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Top 5 Careers in Data Science You Need to Know About!

Posted on by Imarticus Learning

Data Science is a rapidly growing field with over 2.7 million data science and analytics job openings expectations in 2020 alone. The number of online users is increasing at a tremendous rate, and with it, the need for data science professionals is also increasing.

As per reports, 2.5 quintillions bytes of data are produced every single day. And there is a huge demand for professionals who can clean, monitor, visualize this data and obtain valuable insights from it to innovate Big Data solutions for technological advancements.

The field of data science is very wide and offers plenty of job opportunities for professionals. If you are interested in computers, maths, and data analysis and share a passion for technological discoveries, then Data Science is the perfect career for you. By enrolling in a data science course, you can become a qualified data science professional and help transform the world for the better.

What is Data Science?

Data Science is the science that helps in data-driven decision-making using methods of collecting, storing, computing, analyzing, and managing data of organizations. Every technology that we use today is based on data. Our online purchases, YouTube recommendations, Instagram feed, etc. are all examples of human-data interactions.

Data collection helps improve the user experience while surfing the internet. You might have noticed that while shopping on Amazon, the site recommends other useful products that can help you along with your original purchase. These recommendations are based on your previous purchase history, search history, and payment history. It also sends you a reminder for your habitual purchases like groceries, etc. They act as a trigger to make you purchase the product without being spammy.

In this way, Data Science professionals help both businesses and consumers. It is proven to increase a company’s profit revenue and helping customers spend less money on a purchase with strategic placements of ads of products at discounts. Thus, it creates a win-win situation for both the company and the customers leading to healthier economic development.

Benefits of Data Science

Data Science not only has commercial benefits but also improves the performance of multiple industries such as public health, food, farming, education, airlines. From its wearable trackers to monitor and improve patient’s health to accurately diagnosing diseases and finding cures, data science is contributing a lot to the healthcare sector.

Its image and voice recognition applications give you recommendations for tagging your friends in pictures on social media. With Google and Siri, you get the job done without the need to type on your smartphone. Data Science helps the airline industry by predicting flight delays, identifying weather, and helping in decision-making for airplane buying.

Data Science has also transformed the Education Sector with its features, including analytical evaluations of students, helping in decision-making for student admissions, etc. It has been very useful in lowering the dropout rate and increasing the engagement rate of students in schools.

Data Science course helps farmers with solutions on the right amount of seed planting, fertilizer, water, etc. It also predicts weather conditions that let farmers modify their harvesting plans accordingly.

The benefits of data science are countless. It is impacting almost every industry in one way or the other. It has become such an inherent part of our lives that we do not even recognize its presence. It is at the center of all the industries today. Building a career in Data Science is a wise option. It not only pays well but also lets you drive the transformation of the world towards a better version of itself.

There are a lot of in-demand data science careers these days. So, let us explore the top 5 data science careers that you can build a substantial career in.

Top 5 Data Science Careers

1. Data Scientist

Data Scientist is one of the most popular jobs worldwide. Data Scientists examine Big Data and perform cleaning and organizing of the data. They process a large amount of complex information and find patterns in the data that help them drive strategic decisions. Data Scientists are well-versed with Machine Learning algorithms.

The solutions discovered by Data Scientists are very important for companies for their business growth. These solutions also let companies have an edge over their competitors and achieve all their business goals. Data Scientist is a technical job and demands a variety of skills. The salaries in this career are among the highest-paid jobs.

Prerequisites for Data Scientist Job

  • Problem-solving skills
  • Coding Language
  • Data Visualization
  • Business Awareness
  • Machine Learning Algorithms

2. Machine Learning Engineer

Machine Learning Engineers create data funnels of the cleaned and organized data. They train a predictive model to help predict the target variable. Their developed models analyze the data trends in the future to help businesses make the right decisions.

The data used has a lot of dimensions to it. Machine learning algorithms make the tasks easy. These engineers test and analyze their models for the best possible outcomes. They are good with statistics, programming, and software engineering skills. In addition to training, they also do data analysis at times to better understand the datasets.

