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.
For any new learner who wishes to join an Online course in data Science it is very important to understand the subject thoroughly.
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.
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.
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 specialised 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.
Students who join our online Data Science Course must understand that more and more companies are looking for a skilled person due to increasing popularity of Data Science Because Harvard Business Review called data science the Sexiest Job in 21st Century
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
Advanced computing is exactly what it sounds like. At the core of data science are many computer programs running on code. The creation, running, and advancing of these source codes is part of advanced computing. Advanced computing is responsible for the comprehensive processing of the data.
5. Visualization
Once the data is processed, it needs to be represented in such a way that it easily communicates all the findings to everyone. Visualization also helps cover a vast amount of data.
Technologies and Technique for Data Science
Data science makes use of many technologies and techniques. They can be different based on the application of data science and the requirement of the predictive models. But it is important to know about them.
Here are the most widely used technologies and techniques in data science:
1. Technique
- Linear Regression– This is a linear way to showcase a relationship between the dependent and independent variable and scalar response.
- Logistic Regression– Probabilities of certain events or classes are modelled through logistic regression.
- Decision Tree– Data fitting and classification are addressed by the decision tree prediction models. Support Vector Machine (SVM)
- Clustering– Grouping data together is called clustering.
- Dimensionality Reduction– For quick computations, data complexity is reduced through dimensionality reduction.
- Machine learning– Inferencing patterns from data is done by machine learning techniques.
2. Languages
- Julia– One of the best languages for computational science and numerical analysis.
- R– The best language for data mining and statistics.
- Python– The most common programming language for data science
3. Frameworks
- TensorFlow– Google’s framework machine learning.
- Pytorch– Facebook’s framework for machine learning.
- Jupyter Notebook– Interactive web interface for faster experimentation.
- Apache Hadoop– Framework for processing data over distributed systems.
4. visualisation Tools
- Plotly– Gives access to multiple scientific graphing libraries.
- Tableau– Software for data visualization.
- PowerBI– Microsoft’s business analytics service.
- Qlik– Multiple software and tools for business intelligence and data visualization.
- AnyChart– Make dashboards and charts using JavaScript libraries.
- Google Charts– Google tool for making elaborate graphical charts.
- Sisense– Front-end tool for data visualizations like reports and dashboards.
- Webix- Is a UI toolkit for data visualization.
5. Platforms
- RapidMiner– Widely used data science software platform.
- Dataiku– Data science software for big data.
- Anaconda– Free, open-source platform for distribution of R and Python.
- MATLAB– Popular platform used in academia and industries
- Databricks– Popular platform for collaborative data science and data engineering.
- IBM Watson Studio– Cloud platform for integrating AI into business-related applications and collaborative data science software and tools.
Growth of Data Science in India
Data Science considered as one of the top professional careers chosen has a perfect future in India. There are a lot of companies coming up in India, and every industry irrespective has bulks of data and require a data scientist anyway.
Previously, the companies used to rely on their gut feelings to take any significant steps. But now they have a data scientist who gives a calculated reason before landing on a decision. It is better to be calculative than following your Gut.
People have seen rapid growths and able to analyze the market trends in a better way. A calculative step minimizes the risk factor.
All these factors clearly, showcase the scope of Data Science in India.
Following are the trends in Data Science job postings per 1 million postings on Indeed, we can infer that Data Science jobs have been growing in trending charts. In 2019, it is expected that this trend will only grow higher.
Some points to note for Job Trends in India –
- India contributes to 6% of job openings worldwide.
- The total number of data science and analytics jobs in India are 97,000.
- 97% of the jobs are on full time basis whereas 3% are part-time.
- There has been an increase in 45% of total jobs in the year 2018.
- There is an increase of 2% in analytics salary above 15 lacs in India.
There are a lot of jobs for Data Scientist in India, giving a vast exposure to the people who want to be a Data Scientist. As we check Naukri.com , one of the top Indian Job seeking sites say more than 25,000+ jobs are there in India just for Data Scientist. And as we checked LinkedIn one of the top jobs finding a place in the whole world, more than 14,000+ jobs are there in India for Data Scientist.
We can say that the companies require some Data Scientist and the requirement will grow and can never decrease.
This clearly shows the requirement of the Data Scientist in India. According to the Indian Times analysis; Recently, business report reveals that 50,000 jobs in Data Scientist and Machine Learning. This shows how business analytics increased in India.
Nowadays, online courses have become very feasible, for the best data science course you can opt Our Online course.
Skills Required for Data Science
The education and the work of a data scientist are quite unique and specialised. Therefore, you need to have a special set of skills to become a data scientist. Even if you may not have them all, you can also work on these skills if you choose to get an education in and pursue data science.
