineer you will be part of the most essential team in your company, and will be able to weigh in on the bigger operations and key assignments.

You might explore a new revenue source

One of the most fulfilling accomplishments is when you study data and interpret them to figure out a way for you company to make more profits, or cut some losses. In the age of IT, there are so many undiscovered options to raise revenues and ways to get more economical. You or your team can be responsible for this.

You might get to work in AI

Artificial intelligence is making use of data analytics now more than ever. Most tech enthusiasts aspire to work in AI someday. You must know that the data analytics boom has changed the face of AI completely, and it is becoming a bigger reality for the industries. More and more companies are focusing on AI and data science is making a huge difference in its operation.

A major priority

Did you know that 77% of successful companies around the world consider data analytics to be a crucial factor which affects their productivity? And as more and more companies wake up to the need for analytics, the competition and the market will only get better for anyone with a career in data science.