What is the Future Scope
of Data Science in 2023?
Everyone wants a profession where their work-life generates skill, status, and profit and not stress!
A future in data science may not give the answer to stress because that depends on various personal and social factors but a career in data science certainly makes sure a learn-filled profiteering life.
Data science is one of the constantly evolving fields with an ever-increasing demand. It has waged a revolution in the industrial warfield. Data is the new oil to smoothen the industrial machinery.
A company with a set of highly skilled professionals in data science can create miracles. Their actionable insights will drive the company towards the profit mines. Data proliferation will never end, and this in itself gives a glimpse of its bright future.
However, the covid aftereffects and later tussles of major national powers have made the future of the global economy gloomy. Countries are struggling to control inflation and people are struggling to save their jobs. In such a scenario, a student or professional who is planning to turn into a data scientist might be having questions about the scope of data science in 2023. The ever-evolving technologies and fields of operations can be one fear.
It is important to be aware of the opportunities and potential of your future professional life. Through this blog, we will address all those mind bogglers in a lucid yet detailed manner. So keep reading!
Common questions and their most simplified answers:
Careers in data science
Glassdoor in the USA is ranking data science as the best job for the past four years. In a demand-driven market system, data science persons are the true assets of any industry. But unfortunately, when industries are craving so deeply for data scientists, India lacks data scientists. The market is open with approx 50,000 – 100000 data science job postings on a daily basis.
So competition in data science is a myth but what is not a myth is the lack of well-trained data scientists. There is a need for a revolution in data science academia to tap the market demand. Data science allows you to serve varieties of profiles as per your desire. Few of the most prominent job profiles for a data scientist are
- Data Scientist
- Data Analyst
- Business Analyst
- Data/Analytics Manager
- Business Intelligence Manager
Thus as a data scientist you don many hats in your workplace which means increased personal worth. From data analytics to building data products, developing visualisations to machine learning algorithms, your can create your important space everywhere.
Data Science Vs AI
“Will automation take away data science jobs?” is the one buzzing question. Data Science and Artificial Intelligence are sometimes used interchangeably but are not the same thing. Yes! Data science takes some help from AI, but it is not replaceable by it.
Data science is the process of collecting and analysing data. AI is a process that only analyses future patterns and trends. Data Science contains a variety of data types such as structured, semi-structured, and unstructured data, whereas artificial intelligence contains standardised data in the form of vectors and embeddings.
Data science contains a whole lot of things that ask for a human brain. Data extraction, manipulation, visualisation, and upkeep of information to predict the occurrence of future events need an expert human brain to give the desired outcomes.
In the end, the job of the data scientist is evolving, though exactly how it is is up for debate. While some activities are being expedited and made simpler by automated solutions, data scientists are still needed in some capacities. In the meantime, new opportunities like quantum data science are emerging.
Increased integration of machine learning:
Machine learning has brought growth to industries in several ways. Industries throughout the world are rapidly adopting machine learning to survive the competition. A 2018 survey by MIT Technology Review and Google Cloud found that 60% of participants had previously used machine learning in company operations. These figures unequivocally demonstrate the enormous potential of machine learning and its acceptance in the commercial world.
It helps by increasing the amount and variety of data, enabling more efficient and powerful computer processing, and lowering the cost of data storage. Some benefits of machine learning are
- Enhanced Network Security
- Making targeted predictions and recommendations
- Personalised customer service
and a lot more
It automatically creates models that can evaluate larger, more complicated data sets and provide quicker, more accurate results – even on a very large scale. And by creating accurate models, a company has a better chance of spotting profitable possibilities and avoiding losses.
Wanna explore all domains of Data Science? We are inviting you to take a look at our Data Science Courses.
Increased data literacy:
In the past few years, there has been an influx of academic programs and data literacy initiatives. This has not just piqued the interest of students to learn data science but also made it affordable for the students to secure a bright future. Exposure of students to data-related disciplines will provide for a competitive environment.
When someone has the abilities to comprehend, explore, use, communicate with, and make decisions utilising data, they are said to be data literate. Developing the skills necessary to ensure data-driven critical thinking is another aspect of literacy.
