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How can a fresher start the career in Data Science ?

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How can a fresher start the career in Data Science

How can a fresher start a career in Data Science The demand for data scientists is developing exponentially, specifically in sectors like BFSI (Banking, Financial Services and Insurance), Energy, Pharma, ECommerce to name a few. Day-to-day evolution in technology and the generation of massive quantities of data have caused the excessive demand for Data Scientists throughout the globe. The significance of collecting and gathering data is critical because it allows organizations to decide and as a result impact the trends in a specific industry. Data Science course in Pune encompasses many breakthrough technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and Deep Learning to name a few. The development and technological trends in data science have improved its effect throughout each industry. What is Data Science?  Data Science may be described as a multi-disciplinary tool that extracts insights from structured and unstructured data using scientific methods, processes, algorithms, and systems. In technical language, Data Science unifies statistics, data analysis, and machine learning to recognize and examine actual phenomena via data. Data Science can’t be taken into consideration as a totally technical tool because it employs strategies and theories from fields which include mathematics and statistics together with computer science and information technology. The important three components concerned in data science are organising, packaging and delivering data. Data Science analyses data and the outcomes of that evaluation are used to attract conclusions and make choices on it. What are the future prospects of Data Science?  The use of data analytics in nearly every industry has contributed to a pointy growth of 45% in the overall jobs associated with data science last year. The developing demand for data scientists will come up with a concept about the scope of Data Science in India. Here are a few main industries with an excessive demand for data scientists.   Ecommerce-  E-commerce and retail are some of the most applicable industries that require data evaluation at the most important level. The powerful implementation of data evaluation will assist the e-commerce organizations to expect the purchases, profits, losses or even manage clients into buying matters by monitoring their behaviour. Retail manufacturers analyse client profiles and based on the results, they market the relevant products to push the client towards purchasing.   Manufacturing- Data Science is utilized in manufacturing for plenty of reasons. The main use of data science in production is to have an effect on productivity, minimise risk, and growth profit. Following are the few regions wherein Data Science may be used to enhance productivity, strategies and expect the trends:   Performance, quality assurance, and defect tracking Predictive and conditional maintenance Demand and throughput forecasting Supply chain and dealer relations Global market pricing Automation and the layout of latest facilities New methods and substances for product improvement and production techniques Sustainability and more energy efficiency   Banking & finance- The banking industry has been evolving rapidly. Banks had been a number of the earliest adopters of data technology for processes and security. Banks are the usage of the technology to recognize their clients, maintain them, and feature new ones as well. Data evaluation is assisting financial establishments to have interaction with clients more meaningfully by knowing their transactional patterns. The data of transactions to be had to banks is utilized in risk and fraud control. The introduction of data science has brought about higher management of each client’s personal data. Banks are starting to recognize the significance of collating and utilizing not only the debit and credit score transactions however additionally buy history and patterns, mode of communication, Internet banking data, social media, and mobile phone usage.     Healthcare- Electronic medical records, billing, scientific systems, data from wearables, and numerous portions maintain to churn out massive volumes of data each day. This offers a precious opportunity for healthcare companies to make certain higher patient care powered by actionable insights from preceding patient facts. Of course, data science is making it happen. Data scientists internationally are progressively revolutionising the healthcare industry. From enhancing care delivery to accomplishing operational experience, they’re operating to optimise every factor of healthcare operation by unlocking the ability of data.     Transport- The transportation industry creates remarkable quantities of data daily. Most of the data in the industry is captured thru passenger counting systems, automobile area systems, ticketing, and fare collection systems, and scheduling and asset management systems. The use of Data Sciences consists of the exceptional ability to derive insights into making plans and dealing with transportation networks. Insights from this captured data are considerable to gain an aggressive advantage, enhance provider reliability, and mitigate risks.   Different Data Science Roles To name a few, a number of the most common job titles for data scientists include:   Business intelligence Analyst- ABI analyst makes use of data to assist figure out market and business trends by analyzing data to expand a clearer picture of wherein the organization stands. Data mining engineer- The data mining engineer examines not only the data for his or her own business however also that of 1/3 parties. In addition to analyzing data, a data mining engineer will create sophisticated algorithms to assist analyze the data further. Data architect- Data architects work intently with users, system designers, and developers to create blueprints that data management structures use to centralize, integrate, maintain, and protect data sources. Data scientists- Data scientists start by translating a business case into an analytics agenda, growing hypotheses, and understanding data—in addition to exploring patterns to measure what effect they’ll have on businesses. They additionally discover and select algorithms to assist further examine data. They use business analytics not only to give an explanation for what impact the data is going to have on an organization in the future, but also can assist devise solutions in order to assist the organization to move forward. Senior Data scientist- A senior data scientist can assume what a business’s future desires will be. Apart from collecting data, additionally they examine it thoroughly … Read more

How to Improve Data Science Skills?