Prerequisites for Machine Learning Engineer Job

  • Programming
  • Data Modeling
  • Machine Learning Algorithms
  • Software Engineering & Systems Design

3.  Data Engineer

Data Engineers integrate data from various sources and perform batch processing on it. Every company needs the development and maintenance of its data pipelines. Data Engineers collect big data from various sources and then optimize this data as per the problem statements. They are responsible for writing queries and providing a streamlined flow of big data.

They create an interconnected data ecosystem that helps data scientists by making the information easily accessible to them. Their prime focus is on the system and hardware which assist in the analysis of the data. They deliver effective warehouse methods to the organization as well.

Prerequisites for Data Engineer Job

  • Machine Learning Algorithm
  • Coding
  • Data Warehousing
  • Database knowledge

4. Business Intelligence Developer

Though Business Intelligence (BI) Developer is more of a non-technical job, it is a big role to play in the successful implementation of data science solutions in the organization. Before going into the job responsibilities for this role, let us first understand: what is business intelligence? Business Intelligence is a combination of strategies and technologies that helps in the data analysis of an organization for business information.

BI Developers formulate and implement business policies created using the insights from data analysis done by the technical team. They act as a bridge between the technical and the non-technical team through their ability to understand the technical stuff and presenting that in a simple non-technical way to the clients. They have a good understanding of business. Using their deep understanding of data, they develop BI tools and applications that help the end-users comprehend the system.

Prerequisites for Business Intelligence Developer Job

  • Business Acumen
  • Data Warehousing
  • Business Intelligence Software Integration
  • Communication Skills
  • Problem Solving

5. Data Analyst

Data Analyst is another important career in the field of data science. Data Analysts are responsible for understanding, transforming, and manipulating the data to suit the needs of the company. They store the data of the different departments of the company. Data Analysts help companies to understand the reason behind the success or failure of their projects.

Their roles also involve web analytics and A/B testing analysis for businesses. The results of their analysis help companies understand the loopholes in their plans. They provide solutions to business problems and also assist in the decision-making processes. They are also an important link between the technical and other working departments of the company.

Prerequisites for Data Analyst Job

  • Critical Thinking
  • Machine Learning
  • Data Visualization
  • Communication
  • Process Modelling
  • Microsoft Excel

Data Science careers are in constant demand as businesses are quickly moving towards automation. Data Science professionals are needed in almost every field, be it government organizations or private firms. Owing to their high importance, the data science salary packages are also quite lucrative. The average salary range varies from job role to job role in this field. Nevertheless, a career in data science is among the highest paying careers for professionals.

If you are looking to break into the data science field, there are various ways to prepare yourself. One can join a data science course and gain the required knowledge and skill-set for making a career in this field. There are various certificate courses, degrees, and diplomas available these days, both online and offline that you can pursue. After gaining the required qualification and skill base, you can apply for fresher roles in this field.

Many companies are on the lookout to hire data science professionals. So, finding a job would not be that difficult. Once you gain some experience, you can also take on another career pathway in this field as most of the data science careers are interconnected and complementary to each other. To succeed in this field, you need to have a technical mindset, an eagerness to learn, and a passion to develop solutions to problems.

Top Data Science Datasets Project Ideas for Beginners!

Posted on by Imarticus Learning

What is Data Science?

Every company receives too much information about something at a moment which becomes tough to be processed at the same pace. Here is when Data Science comes into the picture.

Data Science is a field of study which deals with gathering massive information about a particular field from various sources and then converting that Big Data into a meaningful output. This data is combined with Machine learning and Artificial Intelligence which all together act as a base for scientific research to take place.

Data Scientists are hired to convert that Big Data into useful conclusions which further assists in lucid Decision Making.

With the advent of technology, everyone is pretty much connected which is the main reason how all the information related to a topic can be made available through the internet. A data science career can open the gate to multiple possibilities.

Data Science Course with Placement in IndiaData Science Datasets Project Ideas for Beginners.

According to a survey, it has been found that by the end of 2020, the demand for Data Scientists will increase by 28%. This is because of the current scenario where everything has shifted to online mode.