Organisations are collecting more data than ever before to benefit through improved service delivery. By using data as an asset, businesses are continuously looking for new methods to stand out from the competition and stay relevant in the market. In order to make timely decisions, organisations must be able to extract relevant signals from the vast amounts of data being produced.
There is a dire need for expert professionals to structure these data and bring actionable insights.
In this world of cutthroat competition, everyone is looking for a space where there is learning free of competition. This exactly fits in the frame of data science. There is so much demand that competition doesn’t harm and it is a constantly evolving field so there is constant learning.
You can see the wide-armed opportunities by the fact that there is a 29 percent year-on-year growth in demand for data scientists i.e. almost 350 percent since 2013. With 2.5 quintillion bytes of data produced on a daily basis, there is an ever-increasing demand for data scientists with a lot of data science jobs for freshers.
Organising and structuring this size of information to produce business solutions is indeed heroic and thus makes data science one of the most coveted professions. Especially after the big data wave, IT companies are in a competitive position to hire the best talents in data science. There is also a shortage of professionals with deep analytical skills.
To succeed in a data science career, you’ll need both technical and practical capabilities. A successful data scientist’s armoury consists of coding skills combined with statistical understanding and the capacity for critical thought.
Data science course eligibility
The only data science course eligibility is to have basic analytical, mathematical skills and a highly motivated attitude.
In the process however you should train yourself in such a way that complex data sets should be easy for you to comprehend and use. You should also be able to use statistical software programs and be knowledgeable about programming languages like Python or R. Additionally, most data scientists hold a qualification from an approved program.
Mathematics is typically necessary for becoming a data scientist, as is previous experience working with enormous volumes of data. Additionally, having knowledge of statistical modelling and machine learning is frequently beneficial.
However, it is not necessary to have a strong or any foundation in computer science. Anybody from any stream of education can create his space in this field.
You will deal with a lot of data on a daily basis as a data scientist. You should especially at ease with statistical techniques and algorithms. Effective manipulation and analysis of massive data sets is a requirement for data scientists. As a result, before becoming a data scientist, you need to have some experience working with massive data sets.
Tapping the data science mania
After so many proofs supporting the rising scope of data science in 2023, any progressive brain can’t stop itself from embarking on this journey. Securing a career in data science is neither expensive nor competitive but what it needs is a perfectly guided approach.
Unlike any recipe-made career, data science is an ever-evolving field. To start this journey, one should equip himself with the following technical skills before diving in, such as
- Machine learning
- Deep learning
- Data visualisation
- Hand of practice with statistical analysis
A job in data science is not just about technical skills, there are some other skills that make the journey even more romantic like
- Clear communication
- Critical thinking
- Entrepreneurial mindset
Now the question is what is the average cost of a data science course on the biggest online educational platforms? While writing this blog, I just checked to see what the current price is. A very general online education platform is asking for 1.5 lakh rupees for a 6-month diploma in data science and this is just one. For a very basic course content without real hands-on practice, people are paying nothing less than a lakh.
Any middle-class person will ask if it is worth paying for it. Obviously not!
What is the alternative?
At CloudyML, the very first principle we bring in our process is to come up with affordable quality education. With world-class educators, CloudyML comes with a very simplified yet quality-rich curriculum. CloudyML has courses starting from a very basic pay of INR 3999/- and our most expensive (Is it?) course is worth INR 7999/-
Yes, a maximum price of just INR 7999/-
Shocked!!! Give a minute to come back to your senses and sink this in.
How CloudyML can build a career in data science in 2023?
CloudyML provides self-paced courses with a learn-by-doing concept. To learn data science at CloudyML means bringing your hands to practise side by side. The purpose is to bring the students to the level of cracking any data science/analytics interview from scratch.
An in-depth study on various aspects of data science with the help of
- Guided assignments
- Real-world projects
- 1-1 teaching assistant
- Daily doubt-clearing support
Hands-on practice and the guided approach make the courses a must to opt for. It not just assists you with theoretical knowledge but also prepares you for the real world outside.
With all this at our disposal, any sincere student who starts his or her journey with ClodyML will be able to land his first job in 2023. So wait no more and grab a promising career in data science by grabbing a CloudyML course.