Technology

Here’s Why Data Science Course is Most Talked About In 2020

Every organization and major businesses have realised the importance of Data Science in 2020. The last decade proved that Data is the new fuel, and the abundant Data flow ensures a stable market in the future. The sudden rise in popularity created a need to learn Data Science which in turn gave rise to multiple Data Science Courses in the market. 

Amidst this evolution, learners often find themselves in a tough spot and cannot narrow down the best Data Science Course Fees options. Let’s deep dive into the reasons to best understand how Data Science Courses evolved in 2020 after becoming the most talked about in 2020.

What is Data Science?

Data Science is a study that involves various disciplines and uses statistical and scientific algorithms to gather insights and solve problems. These problems can be anything from a small anomaly to growing a business for a company, Data Science takes the raw data and processes the input using various Data Science Processes to find the solutions.

The following processes are involved in the Data Science Life Cycle:

  1. Data Extraction, Transformation, Loading: The process starts with extracting the data from various sources. It is then transformed before we load the data into the program.
  2. Data Manipulation: This process takes care of the necessary changes to the data to remove noise from the data.
  3. Feature Engineering: We Optimize Relevant input values to get the output.
  4. Model Planning: Based on the initial analysis, we explore the options before choosing the model for further analysis.
  5. Model Building: Effective model building provides a desirable output.
  6. Gather Insights & Solutions: Results from the model are studied for insights and solutions to fulfil the requirements.

With a sudden rise in data generation, Data Science picked up the pace. And almost every organization in today’s day and age are using Data Science for their benefit.

Why is Data Science the Next Big Thing?

Every day at least 2.5 quintillion bytes of data are generated by humans every day. We do not realize but everyone acts as a data point in one or more datasets keeping track of each online activity. It could be a reaction to a post on social media, choice of music online, search history, etc. The data collected is then used to identify patterns and to create useful insights.

Now, the kind of data that we generate every day also calls for a large number of workforce to make sense of the humongous data at our disposal.

  • Data Science Career Opportunities

Over the last decade, the number of Data Science Jobs has quadrupled in numbers. A study in 2019, suggested an estimated 11.5 million Data Science career opportunities by 2025 in the Data Science market.

Even during the pandemic, our very best chance was Data. The documented data that officials collected during centuries. Data Science shaped the research process and sped the process quite significantly.

The pandemic affected the job market slightly due to layoffs and salary cuts but the number of job openings somehow remained constant in the Data Science job market. With at least 4,000 active jobs in India and close to 18,000 active jobs in the United States, the Data Science job market looks promising and will flourish in the upcoming months.

  • Data Science Profile Salary

The salary aspect of Data Science is one of the reasons why it is most talked about and preferred profile in 2020.

If we analyze the trend, a junior-level Data Science professional took home 75K dollars a year. A mid-level Data Science professional got 105K dollars a year and a senior professional took home 145K dollars a year on an average.

In India, the average salaries ranged between 400K rupees a year to at least 2 million rupees for a senior Data Science Professional.

And the salaries are distributed in such a wide range of job roles and profiles, it is quite difficult to estimate the exact sum of compensation a Data Science would receive. The only way to ensure a fruitful career is a structured and insightful career path during the learning phase.

  • Data Science Career Path

Data science is an advanced version of conventional data analysis. So, automatically that makes mathematics the most important and key aspect of the Data Science Career path. Statistics, linear algebra, probability, applied mathematics are the key concepts to master to begin a Data Science career.

The following skills are the most crucial in your Data Science Journey:

  1. Data Analysis- It includes the various processes that involve collecting the data and doing the initial data analysis to understand the problem statement.
  2. Programming Language (Python/R) – A programming language is needed to execute/implement the ideas using the code.
  3. Data Transformation- Transformation to convert the data into a specific format to fit the model.
  4. Data Modeling- Modeling to get the desired output.
  5. Machine Learning – Machine learning concepts to make sense of previous data and fed to the model to learn and give the desired output.
  6. AI/ML Algorithms – We use Various machine learning and artificial algorithms to make models depending on the type of machine learning problem like classification, regression, etc.
  7. Cloud Computing – Data processing can be done on the data using various cloud computing tools.

Any company with an active Data Science related job opening will be looking for the above skills. Sometimes, the role of a Data Scientist is a little conflicted in an organization. In a bigger company, Data Scientists may find themselves doing just data cleaning. In a smaller organization, a Data Scientist may have to work on all the processes starting from ETL to the outcome.

This hierarchical anomaly has added a significant amount of job roles that benefit the entry-level Data Science professionals the most. In a bigger organization, job openings double for each process in the life cycle.

  • Data Scientist Skills

Even though the job market is flourishing with an increasing number of job openings for Data science professionals, the recruiters are still pretty adamant about the orthodox trends while testing a candidate. Unless professionals are proficient enough in the following skills, it becomes fairly difficult for anyone to clear the interview.

  1. Programming Language
  2. Statistics and Probability
  3. Machine Learning Skills
  4. Data Wrangling
  5. Data Visualization
  6. Familiarity with Cloud Computing
  7. Big Data
  8. Database Management
  9. Communication Skills & Problem Solving Skills

Mastering above skills can easily get you a job in Data Science.

  • Growth of Python

The programming language is one of the main components of the Data Science life cycle. Python programming became one of the reasons for the Data Science Course’s popularity.

The ease of access and readability moved new learners towards the programming language. When Data Science picked up space, Python’s library support provided easier implementations for each Data Science Process in the Data Science Life Cycle.

Pandas, Numpy, Scipy provided implementations for the ETL, Data Manipulation, and Feature engineering. Seaborn and Matplotlib, on the other hand, came with efficient visualization tools for making visual representations.

Scikit-Learn, TensorFlow, Pytorch help the Machine learning and Deep learning aspect associated with Data Science.

  • Cloud-Based Big Data Science

We can consider Big data as a subset of Data Science. Data scientists can make use of cloud computing technology to make use of various tools and programming languages for improved data processing. This is the future of Data Science, aligning perfectly with cloud computing and using SAAS to store and retrieve information from the cloud.

The consolidation of the Data Science ecosystem in the last decade provides a promising career for budding aspirants. But, learners find themselves in a hesitant and confused state while choosing a Data Science Course.

It is quite evident that a structured learning career path is the only thing that can set you apart from the crowd. The promising career has attracted a significant amount of applicants with the same skill set.

So how does a learner decide which Data Science Course Fees is the most appropriate?

How to Choose the Best Data Science Course Fees?

When choosing a Data Science course there should be 2 parameters that must be fulfilled. Anything above that is the perks that require extra compensation.

The first aspect is the curriculum. You must do initial research and understand how the curriculum is going to help you. If the curriculum satisfies the desired results for your growth then you must check the other parameter i.e Data Science Course Fees.

Most of the courses offer the same Data Science Course Fees. Sometimes, a company might add a few perks such as placement assistance, customer support, online cloud labs, etc. These are the extra features that attract an increase in the Data Science Course Fees. Although if a course provides placement assistance, it is worth paying the extra money.

Conclusion

Even in the darkest of times, where professionals are losing their jobs, companies are losing businesses, and humanity faces an unprecedented attack on their livelihood, Data Science promises decent career growth.

For fresh graduates as much as experienced professionals the job market is flourishing with job openings. Data science has a sense of job security since data is the new fuel and we have generated even more data than we had in the whole decade during the whole lockdown in the pandemic.

The constant flow of data ensures future developments in the Data Science domain. The only way to stay ahead of the curve is by making sure you get the head start. Enrol in Springboard’s Data Science Course to kick start your career with a placement assistant and a world-class curriculum.