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Improve Data Science Skills | Ethan's Tech

Data Science Skills – Overview As the demand for data scientists increases, the area offers an engaging profession direction for students and existing professionals. This consists of people who aren’t data scientists however are passionate about data and data science, which has left them asking about what data science skills and huge data skills are had to pursue careers in data science. Data science requires a numerous set of skills. It is an interdisciplinary area that attracts on components of science, math, computer science, enterprise and communication. Data scientists might also additionally advantage from a numerous skill-set that allows them to both crunch the numbers and successfully impact decisions. Top 6 Skills Required to Master Data Science in 2021 The area of data science comes with a steep learning curve. Data scientists want to master essential programming languages and statistical computations, in addition to strong communication and interpersonal skills. Aside from a strong basis in mathematics and statistics, data scientists want to be literate in sophisticated statistical modeling software program and feature a stable knowledge and understanding of programming. Skills required to master Data Science in 2021 are as follows: 1. Python Coding Python is the most common coding language I generally see required in data science roles, together with Java, Perl, or C/C++. Python is a splendid programming language for data scientists. This is why 40 percentage of respondents surveyed by O’Reilly use Python as their fundamental programming language. Because of its versatility, you could use Python for almost all of the steps concerned in data science processes. It can take numerous formats of data and you could effortlessly import SQL tables into your code. It permits you to create datasets and you may actually locate any sort of dataset you want on Google. 2. SQL Database/Coding SQL (structured query language) is a programming language that permit you to to perform operations like add, delete and extract data from a database. It can also assist you to perform analytical functions and rework database structures. You want to be proficient in SQL as a data scientist. This is due to the fact SQL is particularly designed that will help you access, talk and work on data. It gives you insights while you operate it to question a database. It has concise instructions that permit you to to save time and reduce the quantity of programming you want to carry out tough queries. Learning SQL will assist you to higher recognize relational databases and improve your profile as a data scientist. 3. Machine Learning and AI A massive variety of data scientists aren’t proficient in machine learning regions and techniques. This consists of neural networks, reinforcement learning, adversarial learning, etc. If you need to stand out from other data scientists, you want to realize Machine learning techniques which include supervised machine learning, decision trees, logistic regression etc. These abilities will assist you to solve different data science issues which are based on predictions of essential organizational outcomes. Data science desires the application of abilities in different regions of machine learning. Kaggle, in one of its surveys, discovered that a small percent of data experts are capable in superior machine learning abilities including Supervised machine learning, Unsupervised machine learning, Time series, Natural language processing, Outlier detection, Computer vision, Recommendation engines, Survival analysis, Reinforcement learning, and Adversarial learning. 4. Data Visualization The business world produces a massive quantity of data frequently. This data desires to be translated right into a layout in order to be easy to comprehend. People certainly recognize pictures in sorts of charts and graphs more than raw data. An idiom says “A picture is really well worth a thousand words”. As a data scientist, you ought to be capable of visualize data with the resource of data visualization tools inclusive of ggplot, d3.js and Matplottlib, and Tableau. These tools will assist you to transform complex outcomes out of your projects to a layout in order to be easy to comprehend. The factor is, plenty of people do not understand serial correlation or p values.  You want to reveal them visually what the ones terms represent to your outcomes. 5. Unstructured Data It is crucial that a data scientist be capable of work with unstructured data. Unstructured data are undefined content that doesn’t suit into database tables. Examples consist of videos, blog posts, client reviews, social media posts, video feeds, audio etc.  They are heavy texts lumped together. Sorting these form of data is tough due to the fact they’re now no longer streamlined. Most people mentioned unstructured data as ‘dark analytics” due to its complexity. Working with unstructured data lets you resolve insights that may be beneficial for decision making. As a data scientist, you ought to have the ability to recognize and manage unstructured data from different platforms. 6. Deep Learning It is a sophisticated form of Machine Learning. Nowadays, each company is deploying Deep Learning models because it possesses the ability to solve obstacles of traditional Machine Learning approaches. Other skills for Data Scientist jobs consist of basics of Neural Networks, the library used for developing Deep Learning fashions like Tensorflow or Keras, and the way Convolutional Neural Networks, Recurrent Neural Networks, and RBM and Autoencoders work.  7 Ways to Improve Your Data Science Skill Data Science is one of the most up to date jobs in the tech industry and a totally beneficial profession choice for individuals who need to step into the sector of Big Data. A data scientist is anticipated to be a ‘jack of all trades,’ be continuously learning, and evolving in their craft. Data scientists use numbers and statistics to make real-world selections and translate business requirements.  It’s clear there’s a large demand for experts however the problem is finding them. If you’re looking to enhance your data scientist skills and stick out from the competition, here is your roadmap to getting better fast. 1. Take an Online Data Science Course The current education system in India could be very different, … Read more

15 Must-Have Skills to Become a Data Scientist

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15 Must-Have Skills to Become a Data Scientist

