What Is the Data Science Learning Path?


The Data Science industry is growing by leaps and bounds, and its disruptive nature continually attracts businesses globally. Therefore, the demand for skilled Data scientists has been ever-increasing. 

You need to be a graduate to become a Data Scientist. If you are prepared to put in the required time and effort and are open to learning new things, you’ll surely become a successful Data Scientist. The opportunities for Data Scientists are unending. Studies show that, if anything, the opportunities will increase in number in the future. Enterprises in all fields definitely would want to employ people with more skills.

The roadmap to becoming a Data Scientist could feel a little overwhelming initially. But, it eventually makes sense when one tries to understand the various career paths for Data Scientists and becomes well versed in the process. The journey to becoming a Data Scientist could be difficult, but it’s going to be worth it in the end.

Describing Data Science and Who Is a Data Scientist!

Data Science is an AI learning path and an interdisciplinary field that applies information from data across various application fields by using scientific methods, procedures, algorithms, and systems to extract knowledge and insights from chaotic organized, and unorganized data.

To build a career in Data Science, one must become a Data Scientist. 

A Data Scientist’s job is to glean information from organized and unstructured data that could impact the way businesses operate. Data Scientists frequently have higher leadership positions in an analytics organization than team leads. Having Data Scientists in an organization is essential because every sector and function embraces analytics. Everything is governed by analytics, from sales and supply chain to marketing and HR.

Qualifications Required for the Data Science Learning Path

To work as a Data Scientist, one needs an undergraduate or graduate degree in a related field, such as business information systems, computer science, economics, information management, mathematics, or statistics. The eligibility for each level of the course varies.

Advanced degrees in data analysis or Data Science are typically required for Data Scientists. The M.Sc. in Data Science, M.Sc. in Business Analytics, M.Sc. in Data Science and Analytics, and M.Sc. in Big Data, among other popular postgraduate degrees, are available.

People usually have one question in mind: “is Data Science hard?”. If a person is interested in the fields mentioned above, then they will enjoy the journey to becoming a Data Scientist. Hard work is a key factor. 

How to Become a Data Analyst Without Any Prior Experience?

After a Data Science learning path, you can work in Data Science if you enjoy playing with numbers and are familiar with the fundamental ideas of math and statistics. Here are a few pointers to help you ace your Data Science interview and launch a lucrative career.

  • An internship with a Data Science firm is recommended.
  • To be well versed in statistics, probability, and linear algebra, it is important to find excellent courses that teach these subjects.
  • Know the fundamentals of speech processing, computer vision, bioinformatics, information extraction, natural language processing, etc.
  • To cover the basics, take up an online course on Data Science.

Data Science Learning Path

To build a career in Data Science, one must be proficient in the following software –

  1. SAS
  • The software program used for data analysis and report authoring is called SAS, or the Statistical Analysis System. 
  • The role of SAS is to calculate simple and complicated stats, modify data and create reports.
  • Statistics are analyzed using SAS, a computer programming language. It is currently the clear market leader in the field of business analytics.
  • Unlike open-source, SAS updates are thoroughly vetted because they are developed in a controlled environment. The language is simple to learn and offers a straightforward alternative for experts with a solid understanding of SQL.
  1. R
  • A language used in programming for statistical analysis. R is frequently used to create statistical tools and analyze data. 
  • R is an open-source programming language and software environment for statistical computation and graphics. Both statisticians and data miners frequently use it. According to an O’Reilly Survey conducted in 2014, it has grown in popularity over time and was the second-most commonly used Data Science language (behind SQL) and one of the key competencies with the highest pay for Data Scientists. Data Scientists already use R at several large companies, including Facebook and Google.
  1. Python
  • Python is a popular programming language in Data Science positions. After SQL, it is the expertise that employers most value, according to KDNuggets. Python was first used to build the Google App Engine, which is another reason why it is Google’s official language. IBM and Quora are two more significant businesses that utilize Python.
  • Python’s compatibility with modules and packages promotes the modularity and reuse of code in programs. The Python interpreter and the comprehensive standard library are distributable for all popular platforms and available in source or binary form.


Data Scientist skills and business skills that will give you an advantage :

  • Statistics and Match proficiency
  • Machine learning tools and techniques
  • Data Mining
  • Software engineering skills
  • R and SAS languages
  • C/C Java
  • Data cleaning and munging
  • Analytic Problem-solving
  • Effective Communication
  • Intellectual curiosity and Industry knowledge
  • Big platforms like Hadoop
  • Data visualisation and reporting techiques


The Data Science learning path might be a little time-consuming and tough, but it is considered one of the best career options for various reasons. On an everyday basis, there is a lot of data accumulating.

These startling figures demonstrate the necessity of a Data Science learning path for scientists to separate structured and unstructured data effectively. One of the most popular job possibilities today for those with a background in technology is the Data Scientist path. This field of work will continue to exist given the speed at which the world migrates to digital operations for all tasks, large and small. This is why IT professionals, as well as recent graduates, are choosing to enroll in a Data Science learning path.

UNext Jigsaw offers PG and Diploma courses in Data Science. You must explore these if you are interested in a successful data scientist career. You get to interact and learn from the industry leaders and grab a hands-on learning experience.

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