Here are the skills required for data science:
1. Mathematical Skills
2. Analytical Skills
3. Programming Skills
4. Communication Skills
5. Presentation Skills
What Are the Different Types of Data Science Courses?
To learn data science, you need to do a data science course. As mentioned before, data science is relatively new, so there aren’t many data science courses available in India. But the currently available ones are good. These courses will make you eligible for a career in data science. However, you can just choose any course. You have to know about these courses and choose the one that meets your education and career goals.
Therefore, here are the different types of data science courses.
1. Certification Training Course in Data Science
This is a certificate course that is mostly taught by private institutions. This is an excellent course if you want to do it as an add-on to your other educational degrees and courses. It is also very flexible and allows professionals who are already working to pursue data science. If done from the right institute, the certification training course in data science can get you quickly started in a data science career. These courses are also quite affordable and let you learn from the best teachers.
2. Graduate Course in Data Science
This is a proper degree course in data science. Offered by universities and private institutions, the graduate course is 3 to 4 years in duration. You will have to attend classes and sit for exams. Once you have this degree, you can choose to pursue a career in data science or study further and get a postgraduate or management degree.
3. Diploma Course in Data Science Online/Offline
Similar to a graduate course, the diploma course in data science is also quite valuable. The advantage with diploma courses is that they tend to be more industry focussed. This diploma course can vary in duration based on where you are doing this course. You can also do this course online Please do visit our website. Data science is so much in demand that good diploma courses can also get started in an excellent data science career.
4. PGD in Data Science Online/Offline
If you already have a degree in another stream but want to switch to data science, you can pursue a PGD in data science. However, you will have to clear the criteria set by the university or institute providing the PGD in data science course. PGD courses are usually overseen by the AICTE, so look for a course and college approved by AICTE for it to have value. This course can land you in some of the top-paying jobs in data science. It is also available online.
5. MBA in Data Science Online/Offline
The MBA in data science is one of the best data science courses you can do. Along with all the technical knowledge, you also get a lot of managerial and administrative knowledge, making you eligible for top posts in data science. This course can be anywhere between 1-3 years in duration and can also be done online from a reputed institute or university.
Is Data Science A Good Career?
Data science is one of the best careers to have right now. With a rise in technology, big data, and organisations realising the importance of data science, data science careers are going to be in high demand all over the world. So, if you are thinking of data scienc below find the key benefits of choosing this course.
Here are 5 key reasons to consider a career in data science:
1. Massive Demand
In 2020, there were more than 1.5 lakh jobs available in the field of data science. This was a 62% growth compared to the figures of last year and experts predict the figures are going to get better in 2021. As countries and economies start reopening, there will be a surge in demand for data scientists. One fact worth knowing is that there is a demand for data science candidates with less experience.
2. High Salary
Even an entry-level data science job can get you a salary of INR 5 lakhs per annum. Data scientists count themselves among the highest paid professionals, not just in India but the world. Multinational companies are hiring teams of data scientists. Even small and mid-level companies are stretching their budgets and hiring data scientists as they know the huge positive impact they can have on their business. So, as a data science professional, you can expect a high salary and other perks and benefits with the job.
3. Part of Every Industry
Data science is not confined to a few core industries; it can enhance business across all industries. From IT and automobiles to healthcare and pharmaceuticals, every industry can benefit from the use of data science to enhance their business operations and decision-making. So, if you have an education in data science, you can choose to join the industry of your choice.
4. Technologically Advanced Field
Technological advancement is the reason why many industries are thriving today. It is going to be the main driving force behind growth and development. Therefore, industries with technology at their core are going to do really well. Therefore, data science is also going to do well as it synergizes with technology really well and is going to be one of the most advanced industries in the future.
5. Challenging Jobs
If you are looking for fun and excitement in your job, data science can definitely provide it. Data scientists face new challenges every day and turn them into opportunities to learn and grow. Therefore, there is never boredom in the data science field. Every day there is something new and exciting.
Career opportunities in Data Science:
Here are some of the top Data Science jobs with their roles, responsibilities, and salaries. You will also find the details of Science jobs. skills required for Data. Let’s start with the most popular one – Data Scientist.
1. Data Scientist
Data Scientists are analytical experts who are responsible for finding insights and patterns in the data. A Data Scientist is responsible for handling raw data, analyzing the data, implementing various statistical procedures, visualizing the data and generating insights from it. He/she churns raw data and transforms it into meaningful products. A Data Scientist is also responsible for handling both structured and unstructured information.
A Data Scientist must have knowledge of various tools like Hadoop, R, Python, SAS, etc. Knowledge of data pre-processing, visualization and prediction are some of the important requirements of a Data Scientist.
2. Data Architect
A Data Architect is responsible for implementing the blueprints of a company’s data platform. This blueprint or architecture delineates various models, policies, rules that govern the storage of data as well as its use in the organizations.