Data Scientist Skills – Overview Data science is a niche field that is steadily growing in popularity and demand. With India set to become the world’s analytics hub, many students are pursuing education and careers in data science. Even professionals from other streams are taking up data science to switch or boost their careers. However, data science is a different subject compared to conventional education. Therefore, you need to have certain skills to do well in this subject. You may possess some of these skills naturally, but even if you don’t, you can work on them and develop yourself into an ideal candidate for data science. The right skills can ensure that you thrive in your education and career, and take advantage of one of the fastest-growing industries in India. Required Educational Qualifications to Become a Data Scientist To become a data scientist, you need formal education in this subject. Right now, many students are opting for data science, but many government universities and institutes still don’t have good data science courses. This sphere is dominated by private institutes that have strong data science certificate, diploma, and degree courses. Once you finish your data science training in Pune at a reputed educational institute, you can pursue a career as a data scientist. Important Skills Required for Data Scientists? Data scientists are one of the most important and highest-paying progressions of the digital age. Not everyone can simply just decide to pursue this career. You need to have certain technical and soft skills. It is important to know about them before you decide to pursue data science. Here are the required data scientist skillset of technical & soft skills: A) Data Scientist Skills: Technical Skills Data science will test your technical skills to the limit as this subject involves the use of a lot of technology. Here are the top 15 technical skills required to become a data scientist: 1. Fundamentals Fundamentals are the basics. So, if you want to become a data scientist, you need to know the fundamentals well. Apart from common terminologies, you need to have some working knowledge of Database Basics, Relational Algebra, Matrices & Linear Algebra Functions, Extract Transform Load, Hash Functions & Binary Tree. You also need to know the difference between machine learning and deep learning, supervised and unsupervised learning, and data science, data engineering, and business analytics. These are all things you can learn on your own, so get learning now. 2. Programming Skills You need to have programming skills to become a data scientist. From developing data models to creating analytical models, many functions in data science require programming, so knowing one or more programming languages is going to be important. However, knowing just any programming language isn’t going to help. You need to know either Python, R, Java, or SQL if you want to do well in data science. You can also benefit from knowing about programming packages and libraries like TensorFlow. 3. Statistics & Math Data science is not just about coding. If it was, any coder could have become a data scientist. Data science is about statistics and mathematics. Only if you understand them well, will you be able to use them correctly to develop data models with accurate assumptions. You can also derive accurate conclusions with statistical and mathematical knowledge. If you have already studied these subjects and have good knowledge of them, you can consider becoming a data scientist. 4. Data Manipulation Data manipulation is one of the key skills required to become a data scientist. You will need to organise, arrange, and change data to make it readable. This is important because the raw data received will not make sense. It needs to be manipulated. Data scientists use data manipulation languages (DML). If you have the opportunity to learn these languages in advance, it will help you in your quest to become a data scientist.  5. Data Analysis The raw data, once processed and manipulated, needs to be analysed. This is one of the most important steps in the whole process. Without analysing the data, you will not be able to derive sense and meaning. You have to spot patterns, discrepancies, and anomalies in unstructured data for which you need to have an analytical viewpoint. You also need to have the ability to go through vast amounts of data without missing important details. 6. Data Visualization Data visualization is the ability to create a visual representation of the results. You should have skills to create accurate and easy-to-understand graphical representations like pie charts, bar graphs, and histograms. These graphical representations are important if you want to have a career in data science. If you have had experience making them, you will have a much easier time using graphical tools like Datawrapper, Tableau, Kibana, and Google Charts. 7. Machine Learning & AI Machine Learning (ML) and Artificial Intelligence (AI) are important aspects of data science. Therefore, if you have skills pertaining to these two subjects, becoming a data scientist will be a lot easier. If you have degrees or certifications in ML or AI, you can pursue data science. Even if you don’t, but have enough knowledge related to the subjects, you can still pursue data science as you will get an opportunity to learn about these subjects if you choose the right course. 8. Big Data Another important aspect of data science is Big Data. Both data science and big data go hand-in-hand when it comes to creating data and reports that help businesses make informed decisions based on the findings. Everything we do in the digital sphere generates torrents of data. Therefore, if you have professional qualifications in big data, you can choose to pursue data science and get an even better career. Big data is not just a buzzword, it is one of the most important aspects of the digital future. 9. Deep Learning Deep learning is different from machine learning. Machine learning tends to have a few limitations, whereas, deep learning does … Read more

