What is the eligibility for a data scientist?

The data science field is interdisciplinary. Data science involves processing large data sets and meeting different requirements. There are theories and techniques involved here, and they are derived from different fields, including:

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The demand for data science has been excellent lately. Many people have started looking for ways to upskill and learn subjects related to this area to handle the demand. Different industries are also taking data science seriously and are encouraging their staff to gain more skills to be competitive. Different learning institutions have also come in to offer courses designed for data science. 

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Demand for data science

Data science will keep growing resulting in a rise in the available job openings in the years to come. 

Some of the most prominent parts of the world where data science is prominent and developments visible are India and the United States. Data science is an appealing and employable field. Because of the demand, there has been a surge in courses offering skills and theories related to the field. 

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Eligibility

Engineers, IT, software, and marketing professionals all have the chance to take up data science programs. These classes can be taken part-time as well. 

Data science combines concepts like statistics, computer science, and mathematics. Students must have a degree in any of the following: 

• mathematics
• engineering
• technology
• science 

With such qualifications, learning is easy. In many areas, this is the eligibility criteria and is considered the minimum requirement for newcomers. Those with programming skills and knowledge, tend to thrive better in the field. Based on a student’s knowledge of programming, machine learning, and statistics, programming students can practically be experts in data science methods implementation in the world.

It is also possible for students coming from other streams, such as business studies, to enroll in relevant course areas in data science. For example, with degrees in business administration, such as MBA and BBA, business professionals are eligible to enroll in data science courses. 

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Data science professionals work as executives within the IT industries. In many cases, they are responsible for CRM reports creation, management information system (MIS), and data quality assessment that is business related. 

The other eligibility criteria to study data science are basic knowledge of statistics, computer science, and math. In addition, the students need to have fifty percent aggregate on the score sheet in high school. 

Students seeking a diploma in this field should possess MSc, MCA, BTech, and BE degrees. The main subjects, in this case, should be programming, computer, and statistics. Therefore, the students must have 50 percent or more to qualify for data science diploma courses. 

If you want a Ph.D., you need 55 percent in a postgraduate program. In addition, students who have a higher-than-average GPA are favored over those that don’t. This information tells us that the eligibility criteria for data science depend on the level you are interested in and how much knowledge and skills you possess in the core areas. 

The curriculum

Data science courses are often designed for certificate and PG-level graduates. However, different engineering colleges and technical institutes have introduced degree levels to instill skills and knowledge of data science as a field into their students. 

Subjects and skills needed in data science

There are different qualifications in data science. They include:

• Degree: Some data science courses demand the students to have at least a degree in STEM streams
• Coding: Generally, you do not need to have any prior coding skills
• Mathematics: math is one of the core subjects in data science and data analytics. Machine learning also involves math. The models are created using mathematical algorithms. Generally, mathematics covers allied, geometry, statistics, differential probability, calculus, algebra, and arithmetic. 
• Statistics: statistical concepts can be great at helping you analyze and understand data. This is the only way to reach valid conclusions based on data. 
• Data visualization: once data has been retrieved and processed, data visualization is needed to offer presentations based on different programs and formats. Data visualization makes it easier to understand data. 
• Exploratory data analysis: you need to explore databases and Excel to gain valuable insights into the data pool. It is the best way to learn from the data properties and attributes. 
• Hypothesis testing: data scientists must be capable of hypothesis formulation and testing. During studies, data scientists are exposed to case studies which prepare them for real business applications. 
• Programming languages: coding is not one of the data science admission criteria. With programming knowledge in languages like Scala, Python, and Java, breaking into data science is easier. Programming is highly recommended. 
• Database: having a good database understanding is desirable in data science. Mastering these skills will make you much better positioned to enter data science and thrive. 

Science behind data

Data science highlights different processes involving systems and algorithms to derive intelligence and knowledge from unstructured and structured data. It covers data-driven initiatives like:

• artificial intelligence
• machine learning
• big data
• data mining

Data science is a concept that unifies data analysis, statistics, and other methodologies that help analyze and derive sense from different situations using data. 

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Data science syllabuses are designed to prepare students to shine in the industry and be ready to face different challenges along the way. Implementing data science knowledge is crucial and must be done correctly for great results. Therefore, most courses are designed to match industry demands. 

Bottom line

Data science is a vast field that demands a lot of qualifications. You need to cover many topics in data science to truly grasp it.  The main components of data science include:  

If you are an aspiring student in data science, you need to pick the right path and stream. First, you should assess your capabilities and then take the right course to get the necessary qualifications. Courses can be from masters, PG certifications, and executive programs. Taking the first step is usually the hardest thing to do. If you are passionate about data science, you should know there are numerous opportunities available.