Data Scientists can lay their hands on various new topics and elements on the internet which can be the basis for their researches.

Some of the Data Science Projects that can help beginners to build a stronger resume are:

  1. Automated Chatbox Project

Considering the current situation, everything has become internet-based. Renowned companies are also switching to the Chat mode in their Customer Care Departments rather than taking up the calls. Chatting has become way more convenient than any other mode of communication. As far as formal or official communication is concerned, chatting sounds the best.

For a beginner, research on an Automated Chat Box can be really promising and fresh. There can be modifications in the classic chatting pattern in terms of official and formal chatting. For instance: When a company receives so many messages from their customers about certain queries, the automatic chatbox can answer some of the repetitive questions by itself.

This lessens the burden on the employees leading to a better focus on the queries rather than a formal salutation.

  1. Automated Caption Inserter Project

Talking about the current trend, where everyone wants to upload their pictures and photographs on Social Media Platforms, they want their captions to be suitable and trendy.

For a beginner who is aspirant of researching Data Science, this can be something new and likable.

When a picture alongside a river is posted on any Social Media Platform, this feature can give suggestions to the users regarding specific captions revolving around rivers or water bodies. This can save a lot of time and effort for the users leading to a great monopoly on the internet.

  1. Song Recommendation Project

Various music and song applications have been designed throughout the world. There can be research in the field of automated song recommendations to the users based on their current playlist or already downloaded songs on the application. This can be a  practical and helpful solution for users who are searching for songs that they may like.

Overview

Data Science, on the whole, is a massive field that can be explored with no limits and boundaries. One can keep carrying out amazing researches in several areas.

Investment Banking Courses with Placement in IndiaAll beginners must take up the Data Science Course if they wish to pursue a bright Data Science Career.

This is a field of study that is always going to be engaging and creative no matter how much work and research gets done.

Do You Know Data Science Professionals Been Hired The Most ?

Posted on by Imarticus Learning

Data science courses have become increasingly popular in the past few years. That’s because the demand for data science professionals has risen substantially in various industries.

Companies in various sectors recognize the importance of big data and want to use it properly. In the following points, we’ll look at the sectors that hire the most data scientists:

Industries that hire the most data scientists

There are several industries involved in hiring data scientists:

Finance

The finance sector utilizes the expertise of data science professionals the most. It uses data science in determining the growth prospects of its investments, to calculate risk, perform predictive analysis and manage its operations.

Banks also rely on data science to detect and prevent credit card frauds. They use data science to track fraudulent behavior patterns in suspicious clients to identify potential credit card frauds.

When you join a data science course with placement, you’ll surely be working on finance-related projects.

Healthcare

Data scientists work in different avenues of the healthcare sector. Mostly, they work in the research aspect of healthcare and contribute to making trials and testing more efficient. Data science and artificial intelligence help companies in reducing errors and enhancing the efficiency of research processes.

Modern healthcare technologies also utilize the data science to provide better experiences to patients. Data science helps in improving the accuracy of diagnoses and delivers more precise prescriptions to patients.

Entertainment

OTT platforms have revolutionized the entertainment industry. Netflix, Amazon Prime, and Hotstar are now some of the biggest entertainment companies in the world. Netflix has been using data science since it launched its digital subscription service and has been a hot topic for case studies in data science courses in India. It relies on data science to attract more customers, create high-quality content and track its growth.

Data Science Course with Placement in IndiaHow to capitalize on this opportunity

As you can see, the demand for data scientists is constantly growing in multiple industries. Whether you want to enter the entertainment sector or the banking industry, becoming a data scientist will help you in your pursuit.

The best way to start your career in this field is by joining data science courses. While there are many data science courses in India, it’s vital to pick one that suits your requirements and aspirations. You should always check the data science course details, including the data science course fees to ensure they match your criteria.

Currently, it would be best to pick an online data science course in India because it would teach you all the required concepts and skills digitally.

Enrolling in a data science course in India would not only teach you the necessary skills, but it will also make you eligible for pursuing data science roles in various companies.

You can also look for a data science course with placement. It would help you kick-start your career as a data scientist easily and quickly.