Data Science vs Machine Learning and Artificial Intelligence

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With the growing importance of data in every sector, terms like data science, artificial intelligence and machine learning have become new buzzwords. People often get confused and use them interchangeably which is wrong. These terms are interconnected but not interchangeable. There are some overlaps in the applications but each term has its own specific usage in the businesses. In this blog we will try to explain the meanings and applications of data science, machine learning and artificial intelligence. Whether you are from IT or non-IT background, you will have a clearer understanding of the terms by the end of the blog.                   Let’s have a quick look at these three terms before diving in the differences and uses. What is Data Science? Data science is used by the companies to get new results from the data. Data Science works with both structured as well as unstructured data. It involves every process related to data- data selecting, preparing, and analysing. It uses various techniques involving statistics, mathematics, and programming to extract meaningful insights and patterns from the large volumes of raw data that are relevant for the businesses. Among all three AI, ML and Data Science, data science is the most widely used technique. Data has become revenue in today’s world as more data can help the organization in generating more business insights. Companies are building recommendation engines using data science that can predict user behaviour. Accurate results can be achieved by applying various algorithms to the vast amount of data available. The more the data, more accurate the results that companies can get. What is Machine Learning? Machine learning is the science that aspires to enable computers to process new data input without explicit programming, based on the learned prototype. It aims at preparing machines to act and learn like humans, where the learning can be improved over the time in a self-sufficient way i.e., without feeding them manual categorical instructions to perform a specific task. In ML, data is fed to the standard algorithm, and the machine builds the logic of its own through that information. No code-writing is involved to perform tasks. In other words, ML is about making machines learn to program themselves. ML helps in making programs scalable with better output results in shorter period of time. But the question that comes to most of us is: how do we make a machine learn? There are three different approaches used 1. Supervised 2. Unsupervised 3. Reinforcement learning In supervised approach, machine uses labelled data to recognize the characteristics for future outputs. In unsupervised approach, unlabelled data is simply put and the machine understands and classify according the characteristics. For eg if we want to classify between birds and animals, supervised approach will provide some labelled pictures and then machine will classify the rest of the data while in unsupervised approach, data will be provided and the machine will classify it without any labelled data provided. In reinforcement approach, machine tries to learn algorithms by analysing the rewards and errors produced by the actions performed like the game of chess. With the help of Machine learning, recommendation engines would not be possible as it is not realistically possible on a human level to go through millions of reviews, likes and search queries to determine the favourites of the customers. What is Artificial Intelligence? Artificial Intelligence can be referred to the imitation of human brain functions by machines. AI focusses on creating machines to do logical reasoning, learning, and self-correction like humans do. The apps that can play games to the speech recognizing devices like Alexa- all are related to AI. Devices are trained to solve problems and learn in a better way than humans can. It is accomplished with the help of artificial neural network created to replicate human intelligence. AI is one of the most complicated technology with lots of computing required. Artificial intelligence is categorised into two parts- General AI and Narrow AI. AI can be described as a vast collection of algorithms(mathematical) to help device establish relationships between the bits of data provided in such a way that this information can be used to derive accurate decisions. Here it should be taken in account that data provided should be enough. If the data provided will not be enough then the accuracy can be low for the predictions provided. Artificial Intelligence needs data to learn and make accurate decisions, hence more the data available, more accurate the predictions/decisions provided will be. Also, the data provided should be accurate as AI focusses on self-correction.  Data Science vs Machine Learning vs Artificial Intelligence   Data Science          Machine Learning   Artificial Intelligence Data Operations are included Data Science collects, analyse and processes data to obtain information. DS uses both structured as well as unstructured data. Popular tools used are Apache and Tableau. Healthcare Analysis is an example. It is a subsection of Artificial Intelligence   ML feed data to the algorithms to perform explicit tasks without writing codes for the specific tasks.     Statistical models are used by Machine learning.   Popular tools used are Lex and ML Studio.     Recommendation systems like Spotify is an example. It includes ML   AI uses vast amount of data through mathematical algorithms to make devices learn automatically.     Decision trees and logics are used by Artificial Intelligence.   Popular tools used are TensorFlow and Keras.     Chatbots is an example. Data Science vs Machine Learning and Artificial Intelligence: Skills Required Some of the required skills for the job as a data analyst, data scientist or data engineer that can help you stand ahead from the peers are data visualisation, data reporting, programming, risk analysis, and data warehousing. Some of the skills required to grab the best jobs available in the market in ML and AI are programming language like c++ and python, ML algorithms, probability, Distributed computing, statistics and data evaluation. From the skill set … Read more

A Complete Guide: How to Start a Career in Data Science?