A Data Architect is responsible fororganizing and managing data both at the macro level as well as the micro level.
Some of the important tools used by a Data Architect are XML, Hive, SQL, Spark and Pig. The average salary of a data architect is Rs. 8,969,165per annum.
3. Data Engineer
A Data Engineer is responsible for building big data pipelines and models for the data scientists to work on. Data Engineering involves the knowledge of various data related topics as well as knowledge of software engineering principles. A Data Engineer must be well versed with both structured as well as unstructured data. A Data engineer is not only responsible for building data models but also maintaining, managing and testing it.
Knowledge of database models and ETL are two of the most essential requirements for a Data Engineer. A Data Engineer is responsible for modelling large scale processing systems using tools like SQL, Hive, Pig, Python, Java, SPSS, SAS etc.
4. Data Science Manager
A Data Science Manager is responsible forhandling and managing data science projects. A Data Science manager handles the team and manages the performance to meet project deadlines. Usually, data science managers have an average of five-year experience in any of the data science domain like date engineering, data science or analysis.
Data Science managers are responsible for planning and curating a roadmap for the data science team to follow. Furthermore, they are responsible for executing the plan of action and delivering the results before the deadline. He She should also have strong communication and leadership skills in order to guide the team efficiently. The average salary for a data science manager is –Rs. 5,000,000/yr.
5. Statistician
A statistician is the oldest job title among all the roles discussed in this blog. Before data science, statisticians were employed by the companies to use statistical modelling for understanding various trends in the market. A statistician is responsible for implementing A/B testing, harvesting data, describing data, developing inferential statistical tools and performing hypothesis testing.
Some of the tools used by statisticians are R, SAS, SPSS, MATLAB, Python, Stata, SQL etc. The average salary of a Statistician is 6,000,000/yr.
6. Machine Learning Engineer
A Machine Learning Engineer is responsible for tailoring machine learning models for performing classification and regression tasks. A Machine Learning Engineer has the knowledge of various techniques like clustering, random forest and several other deep learning algorithms. It is an advanced field and people are required to possess analytical aptitude skills to develop machine learning algorithms.
Some of the popular tools used by the machine learning engineers are TensorFlow, Keras, PyTorch, scikit-learn, Caffe etc. The average salary of a machine learning engineer isRs. 8,327,100/yr.
7.Decision Scientist.
The field of decision science is a relatively new field. Decision Scientists help the company to make business decisions with the help of tools like Artificial Intelligence and Machine Learning. It is a part of data science that extends to design thinking and behavioural sciences to better understand the clients. The average salary of a decision scientist is Rs. 5,000,000/yr.
How Data Science Will Change the World
Data science gives an opportunity to look into the future, and change the present to make it better. But this is a rather simplistic overview. Data science does a whole lot more. Through data, data science can help us get deep into the problems and failures of the past, and help us understand and plan accordingly. It can help in bringing overall improvement in all aspects of human life.
Another great example of data science changing the world is the current COVID-19 vaccines. These vaccines have been developed in record time thanks to data science and artificial intelligence. In the future, data science can also help humanity predict pandemics and other calamities. It can help us be prepared and help improve the lives of everyone. Many people only think of data science’s business applications but it can do so much more and truly change the world.
How Online learning can be the best option for this course
eLearning courses have become hugely popular by the simple virtue of being so much more convenient than traditional face to face courses.
Online courses are easily accessible on much smaller budgets.
In addition to the convenience and the cost, a large number of students are turning to online learning courses because they have become a better way to learn.
Remember that an online course in data science online bears the same weight as a campus degree on your resume. An online course may offer more flexibility and better work life balance. It may also reduce total cost by eliminating a commute to campus. If you feel it’s worth the investment, don’t be afraid to go for it.
Admissions criteria for a data science master’s online and certificates are all over the map, so make sure the program fits perfectly to your skill level.
Programs typically include a blend of core courses and electives. Multimedia lectures, discussion boards, video conferencing, group project work and virtual office hours are some common elements.
Flexibility
There are quite a few benefits of learning Data Science online, but one of the major benefits of a data science online course is flexibility. Students can manage their job and other responsibilities while learning online. If you are a hardworking Multi tasker, you are on the right place, we welcome you to join our course.
Summary
All the above-given information will give you a clear picture of data science and help you decide if it is the career for you. But most experts will tell you that data science is one of the best courses you can do.
One of the great things about data science is that currently, employers are also hiring candidates with less experience. So, if you are just starting off, or making a career switch, or adding on data science certifications to boost your career, you will get a job in a reputed company. But you have to ensure you do your data science course from the right place.
The best place for you to do a data science online course is Right here. We offer the most comprehensive and prolific online and offline data science courses taught by the best faculty and experts in India. To know more visit our website. Our representatives will get in touch with you with all the information you need. All the best!
