The field of data science has significantly changed how humans have conventionally looked at data. To a normal human being, data might seem meaningless. But in reality, data holds great power. When analysed through modern data analysis techniques, it can reveal unforeseen insights, practically impossible to deduce from just human interpretation. It can help understand the fundamental workings of things and help establish a correlation between seemingly unrelated data sets.
Data science has been around for quite some time now. But the technology required to undertake data science on a larger scale was missing from the picture. Historically, computational power had always worked as a bottleneck when people tried to work with large data sets. With the advancement in computing technology, this bottleneck has been removed from the equation. Now a person can analyse large data sets right from their laptops. Cloud computing services have allowed businesses to outsource computational power to them. In turn, removing the need to develop and maintain highly sophisticated computational technologies.
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What is taught in Data Scientist Courses?
Data science as a field of study is an amalgamation of multiple disciplines. From statistics to machine learning, it combines various disciplines to extract meaningful and actionable insights. Data scientists build algorithms that can analyse in such depth that it is practically impossible through human analysis.
Data scientist courses in India teach a broad spectrum of subjects required for undertaking data analysis processes. Let’s briefly discuss these subjects.
- Mathematics
The very first thing that is inseparable from data science is mathematics. But one won’t have to learn university-grade mathematics. The students will have to learn mainly three things. Calculus, Linear Algebra, and Statistics. These are required to make machine learning algorithms and analyse and deduce data insights.
- Programming language
Programming language is the second most important subject when learning data science. The most preferred programming language is python. Most courses tend to prefer python over all the other options due to the vast resources available for it. Making it easier to learn and use when compared with other relevant programming languages.
- Dashboard creation and related software
The ultimate goal of data science in a job setting is to find meaningful insights and present them comprehensibly for people not coming from a data science background. For this reason, data science courses include classes on various data visualisation and dashboard creation software.
- Data structuring
Data comes in all sizes and shapes, but one common thing is it will mostly be unstructured. Now unstructured or raw data can not be fed through most data-analysing software, and even if one does go forward with unstructured data, the insights will tend to be inaccurate to a large degree. Therefore structuring the data and removing inaccuracies is of utmost importance. Data science courses teach about various software and techniques that are used for structuring and removing inaccuracies from raw data.
- AI technologies
For data analysis, machine learning and deep learning are used extensively. These are used to automate the data analysis process, gather insights, and establish correlations between various data points. Therefore data scientist courses include both these technologies in their curriculums.
- Cloud computing
Cloud computing is the facilitator that allows the broad use of data science. With it, only a few companies were able to process ever-increasing sizes of data sets. Data science courses make the students familiar with various cloud computing service providers and the process of using them effectively.
Data scientist job opportunities
Data science is a broad field, and almost every industry today uses some form of data analysis to further advance itself in this ever-changing and increasingly competitive market. For all practical purposes, we will discuss the broad job positions that prevail over all the others. These are data analysts and business analysts.
Data analysts have the responsibility of creating analysis models as per the requirements of a business or institution. They will gather insights from analysing the data and understandably present them. On the other hand, business analysts must take these insights and pinpoint actionable insights best suited to the company’s needs. Business analysts’ prior work experience helps them combine their work experience with insights and find the right course of action for the company.
Data analysis in a business context
The analysts generally follow a set path to reach their ultimate goals. The path is divided into four stages. They are descriptive analysis, diagnostic analysis, predictive analysis, and prescriptive analysis.
- Descriptive analysis
Descriptive analysis is the most rudimentary form of data analysis. It is also the oldest form of data analysis and has been used for centuries. In it, the goal is to answer a straightforward question. What happened over some time?
To answer this question, the analysts will take key performance indicators of a company and chart out the outcome of the company’s performance in that period. The result is then compared with previous time frames to analyse if the company performed better or worse than the previous quarter or year.
- Diagnostic analysis
The next step in the process is called diagnostic analysis. In diagnostic analysis, the goal is to find the answer to why something happened.
The analysts will dive deep into the various aspects of the business and look to find a sensible answer that supports the results of descriptive analysis.
- Predictive analysis
Predictive analysis is one of the more advanced forms of data analysis. In it, the goal is to find the future outcome through the data analysis process. For this type of analysis, machine learning and deep learning programs are necessary. Predictive analysis not only predicts a company’s future outcome but also helps them take precautionary actions to safeguard themselves from adversities.
- Prescriptive analysis
The prescriptive analysis gives actionable insights, which can be used to either streamline processes or improve a product or service. It is the most advanced form of analysis, and until recently, only a few companies had the recourse and technical know-how to partake in it.
Online data scientist courses in India and their benefits
Online data scientist courses in India have become the go-to choice for working professionals. And rightly so; failing to constantly upskill can be disastrous for any working individual. The current economy and job market are susceptible to changes from all kinds of technological advances or macroeconomic situations.
Take, for example, the looming fear of recession. Historical data shows that during every recession, even massive companies had to resort to mass layoffs to sustain themselves through the economic downturn. Many experts are already hinting at a possible worldwide recession in 2023, and only those who have significant importance to the companies can safeguard their jobs. Therefore constantly upgrading oneself should be the top priority of any working individual in today’s market.
The biggest hurdle between a working professional and upskilling is time constraints. They can only attend regular courses once they quit their current job or take extended unpaid leave, which only a limited number of companies allow. Therefore online courses become the only viable option for them. An online data scientist course will teach all the required subjects, the same as any regular course, but the classes will be held online and outside working hours. Some even have physical classes during weekends and online classes on weekdays.
The only downside is that some employers put more faith in regular degrees than online degrees. But the truth is a working professional with some industry experience is a far better asset for a company than an individual with a regular degree but no experience.