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Starting a Career in Data Science? In the modern era, starting a career is not that difficult thanks to various colleges, institutions, and universities that have adopted Data Science in their regular curriculum. Moreover, due to the presence of online classes, several students as well as working professionals are getting their certification from reputed professional training institutes and are enjoying a prosperous career in the domain of data science. A career in data science is highly rewarding as various industries are hiring professionals who are great in data analysis and are proficient in similar stuff. Top HRs and recruiters are on a constant lookout for skilled data science professionals. Did you know – according to Forbes Data Scientist is one of the hottest jobs of the 21st century? If you are planning to start a career in Data Science this is the best time as Naurki.com has 19375 jobs available for candidates in their portal. You will be glad to know that the U.S. Bureau of Labor Statistics predicts strong growth in the role of the data science field and states that the number of jobs will increase by about 28% through 2026. The scope of data science is huge as every SMB and enterprise wants to know what to do with the data that is available to them; how to process it and convert it into useful information. Related Blog: What is Data Science: A Comprehensive Guide for Beginners 15 Tips to Start a Career in Data Science Do you want to start a data science? Are you willing to take the charge in your hand and take your career to a whole new level? Have you got stuck in your current job position and want to power ahead your career? If yes, then you have come to the right place as we are going to see 15 tips to start a career in data science. Starting a career in data science depends on myriads of facts and we are going to see them all in brief. There is a slight margin between good and great data scientists and if you are going to follow the below 15 points then no one can stop you from being one of the best data scientists in the world. With the acquired skills you can revolutionize any industry and everyone will welcome you with open arms and hearts. Here are the 15 tips to start a career in data science:  1. Hone Your Mathematical Skills It is a rule of thumb that every data scientist must be good at mathematics so it is quite pivotal that every data scientist must start polishing their mathematical skills. A data scientist will have to analyze data and convert it into actionable insight; collect vast data and organize them into a structured format. Data science is all about finding patterns and it can be achieved only with the help of a strong foundation in math. 2. Learn Python, R, and SQL To become a great data scientist knowledge of certain programming languages as well as databases is compulsory. Learn Python, SQL, and R and prove that you possess all the skills and knowledge required to become an asset to an organization. With these aforementioned programming languages and a firm knowledge of databases, you can easily start working with a private or public sector organization. These programming languages will make you an outstanding coder and will assist to boost your statistical computational skills. 3. Do Internships Doing an internship is a great way to acquire relevant data scientist skills. Many candidates think that they will not get paid during the internship but that’s not the point at all; gaining skill is! Go for an internship in an MNC or even a startup organization to know how an organization works within departments and skyrocket your hands-on experience via practical knowledge. Prepare well by practicing a lot before the interview as this will be the deciding factor for your career. With an internship, you will have the opportunity to solve real-world problems, and also you will get real-time feedback on your performance which is necessary to boost your confidence if you want to become a very good data scientist. 4. Go for Professional Training Enrolling yourself in a reputed professional training institute is highly recommended if you want to attain skills and knowledge that will make you a great data scientist. A professional training institute has mentors and instructors that are willing to make you learn data science with their huge experience. These professional training institutes teach you the basics and advanced concepts of data science via real-life examples and projects which go beyond the typical classroom approach. Also, you will be given a reputed and valuable certification once you have successfully completed the data science training. 5. Begin as a Data Analyst Numerous candidates think that data scientists and data analysts are the same but that’s a myth. It is advisable that you should start working as a data analyst and once you have gained enough experience and knowledge then you can move towards being a data scientist. A data analyst’s role is to manage data collection and perform identification of dataset trends; they might not be involved with the coding part. But a data scientist has to be well-versed with coding concepts as well as we have already seen that in point no. 2. 6. Create a Strong Network By creating a strong network we mean to say that you should create a strong connection with people who are already working as a data scientist. Why? It is because doing so will help you gain knowledge in this niche and also they can help you recommend their respective organizations for the job role of a data scientist if they have vacancies. Through your network, you can seek assistance if you are stuck in any project or simply if you want to clear your doubts. You should join online communities, groups, and forums because their people are always willing to help each other. … Read more

What is Data Science: A Comprehensive Guide for Beginners

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In this blog, you will have all the information you need to know about data science. From what data science is all about to the various data science courses to the skills required for data science, the following is a comprehensive guide for beginners who are thinking of education and a career in data science. What is Data Science? Data science is the study and processing of data and analytics through technologically advanced methods like software and tools powered by machine learning. It allows us to gain an insightful look into data and derive meaningful information that will help in making predictive models that can be used to make smart business decisions. Data science helps us tap into the power of data in a big way. Thanks to widespread digitisation, today, humans produce a vast amount of data through their daily routine. This data can be used to make life better. Companies can use this data to drive innovation and market the right products and services. Governments can use it to become efficient and make their citizens’ lives safer. The applications are vast, and the possibilities arising from them are innumerable. Therefore, data science has emerged as the fastest rising subject of education in the world. Data Science With Example The best way to understand something is by seeing a live example in action. Similarly, you will truly understand the importance and application of data science through a live example that you might be familiar with, but not know that it is being powered by data science. Here are some excellent data science examples:  1. Netflix – One of the biggest platforms that makes use of data science is Netflix. In network television, only 35% of TV shows get renewed for a second season, whereas, in 2017, 93% of Netflix’s shows got renewed for a second season. This decision was possible through the use of data science. The superhit show Stranger Things was renewed for a second season only after a thorough study of its data analytics. Needless to say, the second season was also successful. 2. Amazon – eCommerce giant, Amazon, employs the best data scientists in the world to improve sales and user experience. Once you search for a product, you start seeing ads related to that product. You even get updates on alternate products, related products, and price drops. This is possible through data science. The data you generate through online shopping is used to optimise your shopping experience. You are even shown products according to the region you live in. That’s how detailed data science can get. Data Science Goals and Deliverables The foremost goal of data science is to improve business decisions. Data science gives such an in-depth look into data that one can make near-accurate predictions based on this data. These predictions can be used to negate risks, improve user experience, drive innovation of products & services, and increase profits. Data science is going to make lives better and safer. It has applications in all aspects of our lives. It will make healthcare and medicines better and more efficient. Technology will evolve faster. Industries will function better. There will be more jobs, but lesser working hours. Commutes will become more efficient and safer. Mankind will have a better understanding of the world and universe. Data science is going to make every aspect of human life better. Why Data Science? Data science is not a passing trend. It is an important subject that is going to be a permanent feature in education and business. But you still need to have strong reasons to pursue this field because data science is a specialized field. Here are some reasons that are answers to the question, why data science is important: Data science is the fastest rising field in education all over the world. The best universities and institutes in the country and world have introduced full-time data science courses at the undergraduate and postgraduate levels. Currently, data scientists find themselves amongst the highest-paid professionals in the world. Data scientists are making INR 12.6 lakhs annually which is even better than software engineers, and this figure is going to get even better. Data science is a field like no other. It is one of the most technologically advanced and challenging fields in the world, meaning, there are not going to be any dull moments in data science careers. Just in the past decade, many fields of education and careers have become irrelevant, but this won’t happen to data science. The demand for data scientists is only going to get higher. If you want to work overseas and find high-paying jobs in multinational companies, data science is the best way to achieve that because data scientists are in huge demand in the international market. Components of Data Science To truly understand data science, you need to know about the components of data science. Each component is like a gear and their functioning is dependent on each other. Therefore, knowing about these components will help you understand data science as a whole: 1. Statistics The collection and arranging of numerical data and analysing it and deciphering important findings is statistics. Numbers are an important part of data science as it uses many statistical models for analysis and predictions. Accurate recording and analysis of statistics are one of the most integral parts of data science. 2. Data Engineering Once the data has been acquired, it needs to be properly stored, retrieved, and processed. This is where data engineering comes to the fore. How, when, where, and what needs to be done with the data is all a part of data engineering. Data engineering also deals with metadata. 3. Domain Expertise Data science is always used to process data of a particular domain and for this, input from a domain expert is needed. Domain expertise brings data science together and gives it a direction, and lets you decide how to best make use of all the insightful findings. 4. Advanced Computing … Read more

