Data Science Course Eligibility, Criteria, Syllabus & Skills

What Are Prerequisites Required to Take Data Science Course?

We know how data science and analytics are transforming businesses and helping them sustain in the complex business environment that has been worsened by the pandemic. Besides automation and efficiency, these digital technologies offer many benefits, which we have enlisted below.

  • Reduces intensive human labour
  • Enables quicker customer service using chatbots and different AI technologies
  • Enables quicker response to disaster

As the importance of data science and analytics is growing, this field offers numerous job opportunities and proves to be a great field to build your career. However, as a prerequisite, you need to have relevant knowledge and skill set, which you can easily acquire with a comprehensive course in data science.

In this article, we will discuss data science courses, skills required for inciting efficiency, and their growing importance in the current milieu. We will begin with learning the eligibility criteria for data science courses and then move on to skills required to excel in the professional realm and more.

What is Data Science?

Data science is the process of gaining knowledge through scientific and statistical methods and techniques. It is a multidisciplinary field that extracts knowledge from large sets of data. Moreover, it uses data for making informed business decisions, gauging market demand, understanding customer requirements, etc.

Data scientists, architects, analysts, statisticians, and others work in the field. It is believed that the demand for data science professionals is expected to rise in the forthcoming years. It is because of the integration and implementation of data science applications like Artificial intelligence (AI), machine learning (ML), and deep learning (DL) across sectors.

 

 

Who is a Data Scientist, And What Do They Do?

A data scientist is an individual who offers expertise at different phases of the data science process. They also collect, analyze, and interpret big data to draw deep insight. Here are some of the roles and responsibilities of a data scientist:

  • Gathering structured and unstructured data and drawing insights from it.
  • Identifying different data analytics processes required to interpret data collected through scientific and statistical methods.
  • Introducing a data-driven approach in the organization to attain automation, deep insight into different processes, and solve complex business problems.
  • Performing data science processes like cleaning, wrangling, interpreting, segregating, etc.
  • Communicating insights are drawn from the data science process to stakeholders.

In order to become a successful data scientist, aspirants take different undergraduate and post-graduate courses such as bachelor’s degrees or master’s degrees in data science, mathematics, statistics, or a similar field. These courses help develop the abilities and knowledge required to perform effective data science and analytics processes in a professional realm.
So, if you want to make a career in data science and analytics, it is imperative to take an advanced course to build a strong foundation. Therefore, let us walk you through the eligibility criteria for data science courses.

Who is Eligible for a Data Science Course?

The eligibility criteria for undertaking Emeritus India’s data science courses offered in collaboration with reputed institutes is as follows:

  • Anyone from a newcomer to a working professional can opt for a data science course.
  • It is believed that aspirants from backgrounds such as engineering, marketing, information technology, and similar fields can thrive in the industry after taking the course.
  • Graduates or students who have secured an aggregate score of 50% or more.

There is a misconception that only science students are eligible for data science courses. However, there is no stream-specific restriction; anyone interested in data science can undertake the course.

Experts state several instances when Bachelor of Business Administration (BBA) and Master of Business Administration (MBA) have taken the course and built prosperous careers as data scientists.

Detailed Information on Data Science Curriculum

The data science curriculum comprises subjects like mathematics, programming, statistics, data visualization and more. Below, we have described these subjects in brief:

● Mathematics
Most data science models are made on a simple mathematical formula. That’s why mathematics is a part of the data science curriculum.

● Programming
A data scientist must be well versed in different programming languages. For example, a trained data scientist can easily code algorithms and databases. Therefore, the data science curriculum lays a strong foundation in programming languages like Python, Java, C, C++, etc., and its uses in business.

● Probability and statistics
A clear understanding of various probability and statistical methods and techniques helps perform data visualization and segregation processes.

● Data visualization
Many data science courses help aspirants understand the basic fundamentals of data visualization. For the unversed, data visualization is the process of representing data in the form of a graph, images, and pie charts. It is a popular data analytical concept.

● Machine learning
Machine learning is a subsect of data science that makes smart and intelligent machines that can perform similar functions to that of a human brain. The subject educates aspirants about the meaning of technology, different types of machine learning systems, the benefits of modern technology, and others.

Now that you know the data science course’s eligibility and curriculum, let’s look at some of the skills that data scientists possess.

What Are the Skills Required to Become a Successful Data Scientist?

Data science professionals need to stay updated about the latest trends and skills in a rapidly evolving business environment. Some of the important data science skills that one should possess are:

1. Technical data science skills

  • Statistics
  • Programming and coding skills
  • Predictive modelling
  • Machine learning and deep learning
  • Data wrangling, cleansing, preparing

2. Non-technical data science skills

  • Excellent business acumen
  • Problem-solving skills
  • Critical thinking
  • Communication skills
  • Collaboration

Aspiring data scientists take numerous certificate courses to learn these skills. Emeritus India offers some of the best data science and analytics courses in partnership with reputed universities and colleges that help aspirants acquire these skills.

Courses on Data Science & Analytics Category