Data Science is a field in the interdisciplinary domain. It is about the scientific approach in processing huge data requirements. The science of data pertains to various scientific techniques and theories derived from several fields in the context of mathematics, statistics, computer science, information science, and domain knowledge.
Data Science Eligibility
Lately, Data Science has been in great demand in the industry. To cope with the demand, students have started looking forward to studying the DS subjects. Industries started upgrading the skills of their staff to remain competitive. Several institutes and course providers picked the industry needs and designed suitable courses in Data Science.
Data Science Demand
According to the report by the US Bureau of Labor Statistics, the rise of Data Science needs will create approximately 11.5 million job openings by 2026. The World Economic Forum predicts that by 2022, the profession of data scientist would be the most emerging in the world.
As the growth suggests, after the United States, India is looked at as the second most prominent hub for Data Science developments. As per the current industry job trends, Data Science is a highly employable and appealing profession. The demand, therefore, introduced a swift surge in the Data Science course providers.
Who is Eligible?
Anyone, whether a newcomer or a professional, willing to learn Data Science can opt for it. Engineers, Marketing Professionals, Software, and IT professionals can take up part-time or external programs in Data Science. For regular courses in Data Science, basic high school level subjects are the minimum requirement.
Data Science, loosely, is an amalgamation of concepts from Mathematics, Computer Science, and Statistics. Students should have a degree in one of the fields in science, technology, engineering, and mathematics (STEM background).
Having studied computer programming in high school is an additional benefit. Students study the fundamentals, as well as advanced concepts in Data Science. Based on the subject knowledge of statistics, machine learning, and programming, students become experts in implementing Data Science methodologies in the practical world.
Students from other streams, like business studies, are also eligible for relevant courses in Data Science. Similarly, business professionals having a basic degree in Business Administration, such as BBA or MBA, are also eligible for higher studies in the Data Science domain.
These professionals work in the capacity of Executives in the IT industry. They are mostly responsible for making CRM reports, MIS (Management Information System), and business-related DQA (Data Quality Assessment).
Data Science Curriculum
The majority of courses designed are PG and certificate level courses for graduates. Recently, several technical institutes and engineering colleges in India launched degree level programs in Data Science and Analytics.
DS Subjects and Skills
In general, for admission to a DS course, the following qualifications are necessary –
- Degree – A graduation from the STEM stream.
- No coding experience is required.
- Mathematics – This subject is the heart of ML/DS and Data Analysis, where the model is created by processing mathematical algorithms’ data. In general, mathematics broadly covers topics in arithmetic, algebra, calculus, differentiation probability, statistics, geometry, and allied.
- Statistics – Statistical concepts will help you understand data, analyse, and derive a conclusion from the data.
- Data Visualisation – Access, retrieve data, and perform visualisation and presentation with R and Tableau.
- Exploratory Data Analysis – Explore Excel and databases to derive useful insights from the pool of data and learn from the data attributes and properties.
- Hypothesis Testing – Formulate and test hypotheses that are applied in case studies to solve real business problems.
- Programming Languages – Though coding is not the criteria for admission to DS courses, knowledge about programming languages, such as Java, Python, Scala, or equivalent, is highly recommended.
- Database – A good understanding of the databases is highly desirable.
The Science Behind Data
The Data Science field highlights the processes involving methods, algorithms, and systems to derive knowledge and intelligence from a pool of structured and unstructured data. Data Science caters to several data-driven initiatives, such as Data Mining, Big Data, Machine Learning, and Artificial Intelligence.
In greater detail, Data Science could be looked at as a concept that unifies statistics, analysis of data, and methodologies to analyse and make sense of the real phenomena with the help of data.
Data Science Syllabus
Educationalists designed a Data Science course syllabus to help make the students industry-ready to implement DS knowledge in the industry. The curriculum is also tuned to match the needs of the industry.
The syllabus focuses on specific areas, such as open-source tools, libraries, databases, SQL, Python, R, data visualisation, data analysis, and machine learning. The centric concept in the course follows the methodologies in data handling. It uses models based on systematically designed algorithms.
Major Tools and Programming Languages used in Data Science –
Most Jobs Expect a DS Professional to Have the Following Skills –
- A good grade and understanding of Statistics, Mathematics, Computer fundamentals, and Machine Learning.
- Expertise in one or more of the programming languages, preferably R or Python.
- Thorough understanding of databases.
- Exposure to Big Data tools, like Hadoop, Spark, and MapReduce.
- Experience in data wrangling, data cleaning, mining, visualisation, and reporting tools.
This is the time for aspirant students to decide on taking the right course in the Data Science stream. Assess your capabilities and decide on taking the courses that suit you the most. upGrad offers various courses in Data Science that make eligible aspirants industry-ready professionals in Data Science. The courses range from PG Diploma, PG Certification, to Masters.