Top Technical Skills to get hired in 2023

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The technological industry is developing quickly. Technology abilities that were once thought to be evergreen are now out of date. Technology’s ongoing development is creating new job opportunities that are in high demand for people with technical expertise. The projections predict a 12% increase in IT employment by 2024, which means that IT experts will have access to an increasing number of jobs.  Even though there is a tonne of job openings and few qualified professionals, there is fierce competition for high-paying positions. To stand out and land high-paying tech jobs in 2023, one needs to have some of the most in-demand tech skills. After graduation, when you begin to map out your career alternatives — what industry you want to work in, what further certifications you’ll need for it, etc. — is one of the most important periods in one’s professional life. Nowadays, there are so many options available that it’s normal to feel confused about which course is best for you to take and will help you land one of the highest-paying professions available. Money, career advancement, and work security are the main factors influencing people’s career decisions. And if these are significant considerations for you as well, this essay will assist you in choosing your next course of action. Here is a selection of the best career-focused programmes you might want to look into! Let’s discuss the top qualifications needed to land the best jobs in India. Tech skills that are hot commodities among employees Programming The process of designing and creating a computer programme to carry out a given task is known as programming. Coding, commonly referred to as programming, has always been a crucial tech skill in the world of technology and can help you take advantage of a plethora of job prospects. JavaScript, Java, and Python are the three most popular coding languages on the market today.  Compared to C and C++, Python is a high-level language that is fairly simple to learn. Python’s user-friendly design has helped it become incredibly popular. It is perfect for both beginners and experienced. According to the TIOBE index, it was ranked third on the popularity chart. A Python specialist typically makes around 5 lakh rupees per year in compensation.  There are no prerequisites that must be met before beginning a Python course. It is regarded as being simpler than c and c++, making it a great option for beginners in both IT and non-IT sectors.  One of the top universities in Pune offering python courses is EthansTech. The course material is structured so that it begins with the fundamentals of Python programming and progresses to more complex ideas. Following the completion of the programme, Ethan’s also offers 100% placement support. Data Science Data science is the process of extracting information and practical insights from the mind-boggling amount of data that an organisation has access to, utilising a variety of tools and algorithms to enable data-driven decision-making. Businesses increasingly rely on data to guide their decision-making because they don’t want to fall behind. Nearly every industry, including banking, finance, and healthcare, needs data scientists. Data-driven talents are highly valued, which is why the demand for professions such as business analysts, database administrators, data analysts, and related positions is on the rise. According to LinkedIn, data science will have the fastest job growth in 2017. From 2022, data scientists and analysts will be in high demand, according to a forecast by Future of Jobs. Since the beginning of 2019, the demand for data scientists has increased by almost 40%. Data science occupations are here to stay and are one of the most in-demand IT skills, as seen by the enormous growth in data science jobs. One of the highest-paying professions in data science, and in India, data scientists make an average salary of 7,57,190 annually. Fundamentals of data analysis, data intuition, data storage, and data interpretation to other domains, such as finance, sales, and marketing, are essential for these positions to derive meaningful patterns and information for the firm. Data scientists with strong data visualisation abilities are in high demand.  To begin a career in data science, no coding knowledge is necessary. In Pune, some schools provide precisely crafted data science courses to enable students to pursue profitable careers in the field. Cloud Computing The transmission of computing services such as servers, storage, software, analytics, and intelligence on an as-needed basis over the Internet (the “cloud”) results in widespread accessibility, more inexpensive resources, and quicker operation. The number of businesses moving to the cloud has increased dramatically, demonstrating the enormous expansion in the potential for the cloud computing sector. In 2020, cloud computing will likely be one of the most lucrative IT industries. Engineers who can plan, create, manage, maintain, and support cloud computing will find employment prospects there. The firms provide lucrative packages to cloud computing professionals because they are in charge of managing crucial applications on the cloud platform. According to PayScale, the average annual compensation for a cloud computing engineer in India is about INR 1,830,766.  Google Cloud Platform (GCP), Microsoft Azure, Amazon Web Services (AWS), Java, and Kubernetes are the most in-demand cloud computing technologies. EthansTech provides all the prominent cloud computing courses in Pune. For more info, you can visit AWS course in pune- AWS Training in Pune | AWS Classes in Pune-Course by Experts (website.ethans.co.in/) Azure course in pune- Microsoft Azure Training in Pune | Best Azure classes in Pune by Ethans Tech GCP course in pune- Google Cloud Platform Training in Pune – Ethans Tech Kubernetes course in pune- Kubernetes Course | Training Certification in Pune – CKA|CKD (website.ethans.co.in/)   Internet of things The internet of things (IoT) is a concept that envisions everyday physical objects becoming connected to the internet and having the ability to recognise other devices as their own. IoT is a young area of technology that has the potential to generate a lot of jobs in the future.  Electrical and electronics students would be very helpful in … Read more

Future of Data Science as a Career

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For the ones who don’t know about data science, Let’s start with the most basic question What is Data Science? Data science involves actively examining and unlocking patterns, trends, and insights hidden within data. It encompasses studying data sourced from various channels and leveraging it as a valuable resource to support the dynamic business cycle. Data science employs various statistical techniques, including data transformations, modeling, statistical operations, and machine learning modeling. Statistics stands out as the fundamental skill for every data scientist, as emphasized by instructors in a data science course in Pune. Furthermore, optimization strategies may be employed to meet specific business requirements. For placement opportunities, consider enrolling in a data science course in Pune. What do Data Scientists do? With the use of their data visualization skills, a data scientist improves business decision-making by bringing more speed and better direction to the entire process. Data scientists are far more technical than data analysts. Aspiring data scientists are strongly advised to have great communication skills because they will need to initiate and interact with many teams inside the firm.  Let’s move on to some more crucial discussions of data science-related problems now that we have a better knowledge of data science and data scientists. What does data science hold for the future? Organizations should be able to use all types of data in real time within the next five years. More data will be used by businesses to make critical business choices, which will stimulate the development of new data science models. Accurate forecasting and decision-making will be emphasized by innovations like “Deep Learning.” As more businesses manage data science and analytics teams, the size of the current teams will increase. Although data science positions are beginning to specialize, predictive analytics and data science will soon be combined. The secret to utilizing big data’s limitless potential will be to hire qualified data scientists, business analysts, and statisticians.  Big Data, Big Paycheck Businesses all over the world are quickly adopting digital technology, showing big growth potential. Data is driving this boom. The global market for big data analytics was worth $37.34 billion in 2018 and is expected to grow to $105.08 billion by 2027, with a yearly growth rate of 12.3%. This shows that businesses are committed to using big data analytics. We expect big data analytics to be used a lot more in the future. In recent years, jobs as data scientists and data engineers have been really popular worldwide. Every industry, like healthcare, banking, retail, telecom, and IT, sets up teams for data analysis and happily hires pros in this area. A survey says that by 2021, 70% of business leaders will want employees who are good with data. More and more people are joining data science courses in Pune to improve their skills and grab job opportunities. Jobs involving data pay well because they’re popular and in demand. The data analysis field is always changing, so there aren’t enough trained people, which makes wages go up. Even beginners get paid a lot because there aren’t enough skilled workers, which messes up the balance between supply and demand. Typical yearly salaries for data-connected positions in India are as follows: According to PayScale, the average income for a data scientist in India is 698,412. A novice data scientist with less than a year of experience can expect to earn around $500,000 per year. Those with one to four years of experience typically make about $610,811 per year. Data engineers earn an average of $830,864 per year. Ethans Tech Pune provides data science training led by industry professionals from top MNCs, offering practical job experience. The training involve deeply individuals in real case studies, preparing them to work by yourself on related projects.

6 Reasons to Study Data Science – Ethans

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According to Harvard Business Review, the sexiest job of the twenty-first century is becoming a data scientist.  Two definitions of data science are the study of data generated from various sources and the process of turning it into useful information that can aid in corporate decision-making.. A data scientist is a professional who spends a lot of time working with raw data to extract insightful business information from it. With the use of their data visualization skills, a data scientist improves business decision-making by bringing more speed and better direction to the entire process. Enroll in a data science course for beginners for a promising career path in this thriving field. Here are the reasons why to learn data science: Data is the New Gold Although we have seen a dramatic increase in the amount of data being produced and consumed, collecting data alone renders it worthless. The knowledge produced by this excellent resource is what provides an organisation with the genuine effect necessary for expansion. We have already observed that businesses that have mastered the collection and use of data outperform their rivals.  High Demand In the modern corporate world, firms cannot disregard the usage of data analytics. Due to the enormous amount of data available, data scientists are in high demand. In 2020, there will be a rise of 364,000 to 2,720,000 openings, according to IBM. The demand will only increase, reaching a startling 700,000 openings.  The top position on Glassdoor’s website, according to that company, is data scientist. Future developments will not affect this position. Check out What to Expect from a Data Science Course in Pune: Curriculum Breakdown. It is a “high-demand skill” since the need for data scientists is increasing exponentially. Companies are paying enormous amounts to those with the qualifications to work as data analysts, scientists, engineers, etc. The second-highest nation for hiring workers in the field of data science or data analytics is India. Lucrative Career Choice Professionals in data science make significantly more money than workers in other markets.  In India, a data scientist makes an average pay of Rs 6,99,928, and a data analyst makes an average compensation of Rs 4,04,924. Your income is likely to improve annually by about 15% if you complete a data science course from a reputable institution. Your salary will continue to rise as you get more work experience and skill proficiency.  High Flexibility Numerous new opportunities are emerging as a result of the massive data surge. Data scientists are in high demand across numerous industries, including business, energy, government, healthcare, intelligence, and security. Additionally, as data science has a wide range of applications, you can choose a career path that appeals to your unique interests. According to professionals who offer data science courses in Pune with placement, it’s an exciting moment to think about a career in the field.  Leadership Roles Shortly, businesses will start using data science for a variety of processes, including Project Management. Businesses may make more profitable decisions with less effort by employing data science to comprehend data insights and patterns. Data analysts need to be able to explain complicated results to the organization’s technical staff. Data analysts now play a significant role in the businesses’ decision-making process thanks to these communications, which are crucial. Experts in analytics frequently have great leadership qualities as well.  Artificial Intelligence The field of artificial intelligence is developing. AI has a wide range of current practical applications. Based on prior data, AI continues to learn over time. A well-known example of an intelligence system created combining data science and artificial intelligence is a chatbot. Although the discipline of data science is vast, the rewards are much larger. Today’s world is seeing a rapid evolution of technologies, and to keep up and advance, we must be adaptable.  The best strategy is to enrol in a Data Science course for beginners certification course that is linked with the market. Since we are ISO 9001:2015 certified, the accreditation from well-known organizations like Ethans Tech adds weight if the employer is seeking the finest candidate. Our data science course in Pune accreditation is accepted by numerous prestigious businesses. Join us as you take the first step toward a thrilling and promising future.

Reasons Data Science is the Most Progressive Career of the Future

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The newest buzzword is data science, and the hoopla is not unfounded. There are several arguments in favor of that. Data dominates modern businesses and nearly every aspect of our lives. The demand for data scientists is at an all-time high, and since data is the key component, it is unlikely to decrease any time soon. It will just continue to grow exponentially. Here are a few key arguments for why data science is  the most forward-thinking profession in the next few years. Continue reading: All companies need data scientists for data management  No organization can exist without data management, according to Pune – based institutions that provide data science courses for beginners. Data administration requires the highest level of professional knowledge, proficiency, and accuracy. In recent years, there has been a sharp increase in demand for data scientists. According to Gemalto’s 2018 Data Security Confidence Index, 65% of firms acknowledged that they had not properly classified, managed, and analyzed their data. 89 percent of companies acknowledged that with efficient and competent data management, they could have dominated their market.  Stringent data protection laws  Companies are aware of the effects of data breaches. Laws governing data security are now more strict than ever. Careless data handling is no longer a viable option. Data scientists ensure that data administration and analysis are done in the most secure, responsible, and professional way possible to prevent unauthorized entry. Privacy requirements must be upheld at all costs. In the majority of EU nations, the General Data Protection Regulation (GDPR) came into being.  Data science is constantly evolving  The field of data science is continually developing, and new opportunities are always emerging. According to experts providing data science courses in Pune with placement, it’s a fantastic time to start working in the sector. Data science profiles are becoming increasingly specialized, which is one reason why a data scientist employed by one company could not be performing the same duties as a data scientist employed by another company. That is sufficient evidence of how broad and diversified the data science profession is. Data is growing  As data increases, so does the need for data scientists. You might find it interesting to know that 5 billion individuals use data every day. By 2025, the population is projected to increase by 6 billion. In essence, this represents the population of the entire planet.  I hope this post was helpful. Please contact us if you would like more details about our data science courses in Pune.