Conclusion

Now, you have learned how data science helps numerous industries. You also found out how joining an online data science course in India can help you capitalize on this demand and become a sought-after professional.

Do check out our data science course details such as the data science course fees, if you’re interested in a career in this field.

How Should You Prepare For Statistic Questions for Data Science Interviews

Posted on by Imarticus Learning

Data Science has been the buzz word of the IT field for the past few years. Courses like data science course from Imarticus will equip you with all the skills required for a data science job. However, to ace the interviews for data science jobs, you should be well versed with the basic components of statistics too. This article discusses one of the key element in Data Science, statistics and its relevant topics to brush up before a data science job interview.
Preparing for Data science interviews
As in many interviews, the statistics are also going to start with technical questions. Many interviewers try to test your knowledge and communication skills by pretending to have no idea about the basic concepts and asking you to explain them. So, it is important to learn how to convey complex concepts without using the assumed knowledge.
Following are the few important topics you could brush off before attending the interview.
1. Statistical features
They are probably the most used statistics concept in data science. When you are exploring a dataset, the first technique you apply will be this. It includes the following features.

  • Bias
  • Variance
  • Mean
  • Median
  • Percentile and many others.

These features provide a quick, informative view of the data and are important to be familiar with.
2. Probability Distribution
A probability distribution is a function that represents the probabilities of occurrence of all possible values in the experiment. Data science use statistical inferences to predict trends from the data, and statistical inferences use probability distribution of data. So it is important to have proper knowledge of probability functions to work effectively on the data science problems. The important probability distributions in the data science perspective are the following.

  • Uniform Distribution
  • Normal Distribution
  • Poisson Distribution

3. Dimensionality Reduction
It is the process of reducing the number of random variables under consideration by taking a set of principle variables. In Data Science, it is used to reduce the feature variables. It can result in huge savings on computer power.
The most commonly used statistical technique for dimensionality reduction is PCA or Principal component analysis.
4. Over and Under-Sampling
Over and Under Sampling are techniques used to solve the classification problems. It comes handy when one dataset is too large or small relative to the next. In real life data science problems, there will be large differences in the rarity of different classes of data. In such cases, it is this technique comes to your rescue.
5. Bayesian Statistics
Bayesian statistics is a special approach to applying probability to the statistical problems. It interprets probability as the confidence of an individual about the occurrence of some event to happen. Bayesian statistics take evidence to account.
These topics from statistics are very important for a Data Science job and make sure you learn more about them before your interview. You can also try various data science training in Mumbai to begin your career at right note. Genpact data science course from Imarticus is an excellent choice to learn more about data science. Check out and join the course immediately.

How is MySQL Used In Data Science

Posted on by Imarticus Learning

Data Science is considered to be the most sought-after profession of the 21st century. With lucrative opportunities and large pay scales, this profession has been attracting IT professionals around the world. Various tools and techniques are used in Data science to handle data. This article talks about MySQL and how it is used in data science.
What is MySQL
In short words, MySQL is a Relational Database Management System or RDBMS that use Structured Query Language (SQL) to do so. MySQL is used for many applications, especially in web servers. Websites with pages that access data from databases use MySQL. These pages are known as “Dynamic Pages” since their contents are generated from the database as the page loads.
Using MySQL for Data Science
Data science requires data to be stored in an easily accessible and analyzable way. Even though there are various methods to store data, databases are considered to be the most convenient method for data science.
A database is a structured collection of data. It can contain anything from a simple shopping list to a huge chunk of data of a multinational corporation. In order to add, access and process the data stored in a database, we need a database management system. As mentioned MySQL is an open-source relational database management system with easier operations enabling us to carry out data analysis on a database.
We can use MySQL for collecting, Cleaning and visualizing the data.  We will discuss how it is done.
1. Collecting the Data
The first part of any data science analysis is collecting the massive amount of data of data. The Sheer volume of data often causes some insights to be lost or overlooked. So, it is important to aggregate data from various sources to facilitate fruitful analysis. MySQL is capable of importing data to the database from various sources such as CSV, XLS, XML and many more. LOAD DATA INFILE and INTO TABLE are the statements mostly used for this purpose.
2. Clean the Tables
Once the data is loaded to the MySQL database,  the cleaning process or correcting the inaccurate datasets can be done. Also deleting the dirty data is also part of this step. The dirty data are the incomplete or irrelevant parts of the data.
The following SQL functions can be used to clean the data.

  • LIKE() – the simple pattern matching
  • TRIM() – Removing the leading and trailing spaces.
  • REPLACE() – To replace the specified string.
  • CASE WHEN field is empty THEN xxx ELSE field END  – To evaluate conditions and return value when the first one is met.

3. Analyze and visualize data
After the cleaning process, it is time to analyze and visualize the meaningful insights from the data. Using the standard SQL queries, you can find relevant answers to the specific questions.
Some analysis examples are given below:

  • Using query with a DESC function, you can limit the results only to the top values.
  • Display details of sales according to the country, gender or product.
  • Calculate rates, evolution, growth and retention.

If you would like to know more about MySQL and its use in Data Science join the data science course offered by the Imarticus. This Genpact data science course offers a great opening to the career opportunities in Data Science. Check out the course and join right away.

The Data Science Vacancy Gap In India

Posted on by Imarticus Learning

Quick. At the top of your head, think about a profession that has many open positions in the market. It’s not engineering. It’s not commerce or the arts. It’s data science and its better-known subset machine learning.
Did you know that data science was once termed to be the hottest job creator for the 21st century. It goes without saying that the large data generation coupled with the technology to play around with the data has given birth to a profession where the demands overrun the supply by a large margin.

Getting Straight To The Facts

  • In India alone, you will find that data science courses and machines learning are the hottest and trending topics of interest not limited to the IT sector alone but also for other industries.
  • Platforms like Thomson Reuters and Great Learning indicate that more than 50,000 positions related to data and data analytics are currently open for the taking in India.
  • The number of postings reached an all-time high towards the end of 2017 and had been rising to a constant range over the following months.
  • The reports also indicate that India currently contributes nearly 12 per cent of all data science positions when compared to the rest of the world.
  • Sectors like banking, finance, e-commerce, media, marketing and healthcare account for more than 67 per cent of the positions spanned mainly over eleven primary Indian states with the highest concentration being from metropolitan centers and urban districts.
  • Similar reports suggest that the banking and financial services are the biggest market for data analytics and data science professionals and are expected to create at least 58 per cent of all jobs for the year 2018. E-commerce is accounted for 17 per cent of the total job share.

Looking At The Factors

  • It is undeniable to say that there has been a rapid rise in the number of colleges and institutions offering data science training, data analyst training but the striking fact is that such skills are becoming increasingly common with completely unrelated professions as well.
  • Employers are no longer looking for candidates with a working level of understanding of computers but rather those who can utilize and leverage the data towards producing meaningful results.  
  • The large gap in the employment sector has been linked to the lack of institutions that properly prepare candidates for the tasks at hand. While there may have been an explosion of data science learning institutes all over the country, quick studies of the curriculum show a stark difference from what the industry is currently looking from.  
  • Government statistics, on the other hand, argue that while more and more data scientists and data analysts are being funneled out, nearly 44 per cent of fresh graduates choose

to work elsewhere outside the country or shift to another position due to dissatisfactions with the pay.

  • It should, however, interest people that average pay scales for data science positions are heavily influenced by the industry the candidate chooses to work in. Top level startups offer initial pays ranging from 89-91 K per year but tend to be higher for well-established companies.

Where The Road Leads Ahead   

  • Software and data science tools like Hadoop, SPSS, SAS, Python and IBM Watson are expected to be the next frontier for leading changes to the data science career as a whole and will likely be the most sought-after skills in the future.
  • More than 39,000 analytics jobs are anticipated to be created in India by 2020 with cyber-security taking an 11 per cent share, healthcare taking up 55 per cent, engineering studies taking up 8 per cent and space exploration 16 per cent.
  • Besides these, agriculture and aviation too will be engaged heavily with data analytic jobs as well as automation and the new buzzword driver less transportation